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-->",".gemini/skills/changelog/SKILL.md":"../../../commands/changelog.md",".gemini/skills/chaos-experiment/SKILL.md":"../../../commands/chaos-experiment.md",".gemini/skills/competitive-matrix/SKILL.md":"../../../commands/competitive-matrix.md",".gemini/skills/content-strategist/SKILL.md":"../../../agents/personas/content-strategist.md",".gemini/skills/cs-aeo/SKILL.md":"../../../agents/marketing/cs-aeo.md",".gemini/skills/cs-agile-product-owner/SKILL.md":"../../../agents/product/cs-agile-product-owner.md",".gemini/skills/cs-backend-engineer/SKILL.md":"../../../agents/engineering/cs-backend-engineer.md",".gemini/skills/cs-backend-review/SKILL.md":"../../../commands/cs-backend-review.md",".gemini/skills/cs-ceo-advisor/SKILL.md":"../../../agents/c-level/cs-ceo-advisor.md",".gemini/skills/cs-content-creator/SKILL.md":"../../../agents/marketing/cs-content-creator.md",".gemini/skills/cs-cto-advisor/SKILL.md":"../../../agents/c-level/cs-cto-advisor.md",".gemini/skills/cs-demand-gen-specialist/SKILL.md":"../../../agents/marketing/cs-demand-gen-specialist.md",".gemini/skills/cs-engineer-grill/SKILL.md":"../../../commands/cs-engineer-grill.md",".gemini/skills/cs-engineering-lead/SKILL.md":"../../../agents/engineering-team/cs-engineering-lead.md",".gemini/skills/cs-financial-analyst/SKILL.md":"../../../agents/finance/cs-financial-analyst.md",".gemini/skills/cs-frontend-engineer/SKILL.md":"../../../agents/engineering/cs-frontend-engineer.md",".gemini/skills/cs-frontend-review/SKILL.md":"../../../commands/cs-frontend-review.md",".gemini/skills/cs-fullstack-engineer/SKILL.md":"../../../agents/engineering/cs-fullstack-engineer.md",".gemini/skills/cs-fullstack-review/SKILL.md":"../../../commands/cs-fullstack-review.md",".gemini/skills/cs-growth-strategist/SKILL.md":"../../../agents/business-growth/cs-growth-strategist.md",".gemini/skills/cs-karpathy-reviewer/SKILL.md":"../../../agents/engineering/cs-karpathy-reviewer.md",".gemini/skills/cs-product-analyst/SKILL.md":"../../../agents/product/cs-product-analyst.md",".gemini/skills/cs-product-manager/SKILL.md":"../../../agents/product/cs-product-manager.md",".gemini/skills/cs-product-strategist/SKILL.md":"../../../agents/product/cs-product-strategist.md",".gemini/skills/cs-project-manager/SKILL.md":"../../../agents/project-management/cs-project-manager.md",".gemini/skills/cs-quality-regulatory/SKILL.md":"../../../agents/ra-qm-team/cs-quality-regulatory.md",".gemini/skills/cs-senior-engineer/SKILL.md":"../../../agents/engineering/cs-senior-engineer.md",".gemini/skills/cs-ux-researcher/SKILL.md":"../../../agents/product/cs-ux-researcher.md",".gemini/skills/cs-webinar-marketer/SKILL.md":"../../../agents/marketing/cs-webinar-marketer.md",".gemini/skills/cs-webinar/SKILL.md":"../../../commands/cs-webinar.md",".gemini/skills/cs-wiki-ingestor/SKILL.md":"../../../agents/engineering/cs-wiki-ingestor.md",".gemini/skills/cs-wiki-librarian/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fcs-wiki-librarian%2FSKILL.md -->",".gemini/skills/cs-wiki-linter/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fcs-wiki-linter%2FSKILL.md -->",".gemini/skills/cs-workspace-admin/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fcs-workspace-admin%2FSKILL.md -->",".gemini/skills/devops-engineer/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fdevops-engineer%2FSKILL.md -->",".gemini/skills/finance-lead/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ffinance-lead%2FSKILL.md -->",".gemini/skills/financial-health/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ffinancial-health%2FSKILL.md -->",".gemini/skills/flag-cleanup/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fflag-cleanup%2FSKILL.md -->",".gemini/skills/google-workspace/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fgoogle-workspace%2FSKILL.md -->",".gemini/skills/growth-marketer/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fgrowth-marketer%2FSKILL.md -->",".gemini/skills/karpathy-check/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fkarpathy-check%2FSKILL.md -->",".gemini/skills/okr/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fokr%2FSKILL.md -->",".gemini/skills/operator-audit/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Foperator-audit%2FSKILL.md -->",".gemini/skills/persona/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fpersona%2FSKILL.md -->",".gemini/skills/pipeline/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fpipeline%2FSKILL.md -->",".gemini/skills/plugin-audit/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fplugin-audit%2FSKILL.md -->",".gemini/skills/prd/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fprd%2FSKILL.md -->",".gemini/skills/product-manager/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fproduct-manager%2FSKILL.md -->",".gemini/skills/project-health/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fproject-health%2FSKILL.md -->",".gemini/skills/retro/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fretro%2FSKILL.md -->",".gemini/skills/rice/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Frice%2FSKILL.md -->",".gemini/skills/saas-health/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsaas-health%2FSKILL.md -->",".gemini/skills/seo-auditor/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fseo-auditor%2FSKILL.md -->",".gemini/skills/slo-design/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fslo-design%2FSKILL.md -->",".gemini/skills/solo-founder/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsolo-founder%2FSKILL.md -->",".gemini/skills/sprint-health/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsprint-health%2FSKILL.md -->",".gemini/skills/sprint-plan/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsprint-plan%2FSKILL.md -->",".gemini/skills/startup-cto/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fstartup-cto%2FSKILL.md -->",".gemini/skills/tc/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftc%2FSKILL.md -->",".gemini/skills/tdd/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftdd%2FSKILL.md -->",".gemini/skills/tech-debt/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftech-debt%2FSKILL.md -->",".gemini/skills/user-story/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fuser-story%2FSKILL.md -->",".gemini/skills/wiki-ingest/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-ingest%2FSKILL.md -->",".gemini/skills/wiki-init/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-init%2FSKILL.md -->",".gemini/skills/wiki-lint/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-lint%2FSKILL.md -->",".gemini/skills/wiki-log/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-log%2FSKILL.md -->",".gemini/skills/wiki-query/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-query%2FSKILL.md -->",".hermes/skills/claude-skills/skills-index.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.hermes%2Fskills%2Fclaude-skills%2Fskills-index.json -->",".vibe/skills/claude-skills/skills-index.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.vibe%2Fskills%2Fclaude-skills%2Fskills-index.json -->","CLAUDE.md":"# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Project Purpose\n\nThis is a **comprehensive skills library** for Claude AI and Claude Code - reusable, production-ready skill packages that bundle domain expertise, best practices, analysis tools, and strategic frameworks. The repository provides modular skills that teams can download and use directly in their workflows.\n\n**Current Scope:** 398 production-ready skills across 20 domains with 766 Python automation tools, 877 reference guides, 123 agents (cs-* + 7 personas), and 157 slash commands, distributed as 104 marketplace plugins. Headline counters are derived from the tree by `scripts/derive_counters.py` (run with `--check` to verify the docs still match). **v2.11.2 (current)** vendors **engineering/skillopt-sleep/** — started as a verbatim, byte-for-byte copy of `microsoft/SkillOpt`'s `skillopt_sleep` engine (stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), then received 23 targeted patches after ten rounds of adversarial review (see `engineering/skillopt-sleep/README.md`'s numbered \"Deviations from upstream\" list, the authoritative source — re-apply all 23 on re-vendor). Gives a local agent a nightly \"sleep cycle\": read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget. The heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) was deliberately **not** vendored — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit. Attribution preserved in `.claude-plugin/authoring-notes.json` + `LICENSE` + `README.md` (MIT, © Microsoft Corporation / Yifan Yang), following the same verbatim-vendor pattern as `loop-library/`. **Unreleased (post-v2.11.2, PR #961 merged)** adds the **agent-launcher/** top-level domain — a plugin re-implementation of Anthropic's `launch-your-agent` reference skill (Apache-2.0; independent, not a fork) for building **Claude Managed Agents (CMA)** in the user's own account. Every session starts with a goal (`./my-agent/goal.json`, surfaced by an opt-in `AGENT_LAUNCHER_SESSION=1` SessionStart hook + `/cs-goal`); `loop_compiler.py` compiles that goal into a **bounded grade→iterate loop** (CMA `user.define_outcome` self-grading, `max_iterations` 1..20), a **recurring POSIX-cron scheduled-deployment loop**, or a **single-pass interview→stage→launch workflow**. 6 skills (orchestrator `context: fork` + interview + stage-launch + grade-iterate + run-without-you + wrap-up), 18 stdlib-only deterministic scaffolder tools (NO network/API calls — live launches emitted as BYOK curl that never prints the key), 4 agents, 8 `/cs-*` commands, opt-in hooks, 5 shared references, 4 assets; validators enforce CMA limits (≤20 skills/session, ≤8 memory stores, depth-1 multiagent, `max_iterations` ≤20, ≤1000 deployments/org). Distinct from `engineering/agent-harness` (generic bounded loop over any domain) and `engineering/write-a-skill` (authors Claude Code skills, not CMAs). **Unreleased (post-v2.11.2)** ships the **productivity coverage expansion** — public audit record `audit/productivity-2026-07/` (all 7 legacy skills scored, 24/24 scripts smoke-tested, coverage map vs the personal-productivity canon) + 3 gap-filling plugins, each with a cs-* agent, /cs-* commands, 3 stdlib scripts and 3 cited references: **weekly-review** (GTD loop; review-gate refuses COMPLETE while a mandatory GET CURRENT step is missing), **deep-work** (time-block planner refusing >4h deep demand, shallow-work budget auditor, focus-session logger), **meetings** (MEET/ASYNC/NOT-READY cost gate, outcome-required agenda builder, action-item extractor with ORPHAN/NO-DUE flags). **Unreleased (post-v2.11.1)** added **productivity/fable-goal** — converts a rambling description of a desired outcome into one polished, copy-paste `/goal` prompt for a fresh autonomous session (ported from `duncan-buildroom/freeskills`). **v2.11.1 (complete)** upgrades **product-team/** and **project-management/** into agent-harness domains: both prose routers rebuilt as `context: fork` orchestrators with deterministic goal routers (exit-code route/ask/refuse), a Jira MCP snapshot bridge (Kanban-Guide-2025 flow metrics + seeded Monte Carlo forecasts, verified end-to-end into velocity_analyzer), a delegation-governance loop gate (human owner / reviewer / machine-checkable acceptance / close refusal), a Torres continuous-discovery cadence tracker + Opportunity Solution Tree linter, cs-pm-orchestrator + cs-product-orchestrator agents, and /cs-pm|grill-pm|pm-loop + /cs-product|grill-product|product-loop commands — plus the public audit record `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria). **v2.9.0 (complete)** added the **research-ops/** top-level domain — enterprise Research Operations (orchestrator + clinical-research + research-finance + market-research + product-research), the managed counterpart to the academic research/ domain, with `context: fork` orchestration and a Matt Pocock \"Forcing-question library\" in every SKILL.md plus `/cs-grill-research-ops`. **v2.8.0 (complete)** added 2 new top-level domains — **business-operations/** (7 internal-ops skills: orchestrator + process-mapper + vendor-management + capacity-planner + internal-comms + knowledge-ops + procurement-optimizer) and **commercial/** (8 per-deal-economics skills: orchestrator + pricing-strategist + deal-desk + partnerships-architect + channel-economics + commercial-policy + rfp-responder + commercial-forecaster) — with orchestrator skills using `context: fork` for chaining, Matt Pocock docs-anchored \"Forcing-question library\" in every SKILL.md, plus `/cs-grill-bizops` and `/cs-grill-commercial`. **v2.8.2** adds a productivity-shaped `handoff` skill (sibling to engineering/handoff) inspired by Matt Pocock — first-run setup with configurable save location, redaction linter, SessionStart + SessionEnd hooks, fidelity self-check, `--refresh` flag. **v2.8.1** upgraded the engineering role-skills (senior-fullstack / senior-frontend / senior-backend) with karpathy-coder + Matt Pocock decision engines + per-role forcing questions. v2.7.3 ports `alirezarezvani/aeo-box` — AEO (Answer Engine Optimization) skill into marketing-skill/ + security-guidance PreToolUse hook into engineering/. v2.7.0 added 13 Path-B skills across 3 top-level domains (productivity, marketing, research). v2.6.0 added 4 Matt Pocock-derived productivity skills.\n\n**Key Distinction**: This is NOT a traditional application. It's a library of skill packages meant to be extracted and deployed by users into their own Claude workflows.\n\n## Maintainer-Local Folders (gitignored)\n\nThe following exist on the maintainer's disk but are excluded from the public GitHub tree so cloners only see production skill packages:\n\n- `documentation/` — sprint plans, strategy, implementation roadmaps\n- `eval-workspace/` — Tessl evaluation outputs\n- `megaprompts/` — pre-skill draft specs (Path-B source material)\n- `tests/` — pytest suite (run locally; not in CI)\n- `.autoresearch/` — autoresearch agent workspace\n- `AUDIT_REPORT.md` — internal audit snapshots\n\n**Distinct from the above:** the top-level `audit/` directory (e.g.\n`audit/newgen-2026-06/`) is an **intentional, public** audit record — rubric +\nper-domain reports with per-skill verification criteria that follow-up PRs use\nas acceptance gates. It is excluded from headline counters by\n`scripts/derive_counters.py`, but it is committed and visible to cloners.\n`AUDIT_REPORT.md` (gitignored, above) is the older internal-snapshot format.\n\nIn-repo references to paths under these folders (e.g. `documentation/implementation/...`) resolve locally for the maintainer but appear as dead links on GitHub. This is intentional.\n\n## Navigation Map\n\nThis repository uses **modular documentation**. For domain-specific guidance, see:\n\n| Domain | CLAUDE.md Location | Focus |\n|--------|-------------------|-------|\n| **Agent Development** | [agents/CLAUDE.md](agents/CLAUDE.md) | cs-* agent creation, YAML frontmatter, relative paths |\n| **Marketing Skills** | [marketing-skill/CLAUDE.md](marketing-skill/CLAUDE.md) | Content creation, SEO, ASO, demand gen, campaign analytics |\n| **Product Team** | [product-team/CLAUDE.md](product-team/CLAUDE.md) | RICE, OKRs, user stories, UX research, SaaS scaffolding |\n| **Engineering (Core)** | [engineering-team/CLAUDE.md](engineering-team/CLAUDE.md) | Fullstack, AI/ML, DevOps, security, data, QA tools |\n| **Engineering (POWERFUL)** | [engineering/](engineering/) | Agent design, RAG, MCP, CI/CD, database, observability |\n| **C-Level Advisory** | [c-level-advisor/CLAUDE.md](c-level-advisor/CLAUDE.md) | CEO/CTO strategic decision-making |\n| **Project Management** | [project-management/CLAUDE.md](project-management/CLAUDE.md) | Atlassian MCP, Jira/Confluence integration |\n| **RA/QM Compliance** | [ra-qm-team/CLAUDE.md](ra-qm-team/CLAUDE.md) | ISO 13485, MDR, FDA, GDPR, ISO 27001 compliance |\n| **Business & Growth** | [business-growth/CLAUDE.md](business-growth/CLAUDE.md) | Customer success, sales engineering, revenue operations |\n| **Finance** | [finance/CLAUDE.md](finance/CLAUDE.md) | Financial analysis, DCF valuation, budgeting, forecasting, SaaS metrics |\n| **Research Operations** | [research-ops/CLAUDE.md](research-ops/CLAUDE.md) | Clinical study design, R&D finance, market research, product research (enterprise counterpart to academic research/) |\n| **Markdown → HTML** | [markdown-html/CLAUDE.md](markdown-html/CLAUDE.md) | Markdown-to-interactive-HTML converter (orchestrator + design-system foundation; md-document/review/slides v2.10.1). Inspired by Shihipar's \"Claude Code HTML output\" essay |\n| **Agent Launcher** | [agent-launcher/CLAUDE.md](agent-launcher/CLAUDE.md) | Claude Managed Agent (CMA) launcher — session-goal orchestrator + interview / stage-launch / grade-iterate / run-without-you / wrap-up; deterministic BYOK-curl scaffolders; bounded grade→iterate + cron deployment loops. Re-implements anthropics/launch-your-agent (Apache-2.0) |\n| **Standards Library** | [standards/CLAUDE.md](standards/CLAUDE.md) | Communication, quality, git, security standards |\n| **Templates** | [templates/CLAUDE.md](templates/CLAUDE.md) | Template system usage |\n\n## Architecture Overview\n\n### Repository Structure\n\n```\nclaude-code-skills/\n├── .claude-plugin/            # Plugin registry (marketplace.json)\n├── agents/                    # 32 standalone agents (cs-* + 7 personas); 51+ cs-* agents repo-wide\n├── commands/                  # slash commands (changelog, tdd, saas-health, prd, code-to-prd, plugin-audit, sprint-plan, slo-design, etc.); 87+ repo-wide\n├── engineering-team/          # 51 core engineering skills + Playwright Pro + Self-Improving Agent + Security Suite\n├── engineering/               # 81 POWERFUL-tier advanced skills (incl. AgentHub, autoresearch-agent, self-eval, llm-wiki, tc-tracker, ship-gate, slo-architect, write-a-skill, caveman, grill-me, handoff, agent-harness)\n├── product-team/              # 17 product skills (incl. apple-hig-expert) + Python tools\n├── marketing-skill/           # 46 marketing skills (8 pods) + Python tools\n├── c-level-advisor/           # 66 C-level advisory skills (full C-suite + founder-mode agents + orchestration)\n├── project-management/        # 9 PM skills + bundled Atlassian Remote MCP (.mcp.json)\n├── ra-qm-team/                # 18 RA/QM compliance skills\n├── compliance-os/             # 9 compliance-OS skills\n├── business-growth/           # 5 business & growth skills + Python tools\n├── business-operations/       # 7 internal-ops skills (orchestrator + 6 sub-skills)\n├── commercial/                # 8 per-deal-economics skills (orchestrator + 7 sub-skills)\n├── finance/                   # 4 finance skills + Python tools\n├── research/                  # 8 academic research skills (orchestrator + 7 specialists)\n├── research-ops/              # 5 research-ops skills (orchestrator + clinical-research + research-finance + market-research + product-research)\n├── markdown-html/             # 2 markdown-to-HTML skills v2.10.0 foundation (orchestrator + design-system); md-document/review/slides land in v2.10.1\n├── agent-launcher/            # 6 CMA-launcher skills (session-goal orchestrator + 5 phase skills; 18 BYOK-curl scaffolder tools, opt-in SessionStart goal hook)\n├── eval-workspace/            # Skill evaluation results (Tessl)\n├── standards/                 # 5 standards library files\n├── templates/                 # Reusable templates\n├── docs/                      # MkDocs Material documentation site\n├── scripts/                   # Build scripts (docs generation)\n└── documentation/             # Implementation plans, sprints, delivery\n```\n\n### Skill Package Pattern\n\nEach skill follows this structure:\n```\nskill-name/\n├── SKILL.md              # Master documentation\n├── scripts/              # Python CLI tools (no ML/LLM calls)\n├── references/           # Expert knowledge bases\n└── assets/               # User templates\n```\n\n**Design Philosophy**: Skills are self-contained packages. Each includes executable tools (Python scripts), knowledge bases (markdown references), and user-facing templates. Teams can extract a skill folder and use it immediately.\n\n**Key Pattern**: Knowledge flows from `references/` → into `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\n## Git Workflow\n\n**Branch Strategy:** feature → dev → main (PR only)\n\n> **⛔ HARD RULE — PR TARGET IS ALWAYS `dev`, NEVER `main`.**\n> Every PR (human or AI-created) must use `--base dev`. Nothing merges into `main`\n> directly — `main` only receives periodic `dev → main` promotion PRs opened by the\n> maintainer. If you find a PR targeting `main`, retarget it to `dev` before review.\n> AI agents (Claude Code included): set the base branch explicitly when creating PRs;\n> never rely on the repository default branch.\n\n**Branch Protection Active:** Main branch requires PR approval. Direct pushes blocked.\n\n### Quick Start\n\n```bash\n# 1. Always start from dev\ngit checkout dev\ngit pull origin dev\n\n# 2. Create feature branch\ngit checkout -b feature/agents-{name}\n\n# 3. Work and commit (conventional commits)\nfeat(agents): implement cs-{agent-name}\nfix(tool): correct calculation logic\ndocs(workflow): update branch strategy\n\n# 4. Push and create PR to dev\ngit push origin feature/agents-{name}\ngh pr create --base dev --head feature/agents-{name}\n\n# 5. After approval, PR merges to dev\n# 6. Periodically, dev merges to main via PR\n```\n\n**Branch Protection Rules:**\n- ✅ Main: Requires PR approval, no direct push\n- ✅ Dev: Unprotected, but PRs recommended\n- ✅ All: Conventional commits enforced\n\nSee [documentation/WORKFLOW.md](documentation/WORKFLOW.md) for complete workflow guide.\nSee [standards/git/git-workflow-standards.md](standards/git/git-workflow-standards.md) for commit standards.\n\n## Development Environment\n\n**No build system or test frameworks** - intentional design choice for portability.\n\n**Python Scripts:**\n- Use standard library only (minimal dependencies)\n- CLI-first design for easy automation\n- Support both JSON and human-readable output\n- No ML/LLM calls (keeps skills portable and fast)\n\n**If adding dependencies:**\n- Keep scripts runnable with minimal setup (`pip install package` at most)\n- Document all dependencies in SKILL.md\n- Prefer standard library implementations\n\n## Current Version\n\n**Version:** v2.14.1 (audit fix release: all 104 plugins bumped so `claude plugin update` reaches existing installs, new version-bump gate G11, category-scoped Codex installer, `${CLAUDE_PLUGIN_ROOT}` script paths, productivity handoff renamed session-handoff. See CHANGELOG.md [2.14.1].)\n\n**Previously: v2.14.0** (audit skills release: agent-regression-evals, coding-agent-rollout and month-end-close plugins, open-source-first youtube-full, claude-coach plugin renamed to power-user-coach with a one-time reinstall. See CHANGELOG.md [2.14.0].)\n\n**Previously: v2.13.0** (October triage and quality-audit release: runnable command names, self-contained c-level-agents/compliance-os, hivemind as an opt-in plugin, six new skills from the community backlog. See CHANGELOG.md [2.13.0].)\n\n**Previously: v2.12.0** (consolidated release — 20 domains, 380 skills; full reported-issue triage sweep; first tag since v2.9.0. See CHANGELOG.md [2.12.0].)\n\n---\n\n**Previously: v2.11.2** (skillopt-sleep — vendored nightly self-improvement plugin from microsoft/SkillOpt)\n\n**v2.11.2 highlights — engineering/skillopt-sleep/:**\n\nVendors `engineering/skillopt-sleep/` — a byte-for-byte start from [microsoft/SkillOpt](https://github.com/microsoft/SkillOpt)'s `skillopt_sleep` engine (32 files, stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), following the same verbatim-vendor pattern as `loop-library/`. Gives a local agent a nightly gated self-improvement cycle: read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget.\n\n- **Deliberately not vendored:** the heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit.\n- **23 deviations from upstream (6 cosmetic, 17 safety/hardening)**, found across ten rounds of adversarial code review rather than assumed safe from the surface docs. The **numbered list in `engineering/skillopt-sleep/README.md`'s \"Deviations from upstream\" section is the single source of truth** — the plugin's `authoring-notes.json` `attribution.derivation_note` and this bullet are both summaries of it, kept in sync by hand; if any of the three ever disagree on the count again, README.md wins. Highlights: `redact_secrets()` now covers every artifact that goes live or persists — `proposed_SKILL.md`/`proposed_CLAUDE.md`, the cross-night task archive (`state.json`), `report.md`/`report.json` (previously only `diagnostics.json` was scrubbed, despite `report.md` being the file the SKILL.md's own workflow tells a human to read *first*), and — the gap that survived seven review rounds because every earlier fix was file-level — the CLI's own `cmd_run`/`cmd_harvest` console/`--json`/`--output` output, which read the same unredacted in-memory `Report`/`TaskRecord` objects and (via `scheduler.py`'s cron redirect) could leak straight into `cron.log`; the generated crontab line is fully `shlex.quote()`-d including the `extra` flags param, and `cron.log` itself is now `chmod 600` (previously uncovered by the state/staging chmod pass); `scheduler.py`'s per-project cron-line marker match is now anchored on end-of-line rather than a bare substring test, closing a real bug where scheduling/unscheduling one project could silently drop a sibling project's job whose path happened to be a prefix of it; the previously-dead `max_tokens_per_night` config key now sizes `dream_rollouts` down via the engine's own `plan_depth()` heuristic; a hardcoded internal Azure OpenAI backend (5 internal-looking endpoint hostnames + a Managed Identity client ID) was removed rather than carried forward; tool-shim names reachable via `--tasks-file` are now validated against a safe-identifier allowlist before use as a filename or shell text; `commands/skillopt-sleep.md` now tells the agent to confirm with the user before `schedule` (which installs a real crontab entry immediately, unlike every other action); every directory/file `state.py`/`staging.py` create is `chmod 0700`/`0600` rather than left at the world-readable process umask default.\n- One documented, opt-in exception to CLAUDE.md's \"no LLM calls in scripts\" anti-pattern (see that section) — `backend.py`'s `claude`/`codex` backends shell out to those CLIs only when a non-`mock` backend is explicitly selected.\n- Registered as its own installable marketplace plugin; **counters:** skills 358 → 359; tools 603 → 635; refs 732 (unchanged); commands 110 → 111; plugins 84 → 85 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**v2.14.0 — three audit-proposed skills (agent-regression-evals, coding-agent-rollout, month-end-close):**\n\nBuilt from the October quality audit's new-skill proposals, ranked by impact on teams. Each is a\nstandalone plugin mirrored into its domain bundle (`engineering/skills/`, `finance/skills/`), with\na cs-* agent, two `/cs-*` commands, stdlib scripts and three cited references; all three SKILL.md\nfiles pass the write-a-skill checklist. Evaluated with skill-creator (with-skill vs no-skill, one\nrealistic prompt each): 21/21 vs 17/21 assertions. The baseline's misses are why the skills exist:\nit called `bypassPermissions` in a project file \"YOLO mode for every engineer\" and `mcp__*` in\nallow \"all tools\", both of which Claude Code ignores, and it used a \"typical\" flux threshold\nwithout asking for the entity's policy.\n\n- **The evals changed the scripts, not just the scores.** Four fixes came from reading the runs:\n  the MCP inventory now scans `args` and `url` for credentials (a `postgresql://user:pass@`\n  string in `args` slipped past it); the reconciliation matcher names a carried-in\n  opening-balance difference before guessing transposition; the flux analyzer takes `--reviewer`\n  and blocks lines the reviewer owns; the flake detector warns when every failure lands in late\n  trials, the signature of state shared between trials.\n- **Rules these encode:** never compare single trials and never quarantine a critical case\n  (agent-regression-evals); policy that must hold for everyone goes in managed settings, not the\n  repo file (team-rollout); a reconciliation is a proof, a signature is not evidence of review\n  (PCAOB SAPA 11), and materiality thresholds are the entity's policy (month-end-close).\n- **Counters:** skills 392 → 398; tools 746 → 766; refs 859 → 877; agents 120 → 123;\n  commands 151 → 157; plugins 101 → 104 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/deep-learning-book (companion, not compilation):**\n\nNew `engineering/deep-learning-book/` plugin: a study companion for *Deep Learning* by\nGoodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org.\nRequested as \"convert this book into a skill\"; built as a **companion** instead, and the\nreasoning is the reusable part.\n\n- **Why not `book-to-skill`.** That skill's rights gate refuses a `shareable` package without\n  `public-domain` / `open-license` / `internal-docs` / `author-permission` — none applies to an\n  MIT Press title whose own site states the HTML-only format exists as a friction against\n  copying under the authors' contract — and its `rights_and_provenance.md` lists publishing a\n  compiled skill of a copyrighted book to a public marketplace under **Do not**. Its hard rule 1\n  also forbids scraping a book from the web, so the pipeline could not have run against a URL.\n  **The rule this sets:** when a user asks to convert a copyrighted work into a *shareable*\n  skill, build a companion that indexes and updates the source, not a compilation that\n  reproduces it; compile only when the gate clears, and keep the output local when it does not.\n  Recorded in `skills/deep-learning-book/references/rights_and_use.md`.\n- **What it is.** The compiled-skill *shape* (master SKILL.md at ~2.0k tokens with a chapter\n  index and topic index, `chapters/ch01..ch20`, glossary, patterns, cheatsheet) filled with\n  original synthesis — no passages, figures, or per-paragraph paraphrase — each chapter file\n  linking to the official free chapter. Passes `book_to_skill`'s own `book_skill_validator.py`\n  clean and every file is inside `token_budget_estimator.py`'s caps.\n- **The differentiator is the delta layer.** A static compilation freezes a source at its\n  publication date; this one dates it. Every chapter carries \"What changed after 2016\", and\n  `references/book_to_2026_delta.md` gives five corrections with primary citations and per-claim\n  confidence levels: double descent qualifying Ch 5's U-curve, AdamW splitting weight decay from\n  L2 (Ch 7 treats them as interchangeable), transformers displacing Ch 10's recurrence (keep the\n  gradient analysis, drop the architecture advice), diffusion growing out of Ch 14's denoising\n  autoencoders and Ch 18's score matching, and self-supervised learning vindicating Ch 15 while\n  replacing every method it names. Two claims are marked contested rather than propagated (batch\n  norm's \"internal covariate shift\" mechanism; the strong lottery-ticket form) and two named as\n  folklore. The stated rule: **the conflict is almost always in the recommendation, not the\n  analysis.**\n- **4 stdlib tools, each with a real refusal.** `reading_path_planner.py` (goal → prerequisite\n  closure over the book's actual dependency graph, ordered, priced in weeks; exit 3 for a goal\n  the book does not cover, naming what does; exit 4 with forcing questions when unroutable),\n  `training_diagnostics.py` (Ch 11's rules in priority order, so a NaN is never reported as\n  overfitting; exit 4 rather than diagnosing with no instruments), `capacity_planner.py`\n  (regularization ladder in cost order, with \"shrink the model\" pushed **last** in the\n  overparameterized regime per double descent; exit 4 on a val-below-train split),\n  `model_arithmetic.py` (params/FLOPs/activation memory per example for conv, linear, MHA and\n  LSTM/GRU stacks; exit 5 naming the layer whose shapes do not connect).\n- 4 references citing 7-8 sources each, 3 assets, `cs-deep-learning-tutor` agent, `/cs-deep-learning`\n  + `/cs-dl-reading-path` + `/cs-dl-diagnose`. **Counters:** skills 386 → 387; tools 723 → 727;\n  refs 838 → 842; agents 116 → 117; commands 146 → 149; plugins 97 → 98 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — marketing/linkedin (organic LinkedIn presence, platform rules in code):**\n\nNew `marketing/linkedin/` plugin answering [discussion #934](https://github.com/alirezarezvani/claude-skills/discussions/934), which asked for a strategic assistant for growing a LinkedIn presence organically rather than a post generator. Six skills (orchestrator + profile + strategy + content + engagement + analytics), 17 stdlib-only tools, 15 references, 2 agents, 8 `/cs-*` commands.\n\n- **The design constraint is the differentiator.** No LinkedIn credentials, no API calls, no scraping, nothing auto-sent — automated posting/connecting/commenting are prohibited by LinkedIn's User Agreement §8.2, and a restricted account ends a compounding asset. `linkedin_policy_gate.py` runs before any drafting and refuses seven request classes (automation, scraping, engagement pods, bulk messaging, fake identity, fabricated proof, named third-party automation platforms), each carrying the policy anchor **and a compliant substitute** — the gate never just says no. Orchestrator is `context: fork` with a deterministic five-lane router (route 0 / ask 2 / no-signal 3) and cross-lane prerequisites.\n- **Refusals are real, not warnings.** Cadence under 90 min/week returns a comment-only plan rather than a schedule that dies in week five; a newsletter whose six-month cost exceeds the budget is refused before the promise is made; an experiment needing more posts than a quarter allows is reported infeasible rather than quietly re-sized; the pattern miner refuses to test anything below 10 posts and reports `NOTHING_SURVIVED` as a finding.\n- **Evidence discipline — two popular claims corrected rather than propagated** (the `andreessen` precedent). (1) \"A personalised note triples connection acceptance (~45% vs ~15%)\" is not supported by the largest samples, which show acceptance close to identical either way (~26.4%); what a note actually moves is the **post-accept reply rate** (~5.4% → ~9.4%) — which is why `outreach_message_builder.py` refuses an ask in a first-touch note. (2) The ~19% in-body external-link reach reduction has **never been confirmed by LinkedIn as a penalty** and has a plausible dwell-time explanation, so it is a warning, not a block. Every reference carries per-claim confidence levels (🟢 LinkedIn-official / 🟡 third-party study / 🔴 folklore, named as folklore).\n- **Accessibility is a blocking lint finding, not a footnote.** Unicode pseudo-bold (the output of \"bold text generators\") fails the linter: screen readers announce those characters as mathematical symbols and LinkedIn search does not index them as words. Engagement bait is also blocking, per the Professional Community Policies. `pattern_miner.py` adds multiple-comparisons accounting and mirrored-candidate de-duplication that no comparable tool implements.\n- All six SKILL.md files are a full **6/6 PASS** on the write-a-skill checklist (binding for post-v2.6.0 skills). Every tool supports `--help`/`--sample`/`--output json` with typed exit codes. **Counters:** skills 380 → 386; tools 706 → 723; refs 823 → 838; agents 114 → 116; commands 138 → 146; plugins 96 → 97 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/spinning-up-deep-rl (the first book compiled by book-to-skill):**\n\nThe first knowledge-base plugin produced end-to-end by `engineering/book-to-skill`, from OpenAI's\n[Spinning Up in Deep RL](https://spinningup.openai.com/) (MIT, © 2018 OpenAI; primarily developed by\nJoshua Achiam). Source obtained by cloning `openai/spinningup` and compiling its `docs/` reStructuredText\ntree — 38 files, ~37k words, ~49K tokens — through the full pipeline: `extract_document.py --mode technical`\n→ analysis → 20 chapter files → glossary / patterns / cheatsheet → master `SKILL.md` → `book_skill_validator.py`\n→ `skill_plugin_emitter.py`. Validator passes clean **in `--strict` mode**; every file is inside budget\n(resident core 2,101 / 4,000 tokens; 20 chapters averaging ~1,256 tokens each, loaded on demand).\n\n- **Rights basis is `open-license`, not fair use.** The emitter's Step-11 gate refuses a shareable package\n  without one; MIT permits derivative distribution. Upstream's notice is reproduced in full in the plugin's\n  `LICENSE` alongside this package's own, and the README names the source, the author and the commit-era —\n  a sidecar JSON is not a license notice.\n- **Chapter structure follows the source's own `toctree`**, not a heading scan: user documentation (ch01-06),\n  Introduction to RL Parts 1-3 (ch07-09), resources — the researcher essay, key papers, exercises, benchmarks\n  (ch10-13), one chapter per algorithm in lineage order (ch14-19: VPG → TRPO → PPO, DDPG → TD3 → SAC), and the\n  logger/MPI/ExperimentGrid utilities (ch20).\n- **The cheatsheet carries what a glossary cannot**: the debug-turnaround threshold (under 5 minutes), the seed\n  minimums (3, ideally 10+), the benchmark network defaults that differ by algorithm family ((64,32)/tanh\n  on-policy vs (256,256)/relu off-policy), and Spinning Up's own **parity disclosure** — DDPG/TD3/SAC are\n  research-grade, VPG/TRPO/PPO are not, and the docs say to use OpenAI Baselines for those instead.\n- **One emitter defect found and fixed in the same change.** `skill_plugin_emitter.py` was writing its `source`\n  provenance block into `plugin.json`, which this repo's own `scripts/check_plugin_json.py` hard-fails\n  (issue #954 — Claude Code rejects the whole manifest on any unrecognized key). Its inline comment claimed\n  `source`/`attribution` were \"approved extension fields,\" which had been true and no longer was. The manifest\n  builder now emits spec fields only and a new `_authoring_notes()` writes `.claude-plugin/authoring-notes.json`.\n  Every future `book-to-skill` package gets a manifest that passes CI; the one emitted here was the first to\n  catch it.\n- **write-a-skill checklist: 4/6, and the two remaining are structural, not defects.** A compiled\n  knowledge base is not a hand-authored instruction skill. (2) \"SKILL.md under 100 lines\" conflicts\n  with the format's mandatory 20-row Chapter Index plus Topic Index; the binding budget here is\n  `book_skill_validator.py`'s 4,000-token cap, and the file sits at 2,101 — trimming to 100 lines\n  would delete exactly the navigation that `budget.over_cap` exists to protect. (3) \"no\n  time-sensitive info\" fires on \"January 2020\", which is a **provenance pin on a frozen source**\n  (Spinning Up's last update), not a staleness claim — removing it would make the skill less honest\n  about what it covers. (5) was a real gap and is fixed: the resident core now carries a worked\n  invocation block.\n- **No new Python tools** — a compiled knowledge base ships notes, not scripts, so the tools and references\n  counters are unchanged. **Counters:** skills 387 → 388; agents 117 → 118; commands 149 → 150; plugins\n  98 → 99, on top of `deep-learning-book` which merged into `dev` first (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/skill-doctor (grade the agent setup from real sessions):**\n\nRebuild of [warpdotdev/common-skills](https://github.com/warpdotdev/common-skills)' `skill-doctor` (MIT, © Denver Technologies, Inc., pinned at `f3b58c81`) as a full plugin. Harvests the last N days of local Claude Code / Codex sessions scoped to one repo, has the agent judge each condensed transcript against two verbatim-preserved rubrics (efficiency, code quality — labels only, closed tables), measures which installed skills actually fired, and proposes only the skill edits the evidence justifies — one local, self-contained HTML report; nothing is ever uploaded.\n\n- **22 numbered deviations from upstream** — `engineering/skill-doctor/README.md`'s list is authoritative; `authoring-notes.json` summarizes it. Headline additions: **`score_aggregator.py`, a deterministic gate with no upstream counterpart** — upstream let the scoring LLM average its own scores and assemble `report.json`; here labels map to scores via embedded tables mirroring the rubrics, scores for unsampled sessions are rejected as fabrications, reasons are length-checked, and a suggestion that cites no scored session id (or carries no diff) fails at exit 4. **Collector hardening:** always-on 12-pattern secret redaction before any transcript touches disk (no off switch; per-label counts land in the inventory and report), `chmod 0700/0600` artifacts, plugin-layout skill discovery (`*/skills/*/SKILL.md`), slash-command usage detection mined from `<command-name>` markers before the injection filter drops them. **Renderer replaced:** zero JavaScript (upstream embeds a 1,531-line prebuilt diff bundle + canvas share-image) — pure-CSS diff coloring, native `<details>` collapse, `prefers-color-scheme`, print-to-PDF; Warp branding and the `warp.dev/factories` CTA removed. **Dropped:** the Warp `warp.sqlite` source and its 392-line hand-rolled protobuf decoder (unauditable vendored binary-format code; Warp users should run upstream).\n- Preserved verbatim: both scoring rubrics (`scorers/`) and the skill-improvement filing bar (\"would a competent agent with the current instructions still fail this way?\"), now §1–§2 of `references/skill_edit_governance.md`. Zero suggestions clearing the bar is a valid, reportable success; proposed edits stay staged under the run's scratch dir until an explicit per-skill yes, and proposals for this repo's skills must pass write-a-skill's 6-item checklist.\n- 3 stdlib tools (all `--help`/`--sample`/`--output json`, typed exit codes; the pipeline smoke-tests end-to-end from `--sample` fixtures including a planted fake secret), 3 references citing 7 sources each, 3 handoff-shape assets, `cs-skill-doctor` agent, `/cs-skill-doctor` command. SKILL.md is a full 6/6 PASS on the write-a-skill checklist. Distinct from `skillopt-sleep` (automated nightly loop; this is one interactive graded pass), `write-a-skill` (authors from expertise; this improves from evidence), and self-eval (grades the current session; this grades a window). **Counters** (this branch merged `dev` after `agent-memory` landed, so these deltas sit on top of it): skills 378 → 379; tools 703 → 706; refs 820 → 823; agents 110 → 111; commands 130 → 131; plugins 95 → 96 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/book-to-skill (document → knowledge-base skill → plugin):**\n\nDerived from [virgiliojr94/book-to-skill](https://github.com/virgiliojr94/book-to-skill) (MIT). Compiles a book, documentation folder, or spec collection (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into an agent skill: a resident master `SKILL.md` (core frameworks + chapter index + topic index, capped at 4k tokens) plus on-demand `chapters/chNN-*.md`, `glossary.md`, `patterns.md`, and a decision `cheatsheet.md`. The agent reads the core, then one chapter — never the whole source again.\n\n- **Vendored close to verbatim:** the extraction library (`scripts/book_to_skill/` — config, exceptions, sanitize, dependencies, utils + 7 per-format parsers) keeps upstream's format chains, chapter detection across Latin/Roman/Chinese/Thai/Korean heading styles, invisible-Unicode (Trojan Source) sanitization and DOCX entity-expansion guard.\n- **26 numbered deviations from upstream** — the list in `engineering/book-to-skill/README.md` is authoritative; the plugin's `authoring-notes.json` `attribution.derivation_note` summarizes it. Highlights: (5) `--install-missing` now defaults to `report` — it prints the pip command and uses the stdlib fallback instead of upstream's TTY prompt that runs `pip install` into the caller's environment; (6) a **rights gate** — `skill_plugin_emitter.py --distribution shareable` refuses without `--rights` from `public-domain|open-license|internal-docs|author-permission`, with `fair-use` deliberately excluded (a defence, not a licence); (10) the two upstream validators merged into one four-family gate, adding **budget** and **index** families — dead chapter links, unindexed chapter files and dangling topic refs are the failure that silently breaks navigation while the skill still looks complete, and upstream had no check for it; (11) folded YAML scalars now parse, so a wrapped description no longer under-reports its length past the 1024-char cap; (12) `discovery_tax.py` → `token_budget_estimator.py` with the optional `tiktoken` path dropped, a post-flight budget audit added, and an explicit **worth-converting verdict** that says \"just read it\" when the source is under ~3× the compiled skill.\n- **Repo-native addition with no upstream counterpart — Step 11 / `/cs-book-to-plugin`:** upstream stops at a bare folder in `~/.claude/skills/`, which this library cannot route to. `skill_plugin_emitter.py` wraps a compiled skill as a full plugin package (manifest + `cs-<slug>` agent + `/cs-<slug>` command + README) and prints the marketplace entry; it never edits `marketplace.json` itself, and refuses to wrap a skill carrying validation errors.\n- **Cross-linked into `engineering/write-a-skill`** (\"author first, compile second\" — that skill authors from expertise in your head, this one compiles from a document on disk).\n- 4 stdlib-only tools (all `--help` / `--sample` / `--output json`), 5 references citing 7–8 sources each, 3 assets, `cs-book-to-skill` agent, 2 commands. **Counters:** skills 362 → 363; tools 644 → 663; refs 741 → 746; agents 102 → 103; commands 116 → 118; plugins 88 → 89 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/memory-engineering (engineer the forgetting, not the remembering):**\n\nNew `engineering/memory-engineering/` plugin. Fills a real gap: the repo had no\nskill for designing, pricing, or auditing an **agent memory system** (nearest\nneighbours `llm-wiki`, `skillopt-sleep`, `agent-harness` all bound something\nelse — a vault, a loop, a task plan). Framing synthesized from *\"How to be a\nMemory Engineer, from the perspective of Stanford, Microsoft, Anthropic and\nNvidia\"* by [@N01ennn](https://x.com/N01ennn/status/2083971749079581120), with\nevery quantitative claim re-cited to the primary source.\n\n- **4 stdlib scripts, one per lens.** `memory_cost_profiler.py` (construction vs\n  query split, **cost per correct answer**, amortization, co-location warning →\n  WRITE-PATH-DOMINANT / UNDER-AMORTIZED / NEEDS-SCHEDULING-FIX);\n  `memory_architecture_picker.py` (scores the paper's four paradigm families,\n  disqualifies on hard constraints, **names the cost the choice makes you pay**,\n  and exits 2 refusing to pick when the top two are within 0.06 — printing the\n  tie-breaking question instead); `memory_density_auditor.py` (classifies every\n  record **FACT / SKILL / LOG / PROSE**, near-duplicates via word-shingle\n  Jaccard, staleness + volatile-wording flags, knowledge density per 1k tokens;\n  runs on a real `--dir` **or** `--jsonl`); `forgetting_policy_linter.py` — **the\n  gate**: 8 checks with **F1** (explicit forgetting rule) and **F4**\n  (contradictions surfaced, never auto-merged) blocking at exit 4.\n- **Evidence discipline — two of the source article's paraphrases are corrected\n  in the references rather than propagated.** (1) The 47× energy figure is the\n  *spread across ten evaluated systems* (BM25 at 4,145 J/correct answer vs\n  A-Mem/MIRIX at 115–197 kJ, a \"28–47× premium\"), **not** \"two systems with\n  identical accuracy.\" (2) The 97% first-pass-error reduction is **Rakuten's\n  named vendor-published customer testimonial** (Yusuke Kaji, at 27% lower cost\n  / 34% lower latency), not a controlled study or a general property of the\n  approach. Every reference carries per-claim confidence levels, per the\n  `andreessen` precedent.\n- **Two classifier defects found and fixed during the build**, both of which\n  would have produced garbage on any real repo: markdown headings *inside*\n  fenced code blocks were splitting records (fixed by masking fences before\n  heading detection — dropped 258 phantom records to 107 on a real directory),\n  and short fragments trivially matched at 1.00 Jaccard (fixed with a\n  20-word floor for duplicate candidacy, eliminating 41 false-positive\n  \"duplicates\"). A third fix added the **PROSE** class: an earlier version\n  labeled every signal-less block LOG, firing LOG_HEAVY at 74% on a prose\n  documentation folder.\n- 4 references citing 7 sources each (arXiv:2606.06448 Stanford characterization;\n  MSR PlugMem; arXiv:2604.09852 MEMENTO + OpenMementos; Anthropic managed-agents\n  memory), 3 assets (seven-question forcing worksheet, combined example spec\n  consumed by all three spec-taking scripts, fillable F1–F8 policy template),\n  `cs-memory-engineer` agent, `/cs-memory-engineering` + `/cs-forgetting-audit`.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist (binding for\n  post-v2.6.0 skills). **Counters** (this branch merged `dev` after\n  `book-to-skill` landed, so these deltas sit on top of it): skills 363 → 364;\n  tools 663 → 667; refs 746 → 750; agents 103 → 104; commands 118 → 120;\n  plugins 89 → 90 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/agent-memory (promotion is earned, not asserted):**\n\nNew `engineering/agent-memory/` plugin. Concept derived from\n[TencentCloud/TencentDB-Agent-Memory](https://github.com/TencentCloud/TencentDB-Agent-Memory)\n(MIT) — **no upstream code included**. A four-tier ladder over Claude Code's own\nhooks: **L0** raw transcripts (never injected) → **L1** candidate atoms\n(gitignored, recalled on lexical relevance per prompt) → **L2** project context\n(committed after adopt, loaded every session start) → **L3** stable persona\n(always loaded). Tiers are distinguished by *injection policy*, not storage\nformat.\n\n- **Three upstream choices deliberately rejected**, each for a repo rule rather\n  than taste: the managed **database** (self-contained-package rule → one\n  append-oriented JSONL per project, capped at 500 atoms); a **proxy layer**\n  between agent and model (Claude Code already exposes the three interception\n  points — adding a proxy to obtain hooks the platform provides buys nothing and\n  adds a failure mode on the critical path); **LLM-based extraction** (the\n  no-LLM-in-scripts anti-pattern, and a model call cannot run in an async\n  teardown hook on a latency budget, nor reproduce its output from the\n  transcript, which would break \"cite, don't invent\").\n- **The gates are the design.** L1→L2 needs ≥3 distinct sessions spanning ≥2\n  distinct calendar days (`stated` = 2 sessions, day rule *still applies*;\n  `verified` = 1 observation and is the only day-exempt path); L2→L3 needs ≥2\n  distinct projects + 30 days. Thresholds are tuned toward refusing because the\n  error costs are asymmetric: under-promotion is self-healing (the user restates\n  it, which is itself an observation), over-promotion silently steers every\n  future session.\n- **Two gates refuse rather than guess.** `redacted: true` blocks promotion on\n  *any* volume of evidence — a **durability-independent barrier**, since a\n  secret restated over five sessions passes every recurrence gate; the flag\n  firing means the text was altered, and a lexical filter finding one secret is\n  not proof it found all of them, while L2/L3 are committed to git. An open\n  contradiction freezes both claims, found by **reverse join** (the newer atom\n  carries no flag) rather than a mirrored field.\n- **Three hooks, all fail-open.** `SessionStart` injects L2+L3 and marks\n  L2↔L3 collisions the project-scoped detector structurally cannot see;\n  `UserPromptSubmit` recalls on a **100 ms internal budget** against a monotonic\n  clock (the 1 s hook `timeout` is a wedged-process backstop, not the budget);\n  `SessionEnd` is async and captures → redacts → merges → detects → stages.\n  Measured: spawn+recall p50 ≈ 29 ms / p95 ≈ 31 ms, scoring itself 2–3 ms over\n  500 atoms — **interpreter cold start is the entire cost**, which is why the\n  in-script loop is not worth optimizing further.\n- **Nothing reaches a `CLAUDE.md` without a human.** Promotions land in\n  `.memory/staged/`; `/cs-memory adopt` walks them one at a time and backs both\n  files up first. `cs-memory-curator` refuses to adopt a redacted claim, an\n  unresolvable citation, or to resolve a contradiction itself.\n- 5 stdlib scripts + 3 hooks (`memory_core.py` is a deviation from `DESIGN.md`\n  §10's four-script tree — the **`README.md` deviations list is authoritative**,\n  and §10.1's stale `+6` tool estimate is corrected to `+8` there and in\n  `DESIGN.md`), 3 references citing 6–7 sources each with per-claim confidence\n  levels, a 69-check example validator, and `DESIGN.md` — ~1,400 lines, 44\n  review rounds, open decisions ranked by what they gate, including the one that\n  permits deleting the folder if rule-based recall proves too low.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist. **Counters:**\n  skills 377 → 378; tools 695 → 703 (+8: 5 scripts + 3 hooks); refs 817 → 820;\n  agents 109 → 110; commands 129 → 130; plugins 94 → 95 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.1) — productivity/fable-goal (ramble → autonomous /goal prompt):**\n\nImproved port of `duncan-buildroom/freeskills` `fable-goal` (informal \"free to use and modify\" grant — quoted, not relicensed; see the `attribution` block). Converts a rambling description of a desired outcome into one polished, copy-paste /goal prompt for a fresh autonomous session — the prompt is the deliverable, never the build. Adds over upstream: wrong-tool check, observable-done principle, six-slot extraction (deliverable/quantity/stakes/tools/quality/destination), per-medium verification defaults, six-point pre-delivery self-check, anti-pattern list + failure-mode catalog reference, second worked example in a non-web medium. Ships `goal_prompt_self_check.py` (stdlib runner for the mechanically checkable self-check subset — word count 150–350, goal line, autonomy directive, verification/freedom/destination language; exit 0/1, `--sample`, `--output json`), `/cs-fable-goal` command. Intentionally no `agents/`/`assets/` (single reasoning pass; see plugin README design notes). SKILL.md is a full PASS on the write-a-skill 6-item checklist. Counters: skills 357 → 358 (this PR also trues up pre-existing engineering-row drift 355 → 357); tools 602 → 603; refs 731 → 732; commands 109 → 110; plugins 83 → 84.\n\n---\n\n**Version:** v2.11.1 (pm/product agent-harness domains — deep audit + orchestrated loops for product-team & project-management)\n\n**v2.11.1 highlights — both PM/product routers become agent harnesses:**\n\nExtends the v2.11.0 agent-harness layer to the two people-process domains. Public audit record at `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria).\n\n- **project-management → delivery loop:** `pm-skills` rebuilt as a `context: fork` orchestrator with 3 stdlib tools — `pm_goal_router.py`\n\n<!-- [TRUNCATED AT 50KB] -->","agent-launcher/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2F.claude-plugin%2Fplugin.json -->","agent-launcher/CLAUDE.md":"# CLAUDE.md — agent-launcher domain\n\nGuidance for working inside `agent-launcher/`. See the root `CLAUDE.md` for\nrepo-wide rules.\n\n## What this domain is\n\nA plugin that scaffolds and launches **Claude Managed Agents (CMA)** in the user's\nown Anthropic account, organized around a **per-session goal** that compiles into a\n**loop or workflow**. Inspired by `anthropics/launch-your-agent` (Apache-2.0);\nindependent re-implementation, not a fork.\n\n## Non-negotiable rules (enforced by SPEC.md + validators)\n\n1. **Deterministic scaffolders only.** Every script under `skills/*/scripts/` is\n   stdlib-only and makes **no** network/API calls. Live launches are emitted as\n   BYOK curl. Do not add `requests`, `anthropic`, or any network client.\n2. **Never surface the API key.** Launch scripts read `$ANTHROPIC_API_KEY`; no\n   tool echoes/logs/writes a key. `payload_validator.py` and reviewers check this.\n3. **CMA limits are law.** Keep `references/cma-primitives.md` as the source of\n   truth for ceilings; validators must match it.\n4. **Bounded loops only.** `loop_compiler.py` never emits a grade→iterate loop\n   without a `max_iterations` cap (1..20).\n5. **The hook is opt-in and crash-proof.** Gated by `AGENT_LAUNCHER_SESSION=1`;\n   exits 0 on any error. Never make it fire unconditionally.\n6. **The folder is the user's.** All artifacts go under `./my-agent/`; scripts\n   accept `--out-dir` and default there. Never write into the plugin folder.\n\n## Structure\n\n- `skills/agent-launcher-orchestrator/` — `context: fork` goal router\n  (`goal_router.py`, `goal_state.py`, `loop_compiler.py`).\n- `skills/{interview,stage-launch,grade-iterate,run-without-you,wrap-up}/` — one\n  phase each, 3 tools each.\n- `agents/` — `cs-agent-launcher-orchestrator` + 3 phase specialists.\n- `commands/` — 8 `/cs-*` commands.\n- `hooks/` — opt-in `session_start.py` / `session_end.py` + `hooks.json`.\n- `references/` — 5 shared docs. `assets/` — schema + templates + example.\n\n## Tool conventions\n\n- Every tool: `argparse` with real `--help`, a `--sample` that runs a deterministic\n  demo and exits 0, and JSON output via `--json` where a machine reads it.\n- Default output dir `./my-agent/`; never assume network access.\n- Import shared logic via relative `sys.path` insert (see how the orchestrator\n  tools import `goal_state`).\n\n## Forcing-question discipline\n\nEvery SKILL.md ships a \"Forcing-question library\" (Matt Pocock grill-with-docs):\nwalk one question at a time, recommend an answer, cite the reference. The\n`/cs-grill-agent-launcher` command surfaces them.\n\n## When editing\n\n- Changing a CMA limit → update `references/cma-primitives.md` **and** every\n  validator in lockstep.\n- Adding a loop shape → update `loop_compiler.py` **and**\n  `references/loops-and-workflows.md`.\n- Keep `SPEC.md` authoritative; if you ship something different, record it in the\n  delivery report.\n","agent-launcher/skills/agent-launcher-orchestrator/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fagent-launcher-orchestrator%2FREADME.md -->","agent-launcher/skills/agent-launcher-orchestrator/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fagent-launcher-orchestrator%2FSKILL.md -->","agent-launcher/skills/grade-iterate/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fgrade-iterate%2FREADME.md -->","agent-launcher/skills/grade-iterate/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fgrade-iterate%2FSKILL.md -->","agent-launcher/skills/interview/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Finterview%2FREADME.md -->","agent-launcher/skills/interview/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Finterview%2FSKILL.md -->","agent-launcher/skills/run-without-you/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Frun-without-you%2FREADME.md -->","agent-launcher/skills/run-without-you/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Frun-without-you%2FSKILL.md -->","agent-launcher/skills/stage-launch/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fstage-launch%2FREADME.md -->","agent-launcher/skills/stage-launch/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fstage-launch%2FSKILL.md -->","agent-launcher/skills/wrap-up/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fwrap-up%2FREADME.md -->","agent-launcher/skills/wrap-up/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fwrap-up%2FSKILL.md -->","agents/CLAUDE.md":"# Agent Development Guide\n\nThis guide provides comprehensive instructions for creating **cs-* prefixed agents** that seamlessly integrate with the 346 production skills in this repository (count derived via `scripts/derive_counters.py`).\n\n## Agent Architecture\n\n### What are cs-* Agents?\n\n**cs-* agents** are specialized Claude Code agents that orchestrate the repository's 346 skills. Each agent:\n- References skills via relative paths (`../marketing-skill/`)\n- Executes Python automation tools from skill packages\n- Follows established workflows and templates\n- Maintains skill portability and independence\n\n**Key Principle**: Agents ORCHESTRATE skills, they don't replace them. Skills remain self-contained and portable.\n\n### ClawHub Publishing Constraints\n\nWhen skills are published to **ClawHub** (clawhub.com):\n- **cs- prefix for slug conflicts only** — applies only on the ClawHub registry when another publisher already owns the slug. Repo folder names and local skill names are never renamed.\n- **No paid/commercial service dependencies** — skills must not require paid third-party API keys or commercial services unless provided by the project itself.\n- **plugin.json** — ONLY fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills: \"./\"`.\n- **Rate limit:** 5 new skills/hour on ClawHub. Use drip publishing for bulk operations.\n\n### Production Agents\n\n**33 agents live in this folder** (93 agent files repo-wide, including plugin-bundled agents). A representative selection:\n\n| Agent | Domain | Description |\n|-------|--------|-------------|\n| [cs-content-creator](marketing/cs-content-creator.md) | Marketing | AI-powered content creation with brand voice consistency and SEO optimization |\n| [cs-demand-gen-specialist](marketing/cs-demand-gen-specialist.md) | Marketing | Demand generation and customer acquisition specialist |\n| [cs-ceo-advisor](c-level/cs-ceo-advisor.md) | C-Level | Strategic leadership advisor for CEOs |\n| [cs-cto-advisor](c-level/cs-cto-advisor.md) | C-Level | Technical leadership advisor for CTOs |\n| [cs-product-manager](product/cs-product-manager.md) | Product | RICE prioritization and customer discovery |\n| [cs-product-strategist](product/cs-product-strategist.md) | Product | Product strategy, OKR cascades, market positioning |\n| [cs-agile-product-owner](product/cs-agile-product-owner.md) | Product | Agile product ownership and backlog management |\n| [cs-ux-researcher](product/cs-ux-researcher.md) | Product | UX research, usability testing, design insights |\n| [cs-product-analyst](product/cs-product-analyst.md) | Product | Product analytics, KPI design, experiment design |\n| [cs-engineering-lead](engineering-team/cs-engineering-lead.md) | Engineering | Engineering team coordination and incident management |\n| [cs-workspace-admin](engineering-team/cs-workspace-admin.md) | Engineering | Google Workspace administration via gws CLI |\n| [cs-senior-engineer](engineering/cs-senior-engineer.md) | Engineering | Architecture decisions, code review, CI/CD setup |\n| [cs-fullstack-engineer](engineering/cs-fullstack-engineer.md) | Engineering | Fullstack orchestrator (v2.8.1): walks 7 Matt Pocock forcing questions, picks profile via deterministic engine, forks (`context: fork`) into api-design-reviewer / database-designer / slo-architect / ci-cd-pipeline-builder. Invokable via `/cs-fullstack-review` or `Agent({subagent_type:\"cs-fullstack-engineer\"})`. |\n| [cs-frontend-engineer](engineering/cs-frontend-engineer.md) | Engineering | Frontend orchestrator (v2.8.1): walks 7 forcing questions (device, LCP target, rendering, bundle, SEO, design system, WCAG), picks framework profile, forks into a11y-audit / performance-profiler / epic-design / apple-hig-expert. Invokable via `/cs-frontend-review`. |\n| [cs-backend-engineer](engineering/cs-backend-engineer.md) | Engineering | Backend orchestrator (v2.8.1): walks 7 forcing questions (read/write + QPS, tenancy, sync vs async, sensitivity, pattern, RPO/RTO, SLO), picks language + pattern profile, forks into api-design-reviewer / database-designer / migration-architect / slo-architect / observability-designer. Invokable via `/cs-backend-review`. |\n| [cs-growth-strategist](business-growth/cs-growth-strategist.md) | Business | Growth strategy and revenue optimization |\n| [cs-financial-analyst](finance/cs-financial-analyst.md) | Finance | Financial analysis, DCF valuation, SaaS metrics |\n| [cs-project-manager](project-management/cs-project-manager.md) | PM | Project management with Atlassian integration |\n| [cs-quality-regulatory](ra-qm-team/cs-quality-regulatory.md) | RA/QM | Regulatory affairs and quality management |\n\n**Template Available**: [templates/agent-template.md](../templates/agent-template.md) (318 lines) - Use this to create new agents\n\n### Agent vs Skill\n\n| Aspect | Agent (cs-*) | Skill |\n|--------|-------------|-------|\n| **Purpose** | Orchestrate and execute workflows | Provide tools, knowledge, templates |\n| **Location** | `agents/domain/` | `domain-skill/skill-name/` |\n| **Structure** | Single .md file with YAML frontmatter | SKILL.md + scripts/ + references/ + assets/ |\n| **Integration** | References skills via `../../` | Self-contained, no dependencies |\n| **Naming** | cs-content-creator, cs-ceo-advisor | content-creator, ceo-advisor |\n\n## Agent File Structure\n\n### Required YAML Frontmatter\n\nEvery agent file must start with valid YAML frontmatter:\n\n```yaml\n---\nname: cs-agent-name\ndescription: One-line description of what this agent does\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n```\n\n**Field Definitions:**\n- **name**: Agent identifier with `cs-` prefix (e.g., `cs-content-creator`)\n- **description**: Single sentence describing agent's purpose\n- **No `skills:` field.** Claude Code preloads every skill listed there into the subagent's context on each spawn (resolved by `plugin:skill` name, not by path). This repo's agents are lightweight routers, so name the skill folder in the agent body instead and let the agent load it on demand (decision recorded on PR #939).\n- **domain**: Domain category (marketing, product, engineering, c-level, pm, ra-qm)\n- **model**: Claude model to use (sonnet, opus, haiku)\n- **tools**: Array of Claude Code tools agent can use\n\n### Required Markdown Sections\n\nAfter YAML frontmatter, include these sections:\n\n1. **Purpose** (2-3 paragraphs)\n2. **Skill Integration** (with subsections)\n   - Skill Location\n   - Python Tools\n   - Knowledge Bases\n   - Templates\n3. **Workflows** (minimum 3 workflows)\n4. **Integration Examples** (concrete code/command examples)\n5. **Success Metrics** (how to measure effectiveness)\n6. **Related Agents** (cross-references)\n7. **References** (links to documentation)\n\n## Relative Path Resolution\n\n### Path Pattern\n\nAll skill references use the `../../` pattern:\n\n```markdown\n**Skill Location:** `../marketing-skill/skills/content-creator/`\n\n### Python Tools\n\n1. **Brand Voice Analyzer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py content.txt`\n\n2. **SEO Optimizer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/seo_optimizer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"keyword\"`\n```\n\n### Why `../../`?\n\nFrom agent location: `agents/marketing/cs-content-creator.md`\nTo skill location: `marketing-skill/content-creator/`\n\nNavigation: `agents/marketing/` → `../../` (up to root) → `marketing-skill/content-creator/`\n\n**Always test paths resolve correctly!**\n\n## Python Tool Integration\n\n### Execution Pattern\n\nAgents execute Python tools from skill packages:\n\n```bash\n# From agent context\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt\n\n# With JSON output\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt json\n\n# With arguments\npython ../product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n```\n\n### Tool Requirements\n\nAll Python tools must:\n- Use standard library only (or minimal dependencies documented in SKILL.md)\n- Support both JSON and human-readable output\n- Provide `--help` flag with usage information\n- Return appropriate exit codes (0 = success, 1 = error)\n- Handle missing arguments gracefully\n\n### Error Handling\n\nWhen Python tools fail:\n1. Check file path resolution\n2. Verify input file exists\n3. Check Python version compatibility (3.8+)\n4. Review tool's `--help` output\n5. Inspect error messages in stderr\n\n## Workflow Documentation\n\n### Workflow Structure\n\nEach workflow must include:\n\n```markdown\n### Workflow 1: [Clear Descriptive Name]\n\n**Goal:** One-sentence description\n\n**Steps:**\n1. **[Action]** - Description with specific commands/tools\n2. **[Action]** - Description with specific commands/tools\n3. **[Action]** - Description with specific commands/tools\n\n**Expected Output:** What success looks like\n\n**Time Estimate:** How long this workflow takes\n\n**Example:**\n\\`\\`\\`bash\n# Concrete example command\npython ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"primary keyword\"\n\\`\\`\\`\n```\n\n### Minimum Requirements\n\nEach agent must document **at least 3 workflows** covering:\n1. Primary use case (most common scenario)\n2. Advanced use case (complex scenario)\n3. Integration use case (combining multiple tools)\n\n## Agent Template\n\nUse this template when creating new agents:\n\n```markdown\n---\nname: cs-agent-name\ndescription: One-line description\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n\n# Agent Name\n\n## Purpose\n\n[2-3 paragraphs describing what this agent does, why it exists, and who it serves]\n\n## Skill Integration\n\n**Skill Location:** \\`../../domain-skill/skill-name/\\`\n\n### Python Tools\n\n1. **Tool Name**\n   - **Purpose:** What it does\n   - **Path:** \\`../../domain-skill/skill-name/scripts/tool.py\\`\n   - **Usage:** \\`python ../../domain-skill/skill-name/scripts/tool.py [args]\\`\n\n### Knowledge Bases\n\n1. **Reference Name**\n   - **Location:** \\`../../domain-skill/skill-name/references/file.md\\`\n   - **Content:** What's inside\n\n### Templates\n\n1. **Template Name**\n   - **Location:** \\`../../domain-skill/skill-name/assets/template.md\\`\n   - **Use Case:** When to use\n\n## Workflows\n\n### Workflow 1: [Name]\n\n**Goal:** Description\n\n**Steps:**\n1. Step 1\n2. Step 2\n3. Step 3\n\n**Expected Output:** Success criteria\n\n**Example:**\n\\`\\`\\`bash\npython ../../domain-skill/skill-name/scripts/tool.py input.txt\n\\`\\`\\`\n\n### Workflow 2: [Name]\n[Same structure]\n\n### Workflow 3: [Name]\n[Same structure]\n\n## Integration Examples\n\n[Concrete examples with actual commands and expected outputs]\n\n## Success Metrics\n\n- Metric 1: How to measure\n- Metric 2: How to measure\n- Metric 3: How to measure\n\n## Related Agents\n\n- [cs-related-agent](../<domain>/cs-related-agent.md) - How they relate\n\n## References\n\n- [Skill Documentation](../../domain-skill/skill-name/SKILL.md)\n- [Domain Roadmap](../../<domain-skill>/roadmap.md)\n```\n\n## Quality Standards\n\n### Agent Quality Checklist\n\nBefore committing an agent:\n\n- [ ] YAML frontmatter valid (no parsing errors)\n- [ ] All required fields present (name, description, skills, domain, model, tools)\n- [ ] cs-* prefix used for agent naming\n- [ ] Relative paths resolve correctly (../../ pattern)\n- [ ] Skill location documented and accessible\n- [ ] Python tools referenced with correct paths\n- [ ] At least 3 workflows documented\n- [ ] Integration examples provided and tested\n- [ ] Success metrics defined\n- [ ] Related agents cross-referenced\n\n### Testing Agent Integration\n\nTest these aspects:\n\n**1. Path Resolution**\n```bash\n# From agent directory\ncd agents/marketing/\nls ../marketing-skill/skills/content-creator/  # Should list contents\n```\n\n**2. Python Tool Execution**\n```bash\n# Create test input\necho \"Test content\" > test-input.txt\n\n# Execute tool\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py test-input.txt\n\n# Verify output\n```\n\n**3. Knowledge Base Access**\n```bash\n# Verify reference files exist\ncat ../marketing-skill/skills/content-creator/references/brand_guidelines.md\n```\n\n## Domain-Specific Guidelines\n\n### Marketing Agents (agents/marketing/)\n- Focus on content creation, SEO, demand generation\n- Reference: `../marketing-skill/`\n- Tools: brand_voice_analyzer.py, seo_optimizer.py\n\n### Product Agents (agents/product/)\n- Focus on prioritization, user research, agile workflows\n- Reference: `../product-team/`\n- Tools: rice_prioritizer.py, user_story_generator.py, okr_cascade_generator.py\n\n### C-Level Agents (agents/c-level/)\n- Focus on strategic decision-making\n- Reference: `../c-level-advisor/`\n- Tools: Strategic analysis and planning tools\n\n### Engineering Agents (agents/engineering/)\n- Focus on scaffolding, code quality, fullstack development\n- Reference: `engineering-team/`\n- Tools: project_scaffolder.py, code_quality_analyzer.py\n\n## Common Pitfalls\n\n**Avoid these mistakes:**\n\n❌ Hardcoding absolute paths\n❌ Skipping YAML frontmatter validation\n❌ Forgetting to test relative paths\n❌ Documenting workflows without examples\n❌ Creating agent dependencies (keep them independent)\n❌ Duplicating skill content in agent files\n❌ Using LLM calls instead of referencing Python tools\n\n## Next Steps\n\nAfter creating an agent:\n\n1. Test all relative paths resolve\n2. Execute all Python tools from agent context\n3. Verify all workflows with concrete examples\n4. Update agent catalog in main README.md\n5. Create GitHub issue for agent testing\n6. Commit with conventional commit message: `feat(agents): implement cs-agent-name`\n\n---\n\n**Last Updated:** June 10, 2026\n**Current:** 33 agents in this folder across 10 domain subfolders (93 agent files repo-wide)\n**Related:** See [main CLAUDE.md](../CLAUDE.md) for repository overview\n","agents/personas/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agents%2Fpersonas%2FREADME.md -->","business-growth/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2F.claude-plugin%2Fplugin.json -->","business-growth/CLAUDE.md":"# Business & Growth Skills - Claude Code Guidance\n\nThis guide covers the 5 production-ready business and growth skills and their Python automation tools.\n\n## Business & Growth Skills Overview\n\n**Available Skills:**\n1. **customer-success-manager/** - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)\n2. **sales-engineer/** - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)\n3. **revenue-operations/** - Pipeline analysis, forecast accuracy, GTM efficiency metrics (3 Python tools)\n\n**Total Tools:** 9 Python automation tools, 9 knowledge bases, 19+ templates\n\n## Python Automation Tools\n\n### Customer Success Manager Tools\n\n#### 1. Health Score Calculator (`customer-success-manager/scripts/health_score_calculator.py`)\n\n**Purpose:** Multi-dimensional customer health scoring with trend analysis\n\n**Features:**\n- Weighted scoring across 4 dimensions (usage, engagement, support, relationship)\n- Red/Yellow/Green classification with configurable thresholds\n- Trend analysis comparing current vs previous period\n- Segment-aware benchmarking (Enterprise/Mid-Market/SMB)\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json --format json\n```\n\n#### 2. Churn Risk Analyzer (`customer-success-manager/scripts/churn_risk_analyzer.py`)\n\n**Purpose:** Identify at-risk accounts with intervention recommendations\n\n**Features:**\n- Risk scoring based on behavioral signals\n- Warning signal detection and categorization\n- Tier-appropriate intervention playbooks\n- Urgency-based prioritization\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json --format json\n```\n\n#### 3. Expansion Opportunity Scorer (`customer-success-manager/scripts/expansion_opportunity_scorer.py`)\n\n**Purpose:** Identify upsell and cross-sell opportunities\n\n**Features:**\n- Adoption depth analysis across product modules\n- Whitespace mapping for unused features\n- Revenue opportunity estimation\n- Priority ranking by effort and impact\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json --format json\n```\n\n### Sales Engineer Tools\n\n#### 4. RFP Response Analyzer (`sales-engineer/scripts/rfp_response_analyzer.py`)\n\n**Purpose:** Score RFP/RFI coverage and identify gaps\n\n**Features:**\n- Requirement coverage scoring (Full/Partial/Planned/Gap)\n- Effort estimation per requirement\n- Gap identification with mitigation strategies\n- Overall bid/no-bid recommendation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json --format json\n```\n\n#### 5. Competitive Matrix Builder (`sales-engineer/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Generate feature comparison matrices and competitive positioning\n\n**Features:**\n- Feature-by-feature comparison matrix\n- Competitive scoring with weighted categories\n- Differentiator identification\n- Battlecard-ready output\n\n**Usage:**\n```bash\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json --format json\n```\n\n#### 6. POC Planner (`sales-engineer/scripts/poc_planner.py`)\n\n**Purpose:** Plan proof-of-concept engagements\n\n**Features:**\n- Timeline estimation based on scope\n- Resource allocation planning\n- Success criteria definition\n- Evaluation scorecard generation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/poc_planner.py poc_data.json\npython sales-engineer/scripts/poc_planner.py poc_data.json --format json\n```\n\n### Revenue Operations Tools\n\n#### 7. Pipeline Analyzer (`revenue-operations/scripts/pipeline_analyzer.py`)\n\n**Purpose:** Analyze sales pipeline health and velocity\n\n**Features:**\n- Coverage ratio calculation (pipeline/quota)\n- Stage conversion rate analysis\n- Sales velocity metrics (4-lever model)\n- Deal aging analysis\n\n**Usage:**\n```bash\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json --format json\n```\n\n#### 8. Forecast Accuracy Tracker (`revenue-operations/scripts/forecast_accuracy_tracker.py`)\n\n**Purpose:** Measure and improve forecast accuracy\n\n**Features:**\n- MAPE (Mean Absolute Percentage Error) calculation\n- Forecast bias detection (over/under-forecasting)\n- Period-over-period trend analysis\n- Category-level accuracy breakdown\n\n**Usage:**\n```bash\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json --format json\n```\n\n#### 9. GTM Efficiency Calculator (`revenue-operations/scripts/gtm_efficiency_calculator.py`)\n\n**Purpose:** Calculate go-to-market efficiency metrics\n\n**Features:**\n- Magic number calculation\n- LTV:CAC ratio analysis\n- CAC payback period\n- Burn multiple assessment\n- Industry benchmarking\n\n**Usage:**\n```bash\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json --format json\n```\n\n## Quality Standards\n\n**All business & growth Python tools must:**\n- Use standard library only (no external dependencies)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **Marketing:** Content creation, demand generation -> `../marketing-skill/`\n- **Product Team:** User research, feature prioritization -> `../product-team/`\n- **C-Level:** Strategic planning -> `../c-level-advisor/`\n- **Engineering:** Technical implementation -> `../engineering-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 5/5 business & growth skills production-ready\n**Total Tools:** 9 Python automation tools\n","business-growth/skills/business-growth-skills/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fbusiness-growth-skills%2FSKILL.md -->","business-growth/skills/contract-and-proposal-writer/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcontract-and-proposal-writer%2FSKILL.md -->","business-growth/skills/customer-success-manager/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcustomer-success-manager%2FSKILL.md 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/api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fsales-engineer%2Freferences%2Fpoc-best-practices.md -->","business-growth/skills/sales-engineer/references/rfp-response-guide.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fsales-engineer%2Freferences%2Frfp-response-guide.md -->","business-operations/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2F.claude-plugin%2Fplugin.json -->","business-operations/CLAUDE.md":"# Business Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `business-operations/`.\n\n## Purpose\n\nThe Business Operations domain ships skills that help **internal operators** (BizOps lead, COO direct reports, vendor management office, IT ops) run the company day-to-day. This is **not strategy** (that's `c-level-advisor/`) and **not external sales** (that's `business-growth/`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Job-to-be-done | `context: fork`? |\n|---|---|---|\n| `business-operations-skills` | Domain orchestrator — routes inquiries to the 6 sub-skills | YES |\n| `process-mapper` | BPMN-style process docs + bottleneck + cycle-time (Lean / TOC canon) | YES |\n| `vendor-management` | Vendor scoring + SLA + third-party risk (NIST SP 800-161 / ISO 27036) | YES |\n| `capacity-planner` | Erlang-C queueing math for ops teams (NOT engineering capacity) | NO |\n| `internal-comms` | ADKAR + Kotter 8-step change comms (NOT marketing) | NO |\n| `knowledge-ops` | SOPs + runbooks with 5W2H validation + KB hygiene (NOT personal PKM) | YES |\n| `procurement-optimizer` | UNSPSC-aligned spend categorization + supplier consolidation | NO |\n\n## Build pattern\n\nPath-B 11-file contract per skill (Matt Pocock-derived discipline preserved):\n\n```\nskill/\n├── SKILL.md                  # YAML frontmatter + workflow + forcing-question library\n├── scripts/                  # 3 stdlib-only Python CLI tools\n├── references/               # 3 ref docs, ≥ 7 cited sources each\n└── assets/                   # ≥ 1 user-customizable template\n```\n\n## Hard rules\n\n1. **Stdlib-only Python** — no `requests`, `pandas`, `numpy`. Just `argparse`, `json`, `sys`, `pathlib`, `statistics`, `dataclasses`, `enum`, `datetime`, `math`, `re`, `collections`.\n2. **Deterministic logic** — no LLM calls in scripts. Same input → same output. Erlang-C math implemented in log-space to avoid factorial overflow.\n3. **Industry tuning** — every scoring tool exposes `--profile {saas,services,manufacturing,healthcare,…}` for threshold calibration.\n4. **Matt Pocock grill discipline** — orchestrator routes via one-question-per-turn with a recommended answer + canon citation. Never bundles. Never auto-routes silently after a question. Every SKILL.md ships a \"Forcing-question library\" section with 5-7 cited canon-anchored questions.\n5. **Output is recommendation, not approval** — `vendor-management` never says \"replace this vendor\"; `procurement-optimizer` never auto-consolidates suppliers; the human always decides.\n\n## Agent + command pattern\n\n- `cs-bizops-orchestrator` — the persona agent. Voice: \"Where does the work spend most of its time waiting?\" (Theory of Constraints anchor).\n- `/cs-bizops <inquiry>` — top-level router.\n- `/cs-grill-bizops <plan>` — Matt-style docs-anchored grilling **before** routing.\n- `/cs-process-map`, `/cs-vendor-review`, `/cs-capacity-plan`, `/cs-internal-comms`, `/cs-knowledge-ops`, `/cs-procurement` — direct per-skill invocation.\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/*` (external sales motion) — BizOps is **internal**\n- ❌ Skills that overlap `c-level-advisor/coo-advisor` — that's strategic; BizOps is tactical\n- ❌ \"Process improvement consultant\" generic skills — every skill must answer a SPECIFIC question (e.g., \"where's the bottleneck?\", \"is this vendor delivering?\", \"are we sized to peak demand?\", not \"how can we improve operations?\")\n- ❌ Tools without `--profile` tuning — every score must be industry-tunable\n- ❌ Bundled questions in the orchestrator — Matt's rule: one at a time, with a recommended answer\n- ❌ Engineering-specific framing in capacity-planner — that's vpe-advisor's lane\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-me`, `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/coo-advisor`\n","business-operations/skills/business-operations-skills/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fbusiness-operations-skills%2FSKILL.md -->","business-operations/skills/capacity-planner/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2FSKILL.md -->","business-operations/skills/capacity-planner/assets/capacity_brief_template.md":"<!-- Skill available on-demand via 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layer that surfaces 8 cs-* persona agents and 17 `/cs-*` slash commands on top of the skills.\n\n## Architecture\n\n```\n/cs-onboard setup (Founder Interview) → company-context.md\n                │\n        Chief of Staff (Router)\n                │\n    ┌───────────┼───────────┐\n    10 Roles    6 Cross-Cut  6 Culture\n    │           │            │\n    └───────────┼────────────┘\n                │\n        Executive Mentor (Critic)\n                │\n        Decision Logger (Two-Layer Memory)\n```\n\n## Skills Overview\n\n### C-Suite Roles (15)\n\n| Role | Folder | Reasoning Technique | Scripts |\n|------|--------|-------------------|---------|\n| **CEO** | `ceo-advisor/` | Tree of Thought | strategy_analyzer, financial_scenario_analyzer |\n| **CTO** | `cto-advisor/` | ReAct | tech_debt_analyzer, team_scaling_calculator |\n| **COO** | `coo-advisor/` | Step by Step | ops_efficiency_analyzer, okr_tracker |\n| **CPO** | `cpo-advisor/` | First Principles | pmf_scorer, portfolio_analyzer |\n| **CMO** | `cmo-advisor/` | Recursion of Thought | marketing_budget_modeler, growth_model_simulator |\n| **CFO** | `cfo-advisor/` | Chain of Thought | burn_rate_calculator, unit_economics_analyzer, fundraising_model |\n| **CRO** | `cro-advisor/` | Chain of Thought | revenue_forecast_model, churn_analyzer |\n| **CISO** | `ciso-advisor/` | Risk-Based | risk_quantifier, compliance_tracker |\n| **CHRO** | `chro-advisor/` | Empathy + Data | hiring_plan_modeler, comp_benchmarker |\n| **General Counsel** | `general-counsel-advisor/` | Risk-Based | contract_risk_scanner, term_sheet_analyzer |\n| **Chief Data Officer** | `chief-data-officer-advisor/` | Decision-Driven | ai_training_data_audit, data_product_strategy_picker, data_asset_valuator |\n| **Chief AI Officer** | `chief-ai-officer-advisor/` | Eval-Demanding | model_buildvsbuy_calculator, ai_risk_classifier, ai_cost_economics |\n| **Chief Customer Officer** | `chief-customer-officer-advisor/` | Retention-Obsessed | retention_decomposition_analyzer, customer_segmentation_designer, cs_coverage_calculator |\n| **VP of Engineering** ⭐ NEW v2.5.5 | `vpe-advisor/` | Throughput-First | delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer |\n| **Executive Mentor** | `executive-mentor/` | Adversarial | decision_matrix_scorer, stakeholder_mapper |\n\n### Orchestration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **C-Suite Onboard** | `cs-onboard/` | Founder interview → company-context.md |\n| **Chief of Staff** | `chief-of-staff/` | Routes questions, triggers board meetings |\n| **Board Meeting** | `board-meeting/` | 6-phase multi-agent deliberation |\n| **Decision Logger** | `decision-logger/` | Two-layer memory (raw + approved) |\n| **Agent Protocol** | `agent-protocol/` | Inter-agent invocation, loop prevention, quality loop |\n| **Context Engine** | `context-engine/` | Company context loading + anonymization |\n\n### Cross-Cutting Capabilities (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Board Deck Builder** | `board-deck-builder/` | Assembles board/investor updates |\n| **Scenario War Room** | `scenario-war-room/` | Multi-variable what-if modeling |\n| **Competitive Intel** | `competitive-intel/` | Systematic competitor tracking |\n| **Org Health Diagnostic** | `org-health-diagnostic/` | Cross-functional health scoring |\n| **M&A Playbook** | `ma-playbook/` | Acquiring or being acquired |\n| **International Expansion** | `intl-expansion/` | Market entry strategy |\n\n### Culture & Collaboration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Culture Architect** | `culture-architect/` | Build and operationalize culture |\n| **Company OS** | `company-os/` | EOS/Scaling Up operating system |\n| **Founder Coach** | `founder-coach/` | Founder development and growth |\n| **Strategic Alignment** | `strategic-alignment/` | Strategy cascade, silo detection |\n| **Change Management** | `change-management/` | ADKAR-based change rollout |\n| **Internal Narrative** | `internal-narrative/` | One story across all audiences |\n\n## c-level-agents Plugin (v1.0.0 — new in v2.5.0)\n\nA separate plugin at the repo's top-level `c-level-agents/` directory (moved out of `c-level-advisor/` in #949 so the two marketplace sources no longer overlap) that wraps the 10 C-roles with persona agents and slash commands. Founder-mode entry layer.\n\n### 13 cs-* Agents (in `../c-level-agents/agents/`)\n\n| Agent | Voice | Wraps Skill |\n|---|---|---|\n| cs-cfo-advisor | Numerate skeptic | cfo-advisor |\n| cs-cmo-advisor | Narrative-first | cmo-advisor |\n| cs-cro-advisor | Pipeline-paranoid | cro-advisor |\n| cs-cpo-advisor | JTBD-driven | cpo-advisor |\n| cs-coo-advisor | Execution OS | coo-advisor |\n| cs-chro-advisor | People-systems | chro-advisor |\n| cs-ciso-advisor | Risk-paranoid | ciso-advisor |\n| cs-chief-of-staff | Router & synthesist | chief-of-staff |\n| cs-general-counsel-advisor | Risk-paranoid (legal) | general-counsel-advisor |\n| cs-cdo-advisor | Decision-driven (data) | chief-data-officer-advisor |\n| cs-caio-advisor | Eval-demanding (AI) | chief-ai-officer-advisor |\n| cs-cco-advisor | Retention-obsessed (customer) | chief-customer-officer-advisor |\n| cs-vpe-advisor ⭐ NEW v2.5.5 | Throughput-first (engineering ops) | vpe-advisor |\n\nExisting `cs-ceo-advisor` and `cs-cto-advisor` live in `/agents/c-level/` and integrate with the same protocol.\n\n### 17 /cs-* Slash Commands (in `../c-level-agents/skills/`)\n\n**Forcing-question office hours (8):** `/c-level-agents:office-hours`, `/c-level-agents:cfo-review`, `/c-level-agents:cmo-review`, `/c-level-agents:cpo-review`, `/c-level-agents:cro-review`, `/c-level-agents:cto-review`, `/c-level-agents:ciso-review`, `/c-level-agents:gc-review`\n\n**Strategic sprint pipeline (5):** `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`\n\n**Meta + safety (4):** `/c-level-agents:founder-mode` (auto-router), `/cs-onboard` (founder interview), `/c-level-agents:cross-eval` (multi-model consensus), `/c-level-agents:freeze` (cooldown lock)\n\nSee [c-level-agents/README.md](../c-level-agents/README.md) for the full plugin guide and [c-level-agents/references/persona-voices.md](../c-level-agents/references/persona-voices.md) for voice specs.\n\n## Executive Mentor Slash Commands\n\nThe only skill with a `plugin.json` (namespace: `em`) because it has slash commands. Other skills are invoked by name through the Chief of Staff router or directly by the user. This is intentional — only add `plugin.json` when a skill has dedicated slash commands that need a namespace.\n\n| Command | Purpose |\n|---------|---------|\n| `/em:challenge` | Pre-mortem analysis of any plan |\n| `/em:board-prep` | Board meeting preparation |\n| `/em:hard-call` | Framework for hard decisions |\n| `/em:stress-test` | Stress-test any assumption |\n| `/em:postmortem` | Honest retrospective |\n\n## Key Design Decisions\n\n- **Two-layer memory:** Raw transcripts (reference) + approved decisions only (feeds future meetings). Prevents hallucinated consensus.\n- **Phase 2 isolation:** During board meetings, agents think independently before cross-examination.\n- **Internal Quality Loop:** Self-verify → peer-verify → critic pre-screen → present. No unverified output reaches the founder.\n- **Proactive triggers:** Every role has context-driven early warnings that surface issues without being asked.\n- **User Communication Standard:** Bottom Line → What → Why → How to Act → Your Decision. Results only, no process narration.\n\n## Python Tools (25 total)\n\nAll scripts are stdlib-only, CLI-first, with JSON output and embedded sample data.\n\n```bash\n# Examples\npython cfo-advisor/scripts/burn_rate_calculator.py\npython cro-advisor/scripts/churn_analyzer.py\npython cpo-advisor/scripts/pmf_scorer.py\npython org-health-diagnostic/scripts/health_scorer.py\npython strategic-alignment/scripts/alignment_checker.py\npython decision-logger/scripts/decision_tracker.py\n```\n\n## Integration with Other Domains\n\n| C-Level Role | Layers Above |\n|-------------|-------------|\n| CMO | marketing-skill/ (content, demand gen, ASO execution) |\n| CFO | finance/financial-analyst (spreadsheets, DCF) |\n| CRO | business-growth/ (revenue ops, sales engineering) |\n| CISO | ra-qm-team/ (ISO 27001 checklists, ISMS audits) |\n| CPO | product-team/ (PM toolkit, user stories, sprint planning) |\n\n---\n\n**Last Updated:** 2026-05-13\n**Skills Deployed:** 33 skills (15 roles incl. General Counsel, CDO, CAIO, CCO, and VPE + 5 mentor commands + 6 orchestration + 6 cross-cutting + 6 culture) + 21 /cs-* sub-skills in c-level-agents plugin\n**Agents:** 15 cs-* (cs-ceo, cs-cto in /agents/c-level/; 13 in ../c-level-agents/agents/ including new cs-vpe-advisor)\n**Python Tools:** 39 (stdlib-only) — +3 with vpe-advisor (delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer)\n**Reference Docs:** 73 (71 in skills + 2 in c-level-agents/references)\n","c-level-advisor/arquiteto-de-empresa/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Farquiteto-de-empresa%2F.claude-plugin%2Fplugin.json -->","c-level-advisor/arquiteto-de-empresa/skills/arquiteto-de-empresa/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Farquiteto-de-empresa%2Fskills%2Farquiteto-de-empresa%2FSKILL.md 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This is **not strategy** (`c-level-advisor/cro-advisor`), **not sales execution** (`business-growth/sales-engineer`), and **not financial close** (`finance/financial-analysis`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `commercial-skills` | Domain orchestrator — routes to 7 sub-skills | YES |\n| `pricing-strategist` | Pricing model picker + Van Westendorp WTP + packaging | NO |\n| `deal-desk` | Per-deal scorer + discount approval routing + redline | NO |\n| `partnerships-architect` | 5-tier classifier + joint GTM + revshare modeler | NO |\n| `channel-economics` | Cost-to-serve + ROI + channel mix optimizer | NO |\n| `commercial-policy` | Data-backed discount matrix + exception flow + policy linter | NO |\n| `rfp-responder` | Shipley-method structured RFP/RFI/RFQ response | YES |\n| `commercial-forecaster` | 4Q-weighted bookings + cohort NRR/GRR + funnel-confidence | NO |\n\n## Hard rules (domain-specific)\n\n1. **Pricing outputs: model + range, never a specific number.** The human picks the number.\n2. **Deal outputs: score + named human approver. Never auto-approve.** Even at 0% discount.\n3. **Forecast outputs: surface the conversion assumption explicitly.** Pipeline math without disclosed assumptions is theatre.\n4. **RFP responses: never invent claims for GAP requirements.** Surface the gap; leadership decides bid/no-bid.\n5. **Partnership tiers: insist on independent-demand evidence for STRATEGIC.** Forrester: channel-led deals from your own pipeline cost more than direct.\n6. **Channel ROI requires retention differential.** CAC alone is meaningless without channel-level retention.\n7. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n8. **Industry tuning** via `--profile {saas,api,enterprise-software,marketplace,services,hardware}` on every scoring tool.\n9. **Matt Pocock grill discipline** — `/cs-grill-commercial` interrogates plan against SaaS pricing canon before any sub-skill runs.\n\n## Build pattern\n\nPath-B 11-file contract per skill. SKILL.md includes a \"Forcing-question library\" section that grills the user with cited canon (Skok, Tunguz, Bessemer, Ramanujam, ProfitWell, Winning by Design, Shipley, APMP).\n\n## Agent + command pattern\n\n- `cs-commercial-orchestrator` — margin-protective Commercial lead. Voice: \"What's the margin at full discount, AND what does next quarter's pipeline look like at the same terms?\"\n- `/cs-commercial <inquiry>` — top-level router\n- `/cs-grill-commercial <plan>` — Matt-style grilling first\n- `/cs-pricing-strategy`, `/cs-deal-review`, `/cs-partner-tier`, `/cs-channel-econ`, `/cs-commercial-policy`, `/cs-rfp-respond`, `/cs-commercial-forecast` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/contract-and-proposal-writer` (prose authoring) — Commercial is **decision logic + structured response**\n- ❌ Skills that overlap `c-level-advisor/cro-advisor` — that's strategic CRO judgment\n- ❌ Skills that recommend a specific price — recommend model + range\n- ❌ Skills that auto-approve deals — score + route to named human\n- ❌ Forecasting tools that hide conversion assumptions\n- ❌ RFP responder that invents claims — surface GAPs, leadership decides\n- ❌ Partnership classifier that grants STRATEGIC tier without independent-demand evidence\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/cro-advisor`\n- Sales execution complement: `business-growth/sales-engineer`\n","commercial/skills/channel-economics/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2FSKILL.md -->","commercial/skills/channel-economics/assets/channel_data_template.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Fassets%2Fchannel_data_template.md -->","commercial/skills/channel-economics/references/channel_anti_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Freferences%2Fchannel_anti_patterns.md 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/api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-research-ops.md -->","docs/commands/cs-research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-research.md -->","docs/commands/cs-rfp-respond.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-rfp-respond.md -->","docs/commands/cs-roast.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-roast.md -->","docs/commands/cs-run-without-you.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-run-without-you.md -->","docs/commands/cs-scrape.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-scrape.md -->","docs/commands/cs-skill-doctor.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-skill-doctor.md -->","docs/commands/cs-spinning-up-deep-rl.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-spinning-up-deep-rl.md -->","docs/commands/cs-stage-launch.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-stage-launch.md -->","docs/commands/cs-syllabus.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-syllabus.md -->","docs/commands/cs-time-block.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-time-block.md -->","docs/commands/cs-vendor-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-vendor-review.md -->","docs/commands/cs-webinar.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-webinar.md -->","docs/commands/cs-weekly-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-weekly-review.md -->","docs/commands/cs-workflow-build.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-workflow-build.md -->","docs/commands/cs-wrap-up.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-wrap-up.md -->","docs/commands/cs-write-a-skill.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-write-a-skill.md -->","docs/commands/financial-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ffinancial-health.md -->","docs/commands/flag-cleanup.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fflag-cleanup.md -->","docs/commands/focused-fix.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ffocused-fix.md -->","docs/commands/google-workspace.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fgoogle-workspace.md -->","docs/commands/index.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Findex.md -->","docs/commands/karpathy-check.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fkarpathy-check.md -->","docs/commands/okr.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fokr.md -->","docs/commands/operator-audit.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Foperator-audit.md -->","docs/commands/persona.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fpersona.md -->","docs/commands/pipeline.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fpipeline.md -->","docs/commands/plugin-audit.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fplugin-audit.md -->","docs/commands/prd.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fprd.md -->","docs/commands/project-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fproject-health.md -->","docs/commands/retro.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fretro.md -->","docs/commands/rice.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Frice.md -->","docs/commands/saas-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsaas-health.md -->","docs/commands/seo-auditor.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fseo-auditor.md -->","docs/commands/skillopt-sleep.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fskillopt-sleep.md -->","docs/commands/slo-design.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fslo-design.md -->","docs/commands/sprint-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsprint-health.md -->","docs/commands/sprint-plan.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsprint-plan.md -->","docs/commands/tc.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ftc.md -->","docs/commands/tdd.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ftdd.md -->","docs/commands/tech-debt.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ftech-debt.md -->","docs/commands/user-story.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fuser-story.md -->","docs/commands/wiki-ingest.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-ingest.md -->","docs/commands/wiki-init.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-init.md -->","docs/commands/wiki-lint.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-lint.md -->","docs/commands/wiki-log.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-log.md -->","docs/commands/wiki-query.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-query.md -->","docs/llms-full.txt":"# Claude Code Skills & Agent Plugins — Full Repository Description\n\n> A comprehensive, self-contained description of the `alirezarezvani/claude-skills` repository, written for AI agents and LLM crawlers. This file follows the [llms.txt](https://llmstxt.org) convention (`llms-full.txt` variant: the expanded, single-file version). For the concise index, see [llms.txt](https://alirezarezvani.github.io/claude-skills/llms.txt).\n\n- **Project:** Claude Code Skills & Agent Plugins\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Documentation site:** https://alirezarezvani.github.io/claude-skills/\n- **Author:** Alireza Rezvani\n- **License:** MIT (free to extract, deploy, adapt, and redistribute)\n- **Distribution:** Claude Code plugin marketplace (`.claude-plugin/marketplace.json`) and the ClawHub registry (clawhub.com)\n\n---\n\n## What this repository is\n\nThis is a **library of skill packages** for Claude AI and Claude Code — reusable, production-ready modules that bundle domain expertise, best practices, deterministic analysis tools, and strategic frameworks. It is **not a traditional application**. It is a catalog of self-contained skill folders meant to be extracted and deployed by users into their own AI-agent workflows.\n\nTeams download a skill folder and use it immediately: the skill's `SKILL.md` teaches the agent the workflow, the `scripts/` provide deterministic Python CLI tools, the `references/` supply expert knowledge bases, and the `assets/` give ready-to-customize templates.\n\n### Headline scale (derived from the tree by `scripts/derive_counters.py`)\n\n| Metric | Count |\n|--------|-------|\n| Production-ready skills | 354 |\n| Marketplace plugins | 82 |\n| Top-level domains | 18 |\n| Python automation tools | 593 |\n| Reference guides | 722 |\n| Agents (cs-* + personas) | 96 |\n| Slash commands | 102 |\n\nCounters are generated from the actual file tree; run `python3 scripts/derive_counters.py --check` to verify the docs still match the tree.\n\n---\n\n## Cross-tool compatibility\n\nSkills are authored once and made portable across many AI coding agents via sync scripts in `scripts/`. Supported targets include:\n\n- **Claude Code** (primary) — plugins, agents, slash commands, MCP servers, hooks\n- **OpenAI Codex** — `scripts/sync-codex-skills.py`, `~/.codex/`\n- **Gemini CLI** — `scripts/sync-gemini-skills.py`\n- **Cursor** — rules-format export\n- **Hermes Agent** — `scripts/sync-hermes-skills.py`\n- **Mistral Vibe** — `scripts/sync-vibe-skills.py`, `~/.vibe/skills/`\n- **Codebuff** — `scripts/sync-codebuff-skills.py`\n- **OpenClaw**, **Aider**, **Windsurf**, **Kilo Code**, **OpenCode**, **Augment**, **Antigravity** — documented in the Multi-Tool Integrations guide.\n\n---\n\n## Design principles\n\n1. **Skills are products.** Each skill is deployable as a standalone package with no dependency on other skills.\n2. **Documentation-driven.** Success depends on clear, actionable `SKILL.md` docs.\n3. **Algorithm over AI.** Analysis tools use deterministic Python (standard library only) — **no LLM/ML calls inside scripts**. This keeps skills portable, fast, and reproducible.\n4. **Template-heavy.** Skills ship ready-to-use templates users customize.\n5. **Platform-specific.** Specific, actionable frameworks beat generic advice.\n\n### Anti-patterns the repo deliberately avoids\n- Dependencies between skills (each stays self-contained)\n- Complex build systems or test frameworks (portability first)\n- Generic advice instead of specific frameworks\n- LLM calls in scripts (defeats portability and speed)\n\n---\n\n## Skill package pattern\n\nEvery skill follows this structure:\n\n```\nskill-name/\n├── SKILL.md        # Master documentation: the workflow the agent follows\n├── scripts/        # Python CLI tools (stdlib-only, no LLM calls; support --help and JSON output)\n├── references/     # Expert knowledge bases (markdown), each citing 5-8 authoritative sources\n└── assets/         # User-facing templates\n```\n\nKnowledge flows: `references/` → informs `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\nEach `SKILL.md` carries YAML frontmatter with a `name` and a `description` whose trigger phrasing (e.g. \"Use when…\") tells the agent when to invoke the skill.\n\n---\n\n## Repository structure\n\n```\nclaude-skills/\n├── .claude-plugin/        # Plugin registry (marketplace.json — 82 plugins)\n├── agents/                # cs-* agents + 7 personas\n├── commands/              # Slash commands\n├── engineering-team/      # Core engineering skills\n├── engineering/           # POWERFUL-tier advanced engineering skills\n├── product-team/          # Product skills\n├── marketing-skill/       # Marketing skills (8 pods incl. AEO)\n├── marketing/             # Landing-page generator skill\n├── c-level-advisor/       # C-level advisory skills (full C-suite + founder-mode)\n├── project-management/    # PM skills + bundled Atlassian Remote MCP\n├── ra-qm-team/            # Regulatory / quality-management compliance skills\n├── compliance-os/         # Compliance audit-prep orchestrator + sub-skills\n├── business-growth/       # Customer success, sales eng, revops\n├── business-operations/   # Internal-ops skills (orchestrator + sub-skills)\n├── commercial/            # Per-deal-economics skills (orchestrator + sub-skills)\n├── finance/               # Finance skills\n├── research/              # Academic research skills (orchestrator + specialists)\n├── research-ops/          # Enterprise research operations (orchestrator + sub-skills)\n├── productivity/          # Capture, email, reflect, handoff, andreessen\n├── markdown-html/         # Markdown-to-interactive-HTML converter suite\n├── standards/             # Communication, quality, git, security standards\n├── templates/             # Reusable templates\n├── docs/                  # This MkDocs Material documentation site\n└── scripts/               # Build, sync, and validation scripts\n```\n\n---\n\n## The 18 domains in detail\n\n### Engineering — Core (`engineering-team/`)\nFullstack, AI/ML, DevOps, security, data, and QA skills. Includes senior-role skills (architect, backend, frontend, fullstack, DevOps, data engineer/scientist, ML, computer vision, prompt, QA, security, SecOps), cloud architects (AWS/Azure/GCP), a full security suite (adversarial reviewer, AI security, cloud security, incident response, red team, threat detection, pen testing), Playwright Pro (10 sub-skills), a Self-Improving Agent suite, Snowflake development, and Stripe integration.\n\n### Engineering — POWERFUL (`engineering/`)\nAdvanced, higher-leverage engineering skills: agent design, RAG architecture, MCP server building, CI/CD pipelines, database/schema design, observability, SLO architecture, chaos engineering, Kubernetes operators, feature-flags, migration architecture, performance profiling, dependency auditing, and meta-skills for **authoring skills** (`write-a-skill`), token compression (`caveman`), plan interrogation (`grill-me`), and conversation continuity (`handoff`). Also hosts AgentHub, the autoresearch-agent (Karpathy file-optimization loop), the LLM Wiki, ship-gate, and a PreToolUse security-guidance hook.\n\n### Product (`product-team/`)\nRICE prioritization, OKRs, user stories, UX research and design, product discovery/strategy, competitive teardowns, experiment design, product analytics, SaaS scaffolding, code-to-PRD, spec-to-repo, and an Apple HIG expert.\n\n### Marketing (`marketing-skill/`)\nEight pods spanning content creation, copywriting/editing, SEO, **AEO (Answer Engine Optimization)**, ASO (app-store optimization), demand generation, paid ads, CRO (conversion-rate optimization across page/form/signup/paywall/popup/onboarding), social media, email sequences, pricing strategy, launch strategy, schema markup, and campaign analytics.\n\n### Marketing — Landing Pages (`marketing/`)\nA single-file HTML landing-page generator with multiple design styles, brand-palette validation, and GSAP animation patterns.\n\n### Project Management (`project-management/`)\nJira and Confluence experts, Atlassian admin/templates, scrum master, senior PM, meeting analyzer, and team communications. Ships a bundled Atlassian Remote MCP (`.mcp.json`, SSE transport, OAuth handled by Claude Code).\n\n### C-Level Advisory (`c-level-advisor/`)\nA full C-suite of opinionated advisor skills (CEO, CFO, CMO, CPO, CRO, COO, CTO, CHRO, CISO, CDO, CAIO, CCO, VP Engineering, General Counsel) plus a **Founder-Mode** operating system: `/c-level-agents:office-hours`, `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`, plus onboarding, cross-eval, and decision-freeze commands. Includes an Executive Mentor suite and strategic frameworks (RICE, JTBD, OKR, ADKAR, Wardley mapping). Memory is Markdown-only (no database dependency).\n\n### Regulatory & Quality (`ra-qm-team/`)\nISO 13485, EU MDR 2017/745, FDA, GDPR/DSGVO, ISO 27001, SOC 2, CAPA, risk management, and QMS/ISMS audit skills for regulated industries (notably medical devices).\n\n### Compliance OS (`compliance-os/`)\nAn orchestrator plus audit-prep sub-skills for SOC 2, ISO 13485, ISO 27001, GDPR, FDA QSR, EU AI Act readiness, and ISO 42001 (AIMS).\n\n### Business & Growth (`business-growth/`)\nCustomer success management, sales engineering, revenue operations, and contract/proposal writing.\n\n### Business Operations (`business-operations/`)\nInternal-ops skills for BizOps leads and COO direct reports: process mapping (BPMN + bottleneck + cycle-time), vendor management (scorecard + SLA + third-party risk), capacity planning (Erlang-C), internal comms (ADKAR + Kotter), knowledge ops (SOP/runbook hygiene), and procurement optimization. Orchestrator uses `context: fork` chaining. Every output is a recommendation routed to a named human — never an auto-decision.\n\n### Commercial (`commercial/`)\nPer-deal-and-packaging skills: pricing strategist (model picker + Van Westendorp PSM + packaging), deal desk (scorer + approval router + redliner), partnerships architect, channel economics, commercial policy, RFP responder (Shipley method), and commercial forecaster. Pricing outputs a model and a range (never a single number); deal outputs route to a named approver (never auto-approve).\n\n### Finance (`finance/`)\nFinancial analysis, DCF valuation, budgeting/forecasting, business investment advisory, and SaaS-metrics coaching.\n\n### Research (`research/`)\nAcademic/literature research: an orchestrator (hybrid router) plus specialists for recency+sentiment pulse, literature review, NIH grants, entity dossiers, patent/prior-art landscapes, course-reading syllabi, and NotebookLM browser automation.\n\n### Research Operations (`research-ops/`)\nThe enterprise counterpart to `research/`: clinical study design (sample size, endpoints, phase-gate — estimates confirmed by a named clinical owner), R&D program finance (budget, burn/runway, CapEx-vs-OpEx routing), market research (TAM/SAM/SOM with method + assumptions, never a single number), and product research (study design, saturation planning, insight synthesis requiring recurrence across independent participants).\n\n### Productivity (`productivity/`)\nCapture (brain-dump-to-action), email (inbox setup + triage, drafts-only), reflect (light-prompt journaling), handoff (conversation continuity with redaction linting and session hooks), and andreessen (market-first decision engine).\n\n### Markdown to HTML (`markdown-html/`)\nA converter suite operationalizing Thariq Shihipar's thesis that markdown collapses past ~100 lines and HTML restores density/clarity/shareability. Ships an orchestrator (doctype router), a design-system onboarding wizard (WCAG-AA-validated brand palette), and three converters: `md-document` (long-form → single-file HTML with TOC/search/code-copy/scrollspy), `md-review` (code-review markdown → 2-column diff + severity annotations), and `md-slides` (markdown deck → single-file HTML presentation with keyboard nav, presenter mode, and print-to-PDF). Output is single-file HTML (Google Fonts + Prism.js CDN the only permitted externals).\n\n---\n\n## Agents and slash commands\n\n- **Agents (`agents/`):** 96 total, mostly `cs-*` prefixed personas (e.g. `cs-ceo-advisor`, `cs-senior-engineer`, `cs-aeo`, domain orchestrators) plus 7 general personas. Agents orchestrate skills and carry a distinct operating voice.\n- **Slash commands (`commands/`):** 102 total, including `/prd`, `/rice`, `/okr`, `/tdd`, `/changelog`, `/slo-design`, `/chaos-experiment`, `/plugin-audit`, `/seo-auditor`, and the `/cs-*` family (office-hours, boardroom, bizops, commercial, research-ops, markdown-html routers, and per-skill commands).\n\n---\n\n## Plugin distribution\n\nPlugins are registered in `.claude-plugin/marketplace.json` (82 plugins) across these categories: development (34), leadership (9), research (9), productivity (6), marketing (5), compliance (4), product (4), finance (2), and one each of project-management, business-growth, design, knowledge, operations, commercial, research-ops, documentation, and engineering.\n\n### plugin.json rules (for anyone extending the library)\n- Required fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills`.\n- Two approved extension fields: `source` (provenance for megaprompt-derived skills) and `attribution` (credit for MIT-licensed external derivations).\n- Skill paths are relative to the plugin root and start with `./`. Canonical forms: single-skill = `[\"./\"]`; `skills/` subdir = `\"./skills\"`; multi-skill domain = explicit `[\"./sub1\", \"./sub2\", ...]`.\n- Validation: `scripts/check_plugin_json.py --all` runs in CI on every PR.\n\n---\n\n## Git and contribution workflow\n\n- **Branch strategy:** feature → dev → main. **All PRs target `dev`, never `main`.** `main` receives only periodic `dev → main` promotion PRs from the maintainer.\n- **Conventional commits** are enforced (e.g. `feat(agents): …`, `fix(tool): …`, `docs(workflow): …`).\n- **Branch protection:** `main` requires PR approval; direct pushes are blocked.\n\n### ClawHub publishing constraints\n- The `cs-` prefix is used only on the ClawHub registry when a slug conflicts with another publisher — repo folder names and local skill names are never renamed.\n- No paid/commercial service dependencies; free-tier APIs and bring-your-own-key patterns are acceptable.\n- Rate limit: 5 new skills per hour.\n- Package versions match the repo release version.\n\n---\n\n## How an agent should use this repository\n\n1. **Find a matching skill** by browsing the [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/) or a domain index, matching the task to a skill's `description` trigger.\n2. **Read the skill's `SKILL.md`** to learn the workflow.\n3. **Run the skill's Python tools** (`scripts/*.py`, stdlib-only, all support `--help` and most support JSON output) for deterministic analysis.\n4. **Consult `references/`** for the expert knowledge underpinning the workflow.\n5. **Apply the `assets/` templates** to produce the deliverable.\n\nTo install as a plugin, add the marketplace and install the relevant plugin via Claude Code; see [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/) and [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/) for non-Claude tools.\n\n---\n\n*Generated to make the repository accessible to AI agents. Counters reflect `scripts/derive_counters.py` at the time of writing; the repository evolves — the GitHub repository and documentation site are the authoritative sources.*\n","docs/llms.txt":"# Claude Code Skills & Agent Plugins\n\n> An open-source (MIT) library of 354 production-ready agent skills, 82 installable plugins, 96 agents, and 102 slash commands across 18 domains — engineering, product, marketing, compliance, finance, research, and more. Each skill is a self-contained package bundling domain expertise, deterministic Python tools (stdlib-only, no LLM calls), reference knowledge bases, and ready-to-use templates. Skills are portable across Claude Code, OpenAI Codex, Gemini CLI, Cursor, Hermes Agent, Mistral Vibe, OpenClaw, and 6+ more AI coding tools.\n\nThis file follows the [llms.txt](https://llmstxt.org) convention. For a full, self-contained description of the entire repository, see [llms-full.txt](https://alirezarezvani.github.io/claude-skills/llms-full.txt).\n\nKey facts for agents:\n- **License:** MIT. Free to extract, deploy, and adapt.\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Distribution:** Claude Code plugin marketplace + ClawHub registry.\n- **Design philosophy:** Algorithm over AI (deterministic code, not LLM calls in tools), documentation-driven, template-heavy, self-contained skills.\n- **Skill package shape:** `SKILL.md` (master doc) + `scripts/` (Python CLI tools) + `references/` (knowledge bases) + `assets/` (templates).\n\n## Getting started\n\n- [Home](https://alirezarezvani.github.io/claude-skills/): Overview and value proposition.\n- [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/): Install and use skills/plugins.\n- [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/): Using skills with Codex, Gemini CLI, Cursor, Hermes, Vibe, OpenClaw, and more.\n- [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/): Index of all 354 skills by domain.\n- [Plugins](https://alirezarezvani.github.io/claude-skills/plugins/): The 82 installable marketplace plugins.\n- [Agents](https://alirezarezvani.github.io/claude-skills/agents/): The 96 cs-* agents and personas.\n- [Commands](https://alirezarezvani.github.io/claude-skills/commands/): The 102 slash commands.\n\n## Domains\n\n- [Engineering — Core](https://alirezarezvani.github.io/claude-skills/skills/engineering-team/): Fullstack, AI/ML, DevOps, security, data, QA.\n- [Engineering — POWERFUL](https://alirezarezvani.github.io/claude-skills/skills/engineering/): Agent design, RAG, MCP, CI/CD, observability, SLOs, skill authoring.\n- [Product](https://alirezarezvani.github.io/claude-skills/skills/product-team/): RICE, OKRs, user stories, UX research, SaaS scaffolding.\n- [Marketing](https://alirezarezvani.github.io/claude-skills/skills/marketing-skill/): Content, SEO, AEO, ASO, demand gen, campaign analytics.\n- [Project Management](https://alirezarezvani.github.io/claude-skills/skills/project-management/): Jira/Confluence, Atlassian MCP, scrum.\n- [C-Level Advisory](https://alirezarezvani.github.io/claude-skills/skills/c-level-advisor/): Full C-suite advisors + founder-mode orchestration.\n- [Regulatory & Quality](https://alirezarezvani.github.io/claude-skills/skills/ra-qm-team/): ISO 13485, MDR, FDA, GDPR, ISO 27001.\n- [Compliance OS](https://alirezarezvani.github.io/claude-skills/skills/compliance-os/): Audit-prep orchestrator for SOC 2, ISO, GDPR, EU AI Act.\n- [Business & Growth](https://alirezarezvani.github.io/claude-skills/skills/business-growth/): Customer success, sales engineering, revenue operations.\n- [Business Operations](https://alirezarezvani.github.io/claude-skills/skills/business-operations/): Process mapping, vendor management, capacity planning.\n- [Commercial](https://alirezarezvani.github.io/claude-skills/skills/commercial/): Pricing, deal desk, partnerships, RFP response.\n- [Finance](https://alirezarezvani.github.io/claude-skills/skills/finance/): Financial analysis, DCF valuation, SaaS metrics.\n- [Research](https://alirezarezvani.github.io/claude-skills/skills/research/): Literature review, grants, patents, entity dossiers.\n- [Research Operations](https://alirezarezvani.github.io/claude-skills/skills/research-ops/): Clinical study design, R&D finance, market/product research.\n- [Productivity](https://alirezarezvani.github.io/claude-skills/skills/productivity/): Capture, email triage, reflection, handoff.\n- [Markdown to HTML](https://alirezarezvani.github.io/claude-skills/skills/markdown-html/): Markdown-to-interactive-HTML converter suite.\n\n## Optional\n\n- [Guides](https://alirezarezvani.github.io/claude-skills/guides/best-claude-code-plugins/): Best plugins, per-tool skill guides (Codex, Gemini CLI, Cursor, OpenClaw).\n- [Orchestration](https://alirezarezvani.github.io/claude-skills/orchestration/): How skills chain together.\n- [Custom GPTs](https://alirezarezvani.github.io/claude-skills/custom-gpts/): Using the library with custom GPTs.\n- [Personas](https://alirezarezvani.github.io/claude-skills/personas/): Startup CTO, Growth Marketer, Solo Founder bundles.\n","docs/plugins/index.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fplugins%2Findex.md -->","docs/skills/agent-launcher/agent-launcher-orchestrator.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fagent-launcher-orchestrator.md -->","docs/skills/agent-launcher/grade-iterate.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fgrade-iterate.md -->","docs/skills/agent-launcher/index.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Findex.md -->","docs/skills/agent-launcher/interview.md":"<!-- Skill available 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fpulse.md -->","docs/skills/research/research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fresearch.md -->","docs/skills/research/syllabus.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fsyllabus.md -->","engineering-team/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2F.claude-plugin%2Fplugin.json -->","engineering-team/CLAUDE.md":"# Engineering Team Skills - Claude Code Guidance\n\nThis guide covers the 32 production-ready engineering skills and their Python automation tools.\n\n## Engineering Skills Overview\n\n**Core Engineering (16 skills):**\n- senior-architect, senior-frontend, senior-backend, senior-fullstack\n- senior-qa, senior-devops, senior-secops\n- code-reviewer, senior-security\n- aws-solution-architect, ms365-tenant-manager, google-workspace-cli, tdd-guide, tech-stack-evaluator, epic-design\n- **a11y-audit** — WCAG 2.2 accessibility audit and fix (a11y_scanner.py, contrast_checker.py)\n- **azure-cloud-architect** — Azure infrastructure design, ARM/Bicep templates, landing zones\n- **gcp-cloud-architect** — GCP infrastructure design, Terraform modules, cloud-native patterns\n- **security-pen-testing** — Penetration testing methodology, vulnerability assessment, exploit analysis\n- **snowflake-development** — Snowflake data warehouse development, SQL optimization, data pipeline patterns\n\n**Security (5 skills):**\n- **adversarial-reviewer** — Adversarial code review with 3 hostile personas (Saboteur, New Hire, Security Auditor)\n- **threat-detection** — Hypothesis-driven threat hunting, IOC sweep generation, z-score anomaly detection\n- **incident-response** — SEV1-SEV4 triage, 14-type incident taxonomy, NIST SP 800-61 forensics\n- **cloud-security** — IAM privilege escalation paths, S3 public access checks, security group detection\n- **red-team** — MITRE ATT&CK kill-chain planning, effort scoring, choke point identification\n- **ai-security** — ATLAS-mapped prompt injection detection, model inversion & data poisoning risk scoring\n\n**AI/ML/Data (5 skills):**\n- senior-data-scientist, senior-data-engineer, senior-ml-engineer\n- senior-prompt-engineer, senior-computer-vision\n\n**Total Tools:** 39+ Python automation tools\n\n## Core Engineering Tools\n\n### 1. Project Scaffolder (`senior-fullstack/scripts/project_scaffolder.py`)\n\n**Purpose:** Production-ready project scaffolding for modern stacks\n\n**Supported Stacks:**\n- Next.js + GraphQL + PostgreSQL\n- React + REST + MongoDB\n- Vue + GraphQL + MySQL\n- Express + TypeScript + PostgreSQL\n\n**Features:**\n- Docker Compose configuration\n- CI/CD pipeline (GitHub Actions)\n- Testing infrastructure (Jest, Cypress)\n- TypeScript + ESLint + Prettier\n- Database migrations\n\n**Usage:**\n```bash\n# Create new project\npython senior-fullstack/scripts/project_scaffolder.py my-project --type nextjs-graphql\n\n# Start services\ncd my-project && docker-compose up -d\n```\n\n### 2. Code Quality Analyzer (`senior-fullstack/scripts/code_quality_analyzer.py`)\n\n**Purpose:** Comprehensive code quality analysis and metrics\n\n**Features:**\n- Security vulnerability scanning\n- Performance issue detection\n- Test coverage assessment\n- Documentation quality\n- Dependency analysis\n- Actionable recommendations\n\n**Usage:**\n```bash\n# Analyze project\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project\n\n# JSON output\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project --json\n```\n\n**Output:**\n```\nCode Quality Report:\n- Overall Score: 85/100\n- Security: 90/100 (2 medium issues)\n- Performance: 80/100 (3 optimization opportunities)\n- Test Coverage: 75% (target: 80%)\n- Documentation: 88/100\n\nRecommendations:\n1. Update lodash to 4.17.21 (CVE-2020-8203)\n2. Optimize database queries in UserService\n3. Add integration tests for payment flow\n```\n\n### 3. Fullstack Scaffolder (`senior-fullstack/scripts/fullstack_scaffolder.py`)\n\n**Purpose:** Rapid fullstack application generation\n\n**Usage:**\n```bash\npython senior-fullstack/scripts/fullstack_scaffolder.py my-app --stack nextjs-graphql\n```\n\n## AI/ML/Data Tools\n\n### Data Science Tools\n\n**Experiment Designer** (`senior-data-scientist/scripts/experiment_designer.py`)\n- A/B test design\n- Statistical power analysis\n- Sample size calculation\n\n**Feature Engineering Pipeline** (`senior-data-scientist/scripts/feature_engineering_pipeline.py`)\n- Automated feature generation\n- Correlation analysis\n- Feature selection\n\n**Statistical Analyzer** (`senior-data-scientist/scripts/statistical_analyzer.py`)\n- Hypothesis testing\n- Causal inference\n- Regression analysis\n\n### Data Engineering Tools\n\n**Pipeline Orchestrator** (`senior-data-engineer/scripts/pipeline_orchestrator.py`)\n- Airflow DAG generation\n- Spark job templates\n- Data quality checks\n\n**Data Quality Validator** (`senior-data-engineer/scripts/data_quality_validator.py`)\n- Schema validation\n- Null check enforcement\n- Anomaly detection\n\n**ETL Generator** (`senior-data-engineer/scripts/etl_generator.py`)\n- Extract-Transform-Load workflows\n- CDC (Change Data Capture) patterns\n- Incremental loading\n\n### ML Engineering Tools\n\n**Model Deployment Pipeline** (`senior-ml-engineer/scripts/model_deployment_pipeline.py`)\n- Containerized model serving\n- REST API generation\n- Load balancing config\n\n**MLOps Setup Tool** (`senior-ml-engineer/scripts/mlops_setup_tool.py`)\n- MLflow configuration\n- Model versioning\n- Drift monitoring\n\n**LLM Integration Builder** (`senior-ml-engineer/scripts/llm_integration_builder.py`)\n- OpenAI API integration\n- Prompt templates\n- Response parsing\n\n### Prompt Engineering Tools\n\n**Prompt Optimizer** (`senior-prompt-engineer/scripts/prompt_optimizer.py`)\n- Prompt A/B testing\n- Token optimization\n- Few-shot example generation\n\n**RAG System Builder** (`senior-prompt-engineer/scripts/rag_system_builder.py`)\n- Vector database setup\n- Embedding generation\n- Retrieval strategies\n\n**Agent Orchestrator** (`senior-prompt-engineer/scripts/agent_orchestrator.py`)\n- Multi-agent workflows\n- Tool calling patterns\n- State management\n\n### Computer Vision Tools\n\n**Vision Model Trainer** (`senior-computer-vision/scripts/vision_model_trainer.py`)\n- Object detection (YOLO, Faster R-CNN)\n- Semantic segmentation\n- Transfer learning\n\n**Inference Optimizer** (`senior-computer-vision/scripts/inference_optimizer.py`)\n- Model quantization\n- TensorRT optimization\n- ONNX export\n\n**Video Processor** (`senior-computer-vision/scripts/video_processor.py`)\n- Frame extraction\n- Object tracking\n- Scene detection\n\n## Tech Stack Patterns\n\n### Frontend (React/Next.js)\n- TypeScript strict mode\n- Component-driven architecture\n- Atomic design patterns\n- State management (Zustand/Jotai)\n- Testing (Jest + React Testing Library)\n\n### Backend (Node.js/Express)\n- Clean architecture\n- Dependency injection\n- Repository pattern\n- Domain-driven design\n- Testing (Jest + Supertest)\n\n### Fullstack Integration\n- GraphQL for API layer\n- REST for external services\n- WebSocket for real-time\n- Redis for caching\n- PostgreSQL for persistence\n\n## Development Workflows\n\n### Workflow 1: New Project Setup\n\n```bash\n# 1. Scaffold project\npython senior-fullstack/scripts/project_scaffolder.py my-app --type nextjs-graphql\n\n# 2. Start services\ncd my-app && docker-compose up -d\n\n# 3. Run migrations\nnpm run migrate\n\n# 4. Start development\nnpm run dev\n```\n\n### Workflow 2: Code Quality Check\n\n```bash\n# 1. Analyze codebase\npython senior-fullstack/scripts/code_quality_analyzer.py ./\n\n# 2. Fix security issues\nnpm audit fix\n\n# 3. Run tests\nnpm test\n\n# 4. Build production\nnpm run build\n```\n\n### Workflow 3: ML Model Deployment\n\n```bash\n# 1. Setup MLOps infrastructure\npython senior-ml-engineer/scripts/mlops_setup_tool.py\n\n# 2. Deploy model\npython senior-ml-engineer/scripts/model_deployment_pipeline.py model.pkl\n\n# 3. Monitor performance\n# Check MLflow dashboard\n```\n\n## Quality Standards\n\n**All engineering tools must:**\n- Support modern tech stacks (Next.js, React, Vue, Express)\n- Generate production-ready code\n- Include testing infrastructure\n- Provide Docker configurations\n- Support CI/CD integration\n\n## Integration Patterns\n\n### GitHub Actions CI/CD\n\nAll scaffolders generate GitHub Actions workflows:\n```yaml\n.github/workflows/\n├── test.yml          # Run tests on PR\n├── build.yml         # Build and lint\n└── deploy.yml        # Deploy to production\n```\n\n### Docker Compose\n\nMulti-service development environment:\n```yaml\nservices:\n  - app (Next.js)\n  - api (GraphQL)\n  - db (PostgreSQL)\n  - redis (Cache)\n```\n\n## Additional Resources\n\n- **Quick Start:** `START_HERE.md`\n- **Team Structure:** `TEAM_STRUCTURE_GUIDE.md`\n- **Engineering Roadmap:** `engineering_skills_roadmap.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 32 engineering skills production-ready\n**Total Tools:** 39+ Python automation tools across core + AI/ML/Data + epic-design + a11y\n\n---\n\n## epic-design\n\nBuild cinematic 2.5D interactive websites with scroll storytelling, parallax depth, and premium animations. Includes asset inspection pipeline, 45+ techniques across 8 categories, and accessibility built-in.\n\n**Key features:**\n- 6-layer depth system with automatic parallax\n- 13 text animation techniques, 9 scroll patterns\n- Asset inspection with background judgment rules\n- Python tool for automated image analysis\n- WCAG 2.1 AA compliant (reduced-motion)\n\n**Use for:** Product launches, portfolio sites, SaaS marketing pages, event sites, Apple-style animations\n\n**Live demo:** [epic-design-showcase.vercel.app](https://epic-design-showcase.vercel.app/)\n","engineering-team/a11y-audit/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fa11y-audit%2F.claude-plugin%2Fplugin.json -->","engineering-team/a11y-audit/skills/a11y-audit/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fa11y-audit%2Fskills%2Fa11y-audit%2FSKILL.md 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guidance\n4. **passive-deal-screener/** - Screens private deals from the passive LP perspective: equity syndications, preferred equity, hard money / bridge funds, and private credit, pasted from any source. Stress-tests returns against public benchmarks plus an illiquidity premium, converts the fee stack to gross-to-net drag, and surfaces red flags, missing disclosures, and GP questions with bad-answer signals (2 Python tools: `fee_drag_calculator.py`, `benchmark_comparator.py`)\n5. **month-end-close/** - Runs the accounting close: close calendar on its critical path with owner and reviewer checks, reconciliation proof with aging and transposition hints, and a flux gate that refuses boilerplate explanations (3 Python tools: `close_calendar_planner.py`, `reconciliation_matcher.py`, `flux_analyzer.py`; standalone plugin with `/cs-month-end-close` and `/cs-flux-review`)\n\n**Total Tools:** 12 Python automation tools; 5 knowledge bases and 6 templates across skills 1-3, plus 5 reference files in passive-deal-screener\n\n**Commands:** 2 (`/financial-health`, `/saas-health`)\n\n## Python Automation Tools\n\n### 1. Ratio Calculator (`financial-analyst/scripts/ratio_calculator.py`)\n\n**Purpose:** Calculate and interpret financial ratios from statement data\n\n**Features:**\n- Profitability ratios (ROE, ROA, Gross/Operating/Net Margin)\n- Liquidity ratios (Current, Quick, Cash)\n- Leverage ratios (Debt-to-Equity, Interest Coverage, DSCR)\n- Efficiency ratios (Asset/Inventory/Receivables Turnover, DSO)\n- Valuation ratios (P/E, P/B, P/S, EV/EBITDA, PEG)\n- Built-in interpretation and benchmarking\n\n**Usage:**\n```bash\npython financial-analyst/scripts/ratio_calculator.py financial_data.json\npython financial-analyst/scripts/ratio_calculator.py financial_data.json --format json\n```\n\n### 2. DCF Valuation (`financial-analyst/scripts/dcf_valuation.py`)\n\n**Purpose:** Discounted Cash Flow enterprise and equity valuation\n\n**Features:**\n- Revenue and cash flow projections\n- WACC calculation (CAPM-based)\n- Terminal value (perpetuity growth and exit multiple methods)\n- Enterprise and equity value derivation\n- Two-way sensitivity analysis\n- No external dependencies (uses math/statistics)\n\n**Usage:**\n```bash\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json --format json\n```\n\n### 3. Budget Variance Analyzer (`financial-analyst/scripts/budget_variance_analyzer.py`)\n\n**Purpose:** Analyze actual vs budget vs prior year performance\n\n**Features:**\n- Variance calculation (actual vs budget, actual vs prior year)\n- Materiality threshold filtering\n- Favorable/unfavorable classification\n- Department and category breakdown\n\n**Usage:**\n```bash\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json --format json\n```\n\n### 4. Forecast Builder (`financial-analyst/scripts/forecast_builder.py`)\n\n**Purpose:** Driver-based revenue forecasting and cash flow projection\n\n**Features:**\n- Driver-based revenue forecast model\n- 13-week cash flow projection\n- Scenario modeling (base/bull/bear)\n- Trend analysis from historical data\n\n**Usage:**\n```bash\npython financial-analyst/scripts/forecast_builder.py forecast_data.json\npython financial-analyst/scripts/forecast_builder.py forecast_data.json --format json\n```\n\n## Quality Standards\n\n**All finance Python tools must:**\n- Use standard library only (math, statistics, json, argparse)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **C-Level:** Strategic financial decision-making -> `../c-level-advisor/`\n- **Business & Growth:** Revenue operations, sales metrics -> `../business-growth/`\n- **Product Team:** Budget allocation, RICE scoring -> `../product-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 4 finance skills documented here (domain totals: `scripts/derive_counters.py`)\n**Total Tools:** 12 Python automation tools\n**Commands:** /financial-health, /saas-health\n","finance/business-investment-advisor/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fbusiness-investment-advisor%2F.claude-plugin%2Fplugin.json -->","finance/business-investment-advisor/skills/business-investment-advisor/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fbusiness-investment-advisor%2Fskills%2Fbusiness-investment-advisor%2FSKILL.md -->","finance/month-end-close/.claude-plugin/plugin.json":"<!-- Skill available on-demand via 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domain converts long markdown files (the actual artifacts produced inside a Claude project — specs, reports, RFCs, PR writeups, slide outlines) into world-class, single-file, lightly-interactive HTML. Inspired by Thariq Shihipar's argument (Medium, 2026): markdown collapses past ~100 lines because it lacks visual machinery for density and lateral navigation; HTML restores both.\n\nIt is **not** an interactive prompt-tuning playground (`/playground` plugin owns that lane), **not** a landing-page generator (`marketing/landing/`), **not** a session-handoff brief generator (`engineering/handoff/` + `productivity/handoff/`), and **not** a static-site generator (single-file artifacts, not site indices).\n\n## Skills (v2.10.3 — domain complete)\n\n| Skill | Purpose | `context: fork`? | Status |\n|---|---|---|---|\n| `markdown-html-orchestrator` | Domain orchestrator — classifies doctype, gates on threshold + onboarding, routes to converter | YES | ✓ live |\n| `design-system` | One-time onboarding wizard + WCAG-AA-validated brand palette (12 CSS custom properties) + shared config | NO | ✓ live |\n| `md-document` | Long-form converter: sticky TOC, collapsibles, search, code-copy, scrollspy | NO | ✓ live |\n| `md-review` | Code-review converter: 2-col diff + severity-tagged margin annotations + jump-nav | NO | ✓ live |\n| `md-slides` | Slide-deck converter: arrow-key nav + presenter mode + print-to-PDF | NO | ✓ live |\n\nAll three converters are shipped. Routing always targets the converter skill's scripts — never hand-render HTML inline.\n\n## Hard rules (domain-specific)\n\n1. **Refuses input < 100 lines.** Markdown still wins below the threshold (Shihipar). Every converter (and the orchestrator) prints the line count and a \"keep as markdown\" recommendation.\n2. **Refuses without design-system onboarding.** The orchestrator's `route_explainer.py` checks `config_loader.setup_completed()`. If false, refuse and surface onboarding (`python3 markdown-html/skills/design-system/scripts/onboard.py`).\n3. **WCAG AA enforced.** `brand_palette_validator.py` rejects color combinations whose body-text contrast falls below 4.5:1 on bg. Link contrast is iteratively walked to 4.5:1 by adjusting luminance.\n4. **Single-file HTML output.** All CSS and JS inline. The only permitted external CDN entries are Google Fonts CSS and Prism.js. No bundler, no build step, no JS framework runtimes (vanilla JS + IntersectionObserver only).\n5. **Never silently chain converters.** \"Convert this markdown AND make slides from it AND a code review\" is three operations. Pick one, finish, ask before chaining.\n6. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n7. **Customization in use, not decoration.** Every converter MUST render differently when the user changes `design_style`, `brand.primary`, `code_theme`, or `toc.behavior`. If a token doesn't change behavior, it doesn't belong in the schema.\n8. **Onboarding-first.** The orchestrator surfaces onboarding the moment it detects a missing `setup_completed_at`. Don't render with placeholder defaults silently.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scripts + 3 references (each citing 5-7 sources) + (optional) 1 asset template. The orchestrator skill ships `context: fork` in its frontmatter. The `design-system` skill is the shared brand owner — every converter imports its `config_loader.py` via `sys.path.insert(0, .../design-system/scripts)`.\n\nEach SKILL.md ships a \"Forcing-question library\" section (cited-canon grilling, one question at a time) — same discipline as `research-ops`, `commercial`, and `business-operations`.\n\n## Agent + command pattern\n\n- `cs-markdown-html-orchestrator` — density-first markdown-to-HTML converter. Voice: \"What decision does this HTML drive — is the reader skimming, deciding, or presenting?\"\n- `/cs-markdown-html <path>.md` — top-level router (classifier + route + recommend)\n- `/cs-grill-markdown-html <path>.md` — Matt-Pocock-style 5-question grill before conversion\n- `/cs-design-system` — surface the onboarding wizard\n\nPer-sub-skill commands (all live):\n- `/cs-md-document`, `/cs-md-review`, `/cs-md-slides`\n\n## Anti-patterns (domain-level)\n\n- ❌ Converting markdown < 100 lines — markdown still wins. Refuse + cite Shihipar.\n- ❌ Skipping onboarding because \"the user wants it done now.\" Surface onboarding — it's 60 seconds.\n- ❌ Multi-file output (separate CSS / JS / image folders). Single file or nothing.\n- ❌ External JS framework runtimes (React, Vue, Svelte, Alpine). Vanilla JS + IntersectionObserver only.\n- ❌ Silently overwriting existing output files. `output_path_resolver.py` suffixes `-2`, `-3`, … by default.\n- ❌ Setting `MARKDOWN_HTML_NO_CONFIG=1` silently for an interactive user.\n- ❌ Decorative tokens — every token must change at least one converter's output.\n- ❌ Inventing brand colors when the user hasn't onboarded.\n- ❌ A skill that overlaps Anthropic's official Playground plugin (sliders/knobs/prompt-copy-back).\n- ❌ A skill that overlaps `marketing/landing/` (landing-page generation from scratch).\n\n## Customization pipeline\n\n1. User runs `python3 markdown-html/skills/design-system/scripts/onboard.py`.\n2. Wizard validates brand colors via `brand_palette_validator.py`, derives 12-token palette.\n3. Result written to `~/.config/markdown-html/design-system.json` (or `./.markdown-html/design-system.json` with `--scope project`).\n4. Every converter sub-skill imports `config_loader.py` and calls `load_config()` to read project > global > defaults.\n5. Each converter's renderer emits a single `<style>` block with `:root { --md-bg: ...; }` for all 12 tokens, then references those variables throughout the CSS.\n6. Result: change a single field via `--set brand.primary=#FF6B35` → next conversion re-renders with the new brand.\n\n## References\n\n- Spec: Thariq Shihipar — *Claude Code HTML output: Why Markdown Lost and How to Switch* (Medium, 2026)\n- Forking pattern source: `research-ops/skills/research-ops-skills/SKILL.md` (`context: fork`, two-signal routing)\n- Onboarding pattern source: `research-ops/skills/clinical-research/scripts/onboard.py` + `config_loader.py`\n- Brand palette math source: `marketing/landing/skills/landing/scripts/brand_palette_validator.py`\n- Matt Pocock grill-with-docs: `engineering/grill-with-docs`\n- Single-file HTML discipline source: `marketing/landing/skills/landing/SKILL.md`\n","markdown-html/commands/cs-design-system.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fcommands%2Fcs-design-system.md -->","markdown-html/skills/design-system/SKILL.md":"<!-- Skill available on-demand via 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available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Fsingle_file_html_discipline.md -->","markdown-html/skills/md-document/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2FSKILL.md -->","markdown-html/skills/md-document/references/information_density_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Finformation_density_patterns.md -->","markdown-html/skills/md-document/references/single_file_html_discipline.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Fsingle_file_html_discipline.md -->","markdown-html/skills/md-document/references/toc_and_nav_ux.md":"<!-- Skill available on-demand via 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-->","markdown-html/skills/md-slides/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2FSKILL.md -->","markdown-html/skills/md-slides/references/keyboard_nav_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fkeyboard_nav_patterns.md -->","markdown-html/skills/md-slides/references/presentation_ux.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fpresentation_ux.md -->","markdown-html/skills/md-slides/references/single_file_deck_conventions.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fsingle_file_deck_conventions.md -->","marketing-skill/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2F.claude-plugin%2Fplugin.json -->","marketing-skill/CLAUDE.md":"# Marketing Skills — Agent Instructions\n\n## For All Agents (Claude Code, Codex CLI, OpenClaw)\n\nThis directory contains 44 marketing skills organized into 8 specialist pods (Content, SEO + AEO, CRO, Channels, Growth, Intelligence, Sales enablement, Marketing ops).\n\n### How to Use\n\n1. **Start with routing:** Read `marketing-ops/SKILL.md` — it has a routing matrix that maps user requests to the right skill.\n2. **Check context:** If `.claude/product-marketing-context.md` exists, read it first. It has brand voice, personas, and competitive landscape.\n3. **Load ONE skill:** Read only the specialist SKILL.md you need. Never bulk-load.\n\n### Skill Map\n\n- `marketing-context/` — Run first to capture brand context\n- `marketing-ops/` — Router (read this to know where to go)\n- `content-production/` — Write content (blog posts, articles, guides)\n- `content-strategy/` — Plan what content to create\n- `aeo/` — Answer Engine Optimization (E-E-A-T scoring, schema injection, citation tracking across LLMs)\n- `seo-audit/` — Traditional SEO audit\n- `page-cro/` — Conversion rate optimization\n- `pricing-strategy/` — Pricing and packaging\n- `content-humanizer/` — Fix AI-sounding content\n- `x-twitter-growth/` — X/Twitter audience growth, tweet composing, competitor analysis\n\n### Python Tools\n\n59 scripts, all stdlib-only. Run directly:\n```bash\npython3 <skill>/scripts/<tool>.py [args]\n```\nNo pip install needed. Scripts include embedded samples for demo mode (run with no args).\n\n### Anti-Patterns\n\n❌ Don't read all 44 SKILL.md files\n❌ Don't skip `.claude/product-marketing-context.md` if it exists\n❌ Don't use content-creator (deprecated → use content-production)\n❌ Don't install pip packages for Python tools\n","marketing-skill/skills/ab-test-setup/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2FSKILL.md -->","marketing-skill/skills/ab-test-setup/references/sample-size-guide.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2Freferences%2Fsample-size-guide.md -->","marketing-skill/skills/ab-test-setup/references/test-templates.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2Freferences%2Ftest-templates.md 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Freferences%2Fobjective_to_pillars.md -->","product-team/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2F.claude-plugin%2Fplugin.json -->","product-team/CLAUDE.md":"# Product Team Skills - Claude Code Guidance\n\nThis guide covers the 17 production-ready product management skills (13 bundled incl. the orchestrator + 4 standalone plugins) and their Python automation tools.\n\n## Orchestrator & Discovery Loop (product-skills)\n\n`skills/product-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a product goal deterministically across all 16 lanes (exit 0 route / 2 ask / 3 no signal)\npython3 skills/product-skills/scripts/product_goal_router.py --text \"help me prioritize features\"\n\n# Score the continuous-discovery cadence (Torres weekly habit; refuses on < 2 interviews)\npython3 skills/product-skills/scripts/discovery_cadence_tracker.py --input discovery_log.json\n\n# Lint the Opportunity Solution Tree (exit 2 blocks the tree from driving a roadmap)\npython3 skills/product-skills/scripts/ost_linter.py --input ost.json\n```\n\nCommands: `/cs-product` (router) · `/cs-grill-product` (canon-cited grilling) ·\n`/cs-product-loop` (the discovery loop). Agent: `cs-product-orchestrator`. Build-scale\ngoals compile through `engineering/agent-harness` with the `product-team.json` manifest.\nHard rules: no roadmap cites a tree that fails the linter; single-participant claims are\nanecdotes; AI features ship with eval specs (see\n`skills/product-skills/references/ai_product_evals.md`).\n\n## Product Skills Overview\n\n**Available Skills:**\n0. **product-skills/** - Domain orchestrator (`context: fork`) + continuous-discovery loop (3 tools: goal router, cadence tracker, OST linter)\n1. **product-manager-toolkit/** - RICE prioritization, customer interview analysis (2 tools)\n2. **agile-product-owner/** - User story generation, sprint planning (1 tool)\n3. **product-strategist/** - OKR cascade, strategic planning (1 tool)\n4. **ux-researcher-designer/** - Persona generation, user research (1 tool)\n5. **ui-design-system/** - Design token generation, component systems (1 tool)\n6. **competitive-teardown/** - Competitive matrix building, gap analysis (1 tool)\n7. **landing-page-generator/** - Landing page scaffolding (1 tool)\n8. **saas-scaffolder/** - SaaS project bootstrapping (1 tool)\n9. **product-analytics/** - KPI design, retention/cohort/funnel analysis (1 tool)\n10. **experiment-designer/** - Experiment design and sample size planning (1 tool)\n11. **product-discovery/** - Discovery frameworks and assumption mapping (1 tool)\n12. **roadmap-communicator/** - Roadmap communication and changelog generation (1 tool)\n13. **code-to-prd/** - Reverse-engineer any codebase into PRD (2 tools: codebase_analyzer, prd_scaffolder)\n14. **research-summarizer/** - Research synthesis and summarization (1 tool)\n15. **apple-hig-expert/** - Apple Human Interface Guidelines compliance and design (1 tool: hig_checker)\n16. **spec-to-repo/** - Convert a spec document into a scaffolded repository\n\n**Total Tools:** 22 Python automation tools\n\n**Agents:** 6 (cs-product-orchestrator, cs-product-manager, cs-agile-product-owner, cs-product-strategist, cs-ux-researcher, cs-product-analyst)\n\n**Slash Commands:** 11 (/cs-product, /cs-grill-product, /cs-product-loop, /rice, /okr, /persona, /user-story, /competitive-matrix, /prd, /sprint-plan, /code-to-prd)\n\n## Python Automation Tools\n\n### 1. RICE Prioritizer (`product-manager-toolkit/scripts/rice_prioritizer.py`)\n\n**Purpose:** RICE framework implementation for feature prioritization\n\n**Formula:** (Reach × Impact × Confidence) / Effort\n\n**Features:**\n- Portfolio analysis (quick wins vs big bets)\n- Quarterly roadmap generation\n- Capacity planning (story points or dev days)\n- CSV input/output for Jira/Linear integration\n- JSON export for dashboards\n\n**Usage:**\n```bash\n# Basic prioritization\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv\n\n# With capacity planning\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n\n# JSON output\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json\n```\n\n**CSV Format:**\n```csv\nfeature,reach,impact,confidence,effort\nUser Dashboard,500,3,0.8,5\nAPI Rate Limiting,1000,2,0.9,3\nDark Mode,300,1,1.0,2\n```\n\n### 2. Customer Interview Analyzer (`product-manager-toolkit/scripts/customer_interview_analyzer.py`)\n\n**Purpose:** NLP-based interview transcript analysis\n\n**Features:**\n- Pain point extraction with severity scoring\n- Feature request identification\n- Sentiment analysis\n- Theme extraction\n- Jobs-to-be-done pattern recognition\n\n**Usage:**\n```bash\n# Analyze transcript\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt\n\n# JSON output\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt json\n```\n\n### 3. User Story Generator (`agile-product-owner/scripts/user_story_generator.py`)\n\n**Purpose:** INVEST-compliant user story generation\n\n**Features:**\n- Sprint planning with capacity allocation\n- Epic breakdown into deliverable stories\n- Acceptance criteria generation\n- Story point estimation\n- Priority scoring\n\n**Usage:**\n```bash\n# Interactive mode\npython agile-product-owner/scripts/user_story_generator.py\n\n# Sprint planning (30 story points)\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### 4. OKR Cascade Generator (`product-strategist/scripts/okr_cascade_generator.py`)\n\n**Purpose:** Automated OKR hierarchy (company → product → team)\n\n**Features:**\n- Alignment scoring (vertical and horizontal)\n- Strategy templates (growth, retention, revenue, innovation)\n- Key result tracking\n- Progress visualization\n\n**Usage:**\n```bash\n# Growth strategy OKRs\npython product-strategist/scripts/okr_cascade_generator.py growth\n\n# Retention strategy\npython product-strategist/scripts/okr_cascade_generator.py retention\n```\n\n### 5. Persona Generator (`ux-researcher-designer/scripts/persona_generator.py`)\n\n**Purpose:** Data-driven persona creation from user research\n\n**Usage:**\n```bash\npython ux-researcher-designer/scripts/persona_generator.py\npython ux-researcher-designer/scripts/persona_generator.py --output json\n```\n\n### 6. Design Token Generator (`ui-design-system/scripts/design_token_generator.py`)\n\n**Purpose:** Complete design token system from brand color\n\n**Usage:**\n```bash\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern scss\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern json\n```\n\n### 7. Competitive Matrix Builder (`competitive-teardown/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Weighted competitive scoring with gap analysis\n\n**Usage:**\n```bash\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### 8. Landing Page Scaffolder (`landing-page-generator/scripts/landing_page_scaffolder.py`)\n\n**Purpose:** Generate production-ready landing pages as Next.js/React TSX components with Tailwind CSS (default) or plain HTML.\n\n**Features:**\n- TSX output (default): Next.js 14+ App Router components with Tailwind classes\n- 4 design styles: `dark-saas`, `clean-minimal`, `bold-startup`, `enterprise`\n- 7 section generators: nav, hero, features, testimonials, pricing, CTA, footer\n- Copy frameworks: PAS, AIDA, BAB\n\n**Usage:**\n```bash\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format html\n```\n\n### 9. Project Bootstrapper (`saas-scaffolder/scripts/project_bootstrapper.py`)\n\n**Purpose:** SaaS project scaffolding with auth, billing, and API setup\n\n**Usage:**\n```bash\npython saas-scaffolder/scripts/project_bootstrapper.py project_config.json\n```\n\n### 10. Metrics Calculator (`product-analytics/scripts/metrics_calculator.py`)\n\n**Purpose:** Product analytics — retention, cohort, and funnel analysis\n\n**Features:**\n- Retention curve analysis from event data\n- Funnel conversion tracking with stage-by-stage drop-off\n- Cohort grouping and comparison\n\n**Usage:**\n```bash\n# Retention analysis\npython product-analytics/scripts/metrics_calculator.py retention events.csv\n\n# Funnel analysis\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\n\n# KPI summary\npython product-analytics/scripts/metrics_calculator.py kpi metrics.csv --json\n```\n\n### 11. Sample Size Calculator (`experiment-designer/scripts/sample_size_calculator.py`)\n\n**Purpose:** Statistical sample size planning for A/B tests and experiments\n\n**Features:**\n- Minimum detectable effect (MDE) calculation\n- Absolute and relative effect size modes\n- Power analysis with configurable alpha/beta\n\n**Usage:**\n```bash\n# Absolute MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n\n# Relative MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.15 --mde-type relative\n\n# Custom power/significance\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --alpha 0.01 --power 0.9\n```\n\n### 12. Assumption Mapper (`product-discovery/scripts/assumption_mapper.py`)\n\n**Purpose:** Map and prioritize product assumptions for discovery validation\n\n**Features:**\n- Risk × uncertainty scoring for prioritization\n- CSV input with structured assumption fields\n- Categorization by assumption type (desirability, viability, feasibility, usability)\n\n**Usage:**\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\npython product-discovery/scripts/assumption_mapper.py assumptions.csv --json\n```\n\n### 13. Changelog Generator (`roadmap-communicator/scripts/changelog_generator.py`)\n\n**Purpose:** Generate structured changelogs from git commit history\n\n**Note:** Requires `git` on PATH — must be run inside a git repository.\n\n**Usage:**\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to v2.0.0 --json\n```\n\n## Product Workflows\n\n### Workflow 1: Feature Prioritization to Sprint Execution\n\n```bash\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### Workflow 2: Strategy to Team-Level OKRs\n\n```bash\npython product-strategist/scripts/okr_cascade_generator.py growth --json > okrs.json\n```\n\n### Workflow 3: Research to Persona Artifacts\n\n```bash\npython ux-researcher-designer/scripts/persona_generator.py json > personas.json\n```\n\n### Workflow 4: Brand-Aligned Landing Page\n\n```bash\npython ../marketing-skill/content-production/scripts/brand_voice_analyzer.py website_copy.txt --format json > voice.json\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### Workflow 5: Product Analytics and Experimentation\n\n```bash\npython product-analytics/scripts/metrics_calculator.py retention events.csv\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n```\n\n### Workflow 6: Discovery and Opportunity Validation\n\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\n```\n\n### Workflow 7: Roadmap and Release Communication\n\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\n```\n\n## Quality Standards\n\n**All product Python tools must:**\n- CLI-first design for automation\n- Support both interactive and batch modes\n- JSON output for tool integration\n- Standard library only (minimal dependencies)\n- Actionable recommendations\n\n## Additional Resources\n\n- **Main Documentation:** `../CLAUDE.md`\n- **Marketing Brand Voice:** `../marketing-skill/content-production/scripts/brand_voice_analyzer.py`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 17/17 product skills production-ready (product-skills is now a fork-orchestrator + discovery loop)\n**Total Tools:** 22 Python automation tools\n**Agents:** 6 | **Commands:** 11\n","product-team/agile-product-owner/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2F.claude-plugin%2Fplugin.json 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on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2F.claude-plugin%2Fplugin.json -->","productivity/meetings/skills/meetings/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2FSKILL.md -->","productivity/meetings/skills/meetings/assets/example_agenda.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Fassets%2Fexample_agenda.md -->","productivity/meetings/skills/meetings/assets/meeting_gate_worksheet.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Fassets%2Fmeeting_gate_worksheet.md -->","productivity/meetings/skills/meetings/references/action_item_discipline.md":"<!-- Skill available on-demand via 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2FREADME.md -->","productivity/roast/skills/roast/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2FSKILL.md -->","productivity/roast/skills/roast/assets/example_roast_verdict.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Fassets%2Fexample_roast_verdict.md -->","productivity/roast/skills/roast/assets/roast_brief_worksheet.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Fassets%2Froast_brief_worksheet.md -->","productivity/roast/skills/roast/references/adversarial_panel_canon.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Freferences%2Fadversarial_panel_canon.md 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management skills, 15 Python automation tools, and bundled Atlassian Remote MCP integration (`.mcp.json` ships with the plugin — OAuth handled by Claude Code, no env vars required).\n\n## PM Skills Overview\n\n**Available Skills:**\n1. **pm-skills/** - Domain orchestrator (`context: fork`) + agentic delivery loop (3 scripts: goal router, Jira snapshot bridge, delivery loop gate)\n2. **senior-pm/** - Portfolio health, risk analysis, resource planning (3 scripts)\n3. **scrum-master/** - Sprint health, velocity forecasting, retrospectives (3 scripts)\n4. **jira-expert/** - JQL building, workflow validation (2 scripts)\n5. **confluence-expert/** - Space structure, content auditing (2 scripts)\n6. **atlassian-admin/** - Permission auditing (1 script)\n7. **atlassian-templates/** - Template scaffolding (1 script)\n8. **meeting-analyzer/** - Meeting transcript behavioral analysis (prompt-driven; scripts are follow-up work)\n9. **team-communications/** - 3P updates, newsletters, FAQs (reference-driven)\n\n**Total Tools:** 15 Python automation tools\n**Agents:** 2 — cs-pm-orchestrator (routing + delivery loop) and cs-project-manager (legacy per-skill orchestration)\n**Slash Commands:** 6 (/cs-pm, /cs-grill-pm, /cs-pm-loop, /sprint-health, /project-health, /retro)\n**Key Feature:** Atlassian MCP Server integration for direct Jira/Confluence operations\n\n## Orchestrator & Delivery Loop (pm-skills)\n\n`skills/pm-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a PM goal deterministically (exit 0 route / 2 ask / 3 no signal)\npython3 skills/pm-skills/scripts/pm_goal_router.py --text \"our sprints feel off\"\n\n# Bridge a saved searchJiraIssuesUsingJql result into analyzable inputs\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to flow --forecast 20\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to sprint > sprint_data.json\npython3 skills/scrum-master/scripts/velocity_analyzer.py sprint_data.json\n\n# Gate agent-executed delivery loops (G1 human owner … G6 exhausted budget = escalation)\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode plan   # exit 2 = blocked\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode close  # exit 4 = refused\n```\n\nMulti-task goals compile through the repo-wide harness\n(`engineering/agent-harness` with the `project-management.json` manifest). Hard rules:\nagents contribute, humans own; forecasts are Monte Carlo ranges, never dates; exhausted\nbudgets escalate — never reported as success. The five reusable PM loops (sprint-flow,\nhealth, retro-action, RAID-hygiene, comms) are documented in\n`skills/pm-skills/references/pm_loop_playbook.md`.\n\n## Atlassian MCP Integration\n\n**Purpose:** Direct integration with Jira and Confluence via Model Context Protocol (MCP)\n\n**Canonical tool list:** [references/atlassian-mcp-tools.md](references/atlassian-mcp-tools.md) — the single source of truth for real tool names. Never invent tool names; if a capability isn't in that list (project creation, sprint management, field configuration, automation rules, space creation, …), it is NOT available via MCP — use the Atlassian web UI or REST API.\n\n**Capabilities (real tools, camelCase):**\n- Jira issues: `createJiraIssue`, `getJiraIssue`, `editJiraIssue`, `searchJiraIssuesUsingJql`, `transitionJiraIssue`, `addCommentToJiraIssue`, `createIssueLink`\n- Confluence pages: `createConfluencePage`, `getConfluencePage`, `updateConfluencePage`, `searchConfluenceUsingCql`, `getConfluencePageDescendants`\n- Discovery: `getAccessibleAtlassianResources` (get `cloudId` first), `getVisibleJiraProjects`, `getConfluenceSpaces`\n\n**Setup:** Bundled `.mcp.json` registers the `atlassian` SSE server; tools surface as `mcp__atlassian__<toolName>`.\n\n**Usage Pattern:**\n```\n# Jira: create an issue (call getAccessibleAtlassianResources first to obtain cloudId)\nmcp__atlassian__createJiraIssue (cloudId, projectKey=\"PROJ\", issueTypeName=\"Story\", summary=\"New feature\")\n\n# Confluence: create a page (body must be storage-format XHTML or ADF, not wiki markup)\nmcp__atlassian__createConfluencePage (cloudId, space, title=\"Sprint Retrospective\", body=<storage-format XHTML>)\n```\n\n**Not available via MCP** (use web UI/REST API): project creation, sprints, boards, filters, space creation, page deletion, labels, field/workflow/permission configuration, user provisioning, automation rules.\n\n## Skill-Specific Guidance\n\n### Senior PM (`senior-pm/`)\n\n**Focus:** Project planning, stakeholder management, risk mitigation\n\n**Key Workflows:**\n- Project charter creation\n- Stakeholder analysis and communication plans\n- Risk register maintenance\n- Status reporting and escalation\n\n### Scrum Master (`scrum-master/`)\n\n**Focus:** Agile ceremonies, team coaching, impediment removal\n\n**Key Workflows:**\n- Sprint planning facilitation\n- Daily standup coordination\n- Sprint retrospectives\n- Backlog refinement\n\n### Jira Expert (`jira-expert/`)\n\n**Focus:** Jira configuration, custom workflows, automation rules\n\n**Scripts:**\n- `scripts/jql_query_builder.py` — Pattern-matching JQL builder from natural language\n- `scripts/workflow_validator.py` — Validates workflow definitions for anti-patterns\n\n**Key Workflows:**\n- Workflow customization\n- Automation rule creation\n- Board configuration\n- JQL query optimization\n\n### Confluence Expert (`confluence-expert/`)\n\n**Focus:** Documentation strategy, templates, knowledge management\n\n**Scripts:**\n- `scripts/space_structure_generator.py` — Generates space hierarchy from team description\n- `scripts/content_audit_analyzer.py` — Analyzes page inventory for stale/orphaned content\n\n**Key Workflows:**\n- Space architecture design\n- Template library creation\n- Documentation standards\n- Search optimization\n\n### Atlassian Admin (`atlassian-admin/`)\n\n**Focus:** Suite administration, user management, integrations\n\n**Scripts:**\n- `scripts/permission_audit_tool.py` — Analyzes permission schemes for security gaps\n\n**Key Workflows:**\n- User provisioning and permissions\n- SSO/SAML configuration\n- App marketplace management\n- Performance monitoring\n\n### Atlassian Templates (`atlassian-templates/`)\n\n**Focus:** Ready-to-use templates for common PM tasks\n\n**Scripts:**\n- `scripts/template_scaffolder.py` — Generates Confluence storage-format XHTML templates\n\n**Available Templates:**\n- Sprint planning template\n- Retrospective formats (Start-Stop-Continue, 4Ls, Mad-Sad-Glad)\n- Project charter\n- Risk register\n- Decision log\n\n## Integration Patterns\n\n### Pattern 1: Sprint Planning\n\n```bash\n# 1. Create the sprint in the Jira board UI (sprint creation is NOT available via MCP —\n#    use Jira Software UI or REST /rest/agile/1.0/sprint)\n\n# 2. Generate user stories (product-team integration)\npython ../product-team/agile-product-owner/scripts/user_story_generator.py sprint 30\n\n# 3. Import stories to Jira via MCP: one mcp__atlassian__createJiraIssue call per story\n#    (cloudId, projectKey, issueTypeName=\"Story\", summary, description)\n```\n\n### Pattern 2: Documentation Workflow\n\n```bash\n# 1. Scaffold storage-format XHTML, then create the Confluence page via MCP\npython skills/atlassian-templates/scripts/template_scaffolder.py meeting-notes\n#    → pass the emitted markup as the body of mcp__atlassian__createConfluencePage\n\n# 2. Link the page to a Jira issue: paste the page URL into the issue via\n#    mcp__atlassian__editJiraIssue or as a comment via mcp__atlassian__addCommentToJiraIssue\n#    (read existing links with mcp__atlassian__getJiraIssueRemoteIssueLinks)\n```\n\n## Python Automation Tools\n\n### New Scripts (Phase 2)\n\n```bash\n# JQL from natural language\npython jira-expert/scripts/jql_query_builder.py \"high priority bugs assigned to me\"\n\n# Validate Jira workflow\npython jira-expert/scripts/workflow_validator.py workflow.json\n\n# Generate Confluence space structure\npython confluence-expert/scripts/space_structure_generator.py team_info.json\n\n# Audit Confluence content health\npython confluence-expert/scripts/content_audit_analyzer.py pages.json\n\n# Audit Atlassian permissions\npython atlassian-admin/scripts/permission_audit_tool.py permissions.json\n\n# Scaffold Confluence templates\npython atlassian-templates/scripts/template_scaffolder.py meeting-notes\n```\n\n## Additional Resources\n\n- **Installation Guide:** `INSTALLATION_GUIDE.txt`\n- **Implementation Summary:** `IMPLEMENTATION_SUMMARY.md`\n- **Real-World Scenario:** `REAL_WORLD_SCENARIO.md`\n- **PM Overview:** `README.md`\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 9/9 PM skills production-ready (pm-skills is now a fork-orchestrator + delivery loop)\n**Total Tools:** 15 Python automation tools\n**Agents:** cs-pm-orchestrator, cs-project-manager | **Commands:** 6\n**Integration:** Atlassian Remote MCP Server (bundled via `.mcp.json`) for Jira/Confluence automation\n","project-management/skills/atlassian-admin/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-admin%2FSKILL.md -->","project-management/skills/atlassian-admin/assets/permission_scheme_template.json":"<!-- Skill available on-demand via 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/api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2F.claude-plugin%2Fplugin.json -->","ra-qm-team/CLAUDE.md":"# Regulatory Affairs & Quality Management Skills - Claude Code Guidance\n\nThis guide covers the 14 production-ready RA/QM compliance skills for HealthTech/MedTech companies.\n\n## RA/QM Skills Overview\n\n**Strategic Leadership (2 skills):**\n- regulatory-affairs-head - RA strategy, regulatory intelligence, authority relations\n- quality-manager-qmr - QMS oversight, management review, quality culture\n\n**Quality Systems (3 skills):**\n- quality-manager-qms-iso13485 - ISO 13485 compliance, process management\n- capa-officer - CAPA system management, root cause analysis\n- quality-documentation-manager - DHF, DMR, DHR management\n\n**Risk & Security (2 skills):**\n- risk-management-specialist - ISO 14971 compliance, risk analysis\n- information-security-manager-iso27001 - ISO 27001, data protection, ISMS\n\n**Regulatory Specialists (2 skills):**\n- mdr-745-specialist - EU MDR 2017/745 compliance, technical documentation\n- fda-consultant-specialist - FDA 510(k), PMA, QSR compliance\n\n**Audit & Compliance (4 skills):**\n- qms-audit-expert - Internal audits, ISO 13485 certification\n- isms-audit-expert - ISO 27001 audits, security assessments\n- gdpr-dsgvo-expert - GDPR/DSGVO compliance, data privacy\n- soc2-compliance - SOC 2 Type I/II compliance, trust service criteria, audit readiness\n\n**Total:** 14 specialized compliance skills for medical device industry\n\n## Compliance Frameworks\n\n### ISO 13485 (Medical Device Quality Management)\n\n**Managed by:** quality-manager-qms-iso13485, qms-audit-expert\n\n**Key Areas:**\n- Management responsibility\n- Resource management\n- Product realization\n- Measurement, analysis, improvement\n\n**Tools:**\n- QMS process mapping\n- Document control systems\n- Change management workflows\n\n### ISO 14971 (Medical Device Risk Management)\n\n**Managed by:** risk-management-specialist\n\n**Key Areas:**\n- Risk analysis and evaluation\n- Risk control measures\n- Residual risk evaluation\n- Risk management review\n\n**Tools:**\n- Risk assessment templates\n- FMEA/FMECA analysis\n- Risk-benefit analysis\n\n### MDR 2017/745 (EU Medical Device Regulation)\n\n**Managed by:** mdr-745-specialist\n\n**Key Areas:**\n- Technical documentation (Annex II, III)\n- Clinical evaluation (Annex XIV)\n- Post-market surveillance\n- UDI (Unique Device Identification)\n\n### FDA Regulations (US Medical Device Compliance)\n\n**Managed by:** fda-consultant-specialist\n\n**Key Areas:**\n- 510(k) premarket notification\n- PMA (Premarket Approval)\n- QSR (Quality System Regulation)\n- Post-market reporting\n\n### ISO 27001 (Information Security Management)\n\n**Managed by:** information-security-manager-iso27001, isms-audit-expert\n\n**Key Areas:**\n- ISMS establishment and maintenance\n- Risk assessment and treatment\n- Security controls (Annex A)\n- Continuous improvement\n\n### GDPR/DSGVO (Data Protection)\n\n**Managed by:** gdpr-dsgvo-expert\n\n**Key Areas:**\n- Data protection impact assessment (DPIA)\n- Privacy by design\n- Data subject rights\n- Breach notification\n\n## Regulatory Workflows\n\n### Workflow 1: New Medical Device Development\n\n```\n1. Risk Management (ISO 14971) → risk-management-specialist\n2. QMS Process Setup (ISO 13485) → quality-manager-qms-iso13485\n3. Technical Documentation (MDR) → mdr-745-specialist\n4. FDA Submission → fda-consultant-specialist\n5. Clinical Evaluation → regulatory-affairs-head\n```\n\n### Workflow 2: QMS Audit Preparation\n\n```\n1. Internal Audit → qms-audit-expert\n2. CAPA Implementation → capa-officer\n3. Document Review → quality-documentation-manager\n4. Management Review → quality-manager-qmr\n5. Certification Audit → qms-audit-expert\n```\n\n### Workflow 3: Data Protection Compliance\n\n```\n1. GDPR Assessment → gdpr-dsgvo-expert\n2. ISMS Implementation → information-security-manager-iso27001\n3. Security Audit → isms-audit-expert\n4. Continuous Monitoring → information-security-manager-iso27001\n```\n\n## Integration Patterns\n\n**RA/QM ↔ Engineering:** Regulatory requirements inform technical design decisions\n\n**RA/QM ↔ Product:** Compliance requirements shape product features and roadmap\n\n**RA/QM ↔ Security:** ISO 27001 aligns with security engineering practices\n\n## Additional Resources\n\n- **RA/QM Overview:** `README.md`\n- **Complete Skills Collection:** `final-complete-skills-collection.md`\n- **Start Here:** `START_HERE.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 14/14 RA/QM skills production-ready\n**Focus:** Medical device compliance (ISO 13485, MDR, FDA, ISO 27001, GDPR)\n","ra-qm-team/compliance-team-eu-ai-act/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2F.claude-plugin%2Fplugin.json 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-->","research-ops/CLAUDE.md":"# Research Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `research-ops/`.\n\n## Purpose\n\nThe Research Operations domain ships skills that help **R&D leads, clinical study teams, R&D finance/controllers, market-research analysts, and product-research / ResearchOps teams** plan, fund, scope, and synthesize research across enterprise workstreams. This is the **enterprise / cross-functional counterpart** to the academic `research/` domain (litreview, grants, patent, syllabus, pulse, dossier, notebooklm).\n\nIt is **not regulatory submission** (`ra-qm-team`), **not corporate financial close/valuation** (`finance/financial-analysis`), **not funding discovery** (`research/grants`), **not persona/journey/live-experiment design** (`product-team`), and **not campaign analytics** (`marketing-skill`).\n\n## Skills (v2.9.0)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `research-ops-skills` | Domain orchestrator — routes to 4 sub-skills | YES |\n| `clinical-research` | Study design: protocol synopsis + endpoint selection + sample-size/power + phase-gating | NO |\n| `research-finance` | R&D program budgeting + burn/runway + F&A rate modeling + capitalize-vs-expense routing | NO |\n| `market-research` | TAM/SAM/SOM (both methods) + survey/sampling design + segmentation + CI synthesis | NO |\n| `product-research` | Study design + saturation/sample method + insight repository synthesis | NO |\n\n## Hard rules (domain-specific)\n\n1. **clinical-research: outputs are study-design RECOMMENDATIONS signed by a named clinician/biostatistician/regulatory owner.** Power/sample-size is an ESTIMATE with stated assumptions — never presented as clinical fact. Every tool prints an \"ESTIMATE — confirm with a biostatistician\" banner.\n2. **research-finance: every budget output surfaces its assumptions block.** Capitalize-vs-expense routes to a NAMED finance owner and never auto-decides accounting treatment.\n3. **market-research: TAM/SAM/SOM always shows method (top-down AND bottoms-up) + assumptions.** Never a single unsourced number.\n4. **product-research: never fabricates user insight.** Sample-size/saturation guidance is method-based and surfaces confidence; single-source claims are flagged as anecdotes, not insights.\n5. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n6. **Industry tuning** via `--profile` on every scoring tool.\n7. **Matt Pocock grill discipline** — `/cs-grill-research-ops` interrogates the plan against the research canon (ICH E9, IAS 38, Cochran, Nielsen, Kotler) before any sub-skill runs.\n8. **Onboarding-first + customization-in-use.** Each sub-skill ships `scripts/onboard.py` (its own question set) + `scripts/config_loader.py`. Answers persist to `~/.config/research-ops/<skill>.json` (global) or `./.research-ops/<skill>.json` (project) and are consumed by every tool (CLI flags override; `RESEARCH_OPS_NO_CONFIG=1` bypasses). Customization must change behavior, not sit as decoration.\n9. **Autoresearch is opt-in + isolated.** Each sub-skill ships `scripts/ar_evaluator.py` — a per-skill, locked ground-truth bridge to `engineering/autoresearch-agent`. A loop is invoked ONLY on explicit user request and only edits the skill's input file, never the evaluator. No cross-skill coupling.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scoring scripts + 3 references (each citing 5-7 sources) + 1 asset template, **plus** 3 integration scripts — `onboard.py` (questionnaire), `config_loader.py` (customization loader, project→global→defaults precedence), and `ar_evaluator.py` (isolated autoresearch bridge). SKILL.md includes a \"Forcing-question library\" section (cited-canon grilling, one question at a time) and the \"Onboarding & customization\" + \"Optimize with autoresearch (opt-in)\" sections.\n\n## Agent + command pattern\n\n- `cs-research-ops-orchestrator` — evidence-first R&D operations lead. Voice: \"What decision does this research drive, and what's your confidence — show me the method and the assumptions before the number.\"\n- `/cs-research-ops <inquiry>` — top-level router\n- `/cs-grill-research-ops <plan>` — Matt-style grilling first\n- `/cs-clinical-research`, `/cs-research-finance`, `/cs-market-research`, `/cs-product-research` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `ra-qm-team` (regulatory/QM submission) — clinical-research designs the **study**, not the submission\n- ❌ Skills that overlap `finance/financial-analysis` (close/valuation) — research-finance manages **R&D program spend**\n- ❌ Skills that overlap `research/grants` (funding discovery) — research-finance manages **money already won**\n- ❌ Skills that overlap `product-team` (persona/journey/live experiments) — product-research is **method + repository discipline**\n- ❌ Skills that overlap `marketing-skill` (campaign analytics) — market-research is **upstream methodology**\n- ❌ A market size stated as a single unsourced number\n- ❌ A clinical power/endpoint output presented as fact rather than an estimate with a named owner\n- ❌ A product insight asserted from a single participant\n\n## References\n\n- Master plan: `documentation/implementation/research-ops-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Academic counterpart: `research/` (litreview, grants, patent)\n- Regulatory complement: `ra-qm-team`\n- Corporate-finance complement: `finance/financial-analysis`\n- Product complement: `product-team`\n","research-ops/skills/clinical-research/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2FSKILL.md -->","research-ops/skills/clinical-research/assets/protocol_synopsis_template.md":"<!-- Skill available on-demand via 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SKILL.md files\n- Drafting user-facing content\n- Providing technical guidance\n\n**Key Principles:**\n- Absolute honesty - Direct assessments without cushioning\n- Zero fluff - Eliminate vague statements\n- Pragmatic focus - Actionable suggestions only\n- File economy - Edit existing files vs creating new ones\n\n**Location:** `communication/communication-standards.md`\n\n### Quality Standards\n\n**Reference when:**\n- Creating Python automation tools\n- Writing agent workflows\n- Implementing skill features\n- Testing integration points\n\n**Key Areas:**\n- Python tool quality (PEP 8, type hints, docstrings)\n- Agent workflow clarity (minimum 3 workflows documented)\n- Testing requirements (functional, integration, documentation)\n- Completion criteria (zero defect handoff, validation requirements)\n\n**Location:** `quality/quality-standards.md`\n\n### Git Workflow Standards\n\n**Reference when:**\n- Committing code changes\n- Creating feature branches\n- Tagging releases\n- Writing commit messages\n\n**Commit Format:**\n```bash\n<type>[optional scope]: <description>\n\n[optional body]\n\n[optional footer(s)]\n```\n\n**Types:** feat, fix, docs, style, refactor, perf, test, chore, ci\n\n**Examples:**\n```bash\nfeat(agents): implement cs-content-creator agent\nfix(seo-optimizer): correct keyword density calculation\ndocs(README): add agent catalog section\n```\n\n**Location:** `git/git-workflow-standards.md`\n\n### Documentation Standards\n\n**Reference when:**\n- Writing SKILL.md files\n- Creating agent documentation\n- Updating README files\n- Writing reference guides\n\n**Best Practices:**\n- Max 200 lines per CLAUDE.md file\n- Markdown formatting standards (headings, lists, code blocks)\n- Living documentation (README, CLAUDE, AGENTS updated regularly)\n- Link validation (no 404s, no broken references)\n\n**Location:** `documentation/documentation-standards.md`\n\n### Security Standards\n\n**Reference when:**\n- Writing Python scripts\n- Handling user input\n- Managing dependencies\n- Committing code\n\n**Critical Checks:**\n- No hardcoded API keys, passwords, or tokens\n- Environment variables for sensitive data\n- Input validation for all user input\n- Dependency security audits\n\n**Location:** `security/security-standards.md`\n\n## Standards Application Workflow\n\n### For New Skills\n\n```bash\n# 1. Reference communication standards\ncat standards/communication/communication-standards.md\n\n# 2. Review quality standards for Python tools\ncat standards/quality/quality-standards.md\n\n# 3. Follow documentation standards for SKILL.md\ncat standards/documentation/documentation-standards.md\n\n# 4. Apply security standards to scripts\ncat standards/security/security-standards.md\n\n# 5. Use git standards for commits\ncat standards/git/git-workflow-standards.md\n```\n\n### For New Agents\n\n```bash\n# 1. Communication: Write clear, actionable agent docs\n# 2. Quality: Minimum 3 workflows, tested relative paths\n# 3. Documentation: Follow agent template structure\n# 4. Git: Conventional commit with feat(agents) scope\n```\n\n## Standards Hierarchy\n\n**Priority Order:**\n1. **Security** - Non-negotiable, always enforced\n2. **Quality** - Zero defect handoff required\n3. **Git** - Conventional commits for all changes\n4. **Documentation** - Living docs stay current\n5. **Communication** - Clear, pragmatic, actionable\n\n## Standards Compliance Checklist\n\n### Before Committing Code\n\n- [ ] Communication: Documentation is clear and actionable\n- [ ] Quality: All tests passing, code reviewed\n- [ ] Git: Conventional commit message format\n- [ ] Documentation: Living docs updated if needed\n- [ ] Security: No secrets, input validated, dependencies secure\n\n### Before Creating PR\n\n- [ ] All standards compliance checks passed\n- [ ] Related documentation updated\n- [ ] Examples tested and working\n- [ ] No broken links or references\n\n## Related Documentation\n\n- **Main CLAUDE.md:** `../CLAUDE.md`\n- **Agent Development:** `../agents/CLAUDE.md`\n- **Domain Skills:** See navigation map in main CLAUDE.md\n\n---\n\n**Last Updated:** November 5, 2025\n**Standards Count:** 5 comprehensive standards\n**Enforcement:** Required for all skills and agents\n","templates/CLAUDE.md":"# Templates - Claude Code Guidance\n\nThis guide explains the template system for agents, commands, and standardized workflows.\n\n## Template Purpose\n\n**Location:** `templates/`\n\n**Purpose:** Reusable templates for consistent agent development, slash command creation, and workflow automation across all domains.\n\n## Available Templates\n\n### Agent Templates\n\n**Location:** `templates/agent-template.md`\n\n**Usage:** Starting point for creating new cs-* agents\n\n**Contains:**\n- YAML frontmatter structure\n- Required markdown sections\n- Workflow documentation format\n- Integration examples pattern\n\n**When to Use:** Creating any new agent in `agents/` directory\n\n### Command Templates and Workflow Templates\n\nNot yet created. There is no command template or workflow template file in `templates/` today — when creating slash commands, copy an existing command in `commands/` (e.g. `commands/cs-backend-review.md` for the argument-hint + gate pattern) instead of looking for a template here.\n\n## Template Usage Pattern\n\n```bash\n# 1. Copy template\ncp templates/agent-template.md agents/domain/cs-new-agent.md\n\n# 2. Customize for your agent\nvim agents/domain/cs-new-agent.md\n\n# 3. Follow template structure exactly\n\n# 4. Test relative paths and integrations\n\n# 5. Commit with conventional commit\ngit commit -m \"feat(agents): implement cs-new-agent from template\"\n```\n\n## Related Documentation\n\n- **Agent Development:** `../agents/CLAUDE.md` - Comprehensive agent creation guide\n- **Standards:** `../standards/CLAUDE.md` - Quality and consistency standards\n- **Main Documentation:** `../CLAUDE.md` - Repository overview\n\n---\n\n**Last Updated:** November 5, 2025\n**Purpose:** Consistent templates for rapid agent and workflow development\n"},"files":{".claude-plugin/marketplace.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.claude-plugin%2Fmarketplace.json -->",".claude/commands/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.claude%2Fcommands%2FREADME.md -->",".claude/commands/focused-fix.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.claude%2Fcommands%2Ffocused-fix.md -->",".claude/commands/git/clean.md":"<!-- 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/api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fproject-health%2FSKILL.md -->",".gemini/skills/retro/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fretro%2FSKILL.md -->",".gemini/skills/rice/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Frice%2FSKILL.md -->",".gemini/skills/saas-health/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsaas-health%2FSKILL.md -->",".gemini/skills/seo-auditor/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fseo-auditor%2FSKILL.md -->",".gemini/skills/slo-design/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fslo-design%2FSKILL.md -->",".gemini/skills/solo-founder/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsolo-founder%2FSKILL.md -->",".gemini/skills/sprint-health/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsprint-health%2FSKILL.md -->",".gemini/skills/sprint-plan/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsprint-plan%2FSKILL.md -->",".gemini/skills/startup-cto/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fstartup-cto%2FSKILL.md -->",".gemini/skills/tc/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftc%2FSKILL.md -->",".gemini/skills/tdd/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftdd%2FSKILL.md -->",".gemini/skills/tech-debt/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftech-debt%2FSKILL.md -->",".gemini/skills/user-story/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fuser-story%2FSKILL.md -->",".gemini/skills/wiki-ingest/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-ingest%2FSKILL.md -->",".gemini/skills/wiki-init/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-init%2FSKILL.md -->",".gemini/skills/wiki-lint/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-lint%2FSKILL.md -->",".gemini/skills/wiki-log/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-log%2FSKILL.md -->",".gemini/skills/wiki-query/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-query%2FSKILL.md -->",".hermes/skills/claude-skills/skills-index.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.hermes%2Fskills%2Fclaude-skills%2Fskills-index.json -->",".vibe/skills/claude-skills/skills-index.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.vibe%2Fskills%2Fclaude-skills%2Fskills-index.json -->","CLAUDE.md":"# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Project Purpose\n\nThis is a **comprehensive skills library** for Claude AI and Claude Code - reusable, production-ready skill packages that bundle domain expertise, best practices, analysis tools, and strategic frameworks. The repository provides modular skills that teams can download and use directly in their workflows.\n\n**Current Scope:** 398 production-ready skills across 20 domains with 766 Python automation tools, 877 reference guides, 123 agents (cs-* + 7 personas), and 157 slash commands, distributed as 104 marketplace plugins. Headline counters are derived from the tree by `scripts/derive_counters.py` (run with `--check` to verify the docs still match). **v2.11.2 (current)** vendors **engineering/skillopt-sleep/** — started as a verbatim, byte-for-byte copy of `microsoft/SkillOpt`'s `skillopt_sleep` engine (stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), then received 23 targeted patches after ten rounds of adversarial review (see `engineering/skillopt-sleep/README.md`'s numbered \"Deviations from upstream\" list, the authoritative source — re-apply all 23 on re-vendor). Gives a local agent a nightly \"sleep cycle\": read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget. The heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) was deliberately **not** vendored — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit. Attribution preserved in `.claude-plugin/authoring-notes.json` + `LICENSE` + `README.md` (MIT, © Microsoft Corporation / Yifan Yang), following the same verbatim-vendor pattern as `loop-library/`. **Unreleased (post-v2.11.2, PR #961 merged)** adds the **agent-launcher/** top-level domain — a plugin re-implementation of Anthropic's `launch-your-agent` reference skill (Apache-2.0; independent, not a fork) for building **Claude Managed Agents (CMA)** in the user's own account. Every session starts with a goal (`./my-agent/goal.json`, surfaced by an opt-in `AGENT_LAUNCHER_SESSION=1` SessionStart hook + `/cs-goal`); `loop_compiler.py` compiles that goal into a **bounded grade→iterate loop** (CMA `user.define_outcome` self-grading, `max_iterations` 1..20), a **recurring POSIX-cron scheduled-deployment loop**, or a **single-pass interview→stage→launch workflow**. 6 skills (orchestrator `context: fork` + interview + stage-launch + grade-iterate + run-without-you + wrap-up), 18 stdlib-only deterministic scaffolder tools (NO network/API calls — live launches emitted as BYOK curl that never prints the key), 4 agents, 8 `/cs-*` commands, opt-in hooks, 5 shared references, 4 assets; validators enforce CMA limits (≤20 skills/session, ≤8 memory stores, depth-1 multiagent, `max_iterations` ≤20, ≤1000 deployments/org). Distinct from `engineering/agent-harness` (generic bounded loop over any domain) and `engineering/write-a-skill` (authors Claude Code skills, not CMAs). **Unreleased (post-v2.11.2)** ships the **productivity coverage expansion** — public audit record `audit/productivity-2026-07/` (all 7 legacy skills scored, 24/24 scripts smoke-tested, coverage map vs the personal-productivity canon) + 3 gap-filling plugins, each with a cs-* agent, /cs-* commands, 3 stdlib scripts and 3 cited references: **weekly-review** (GTD loop; review-gate refuses COMPLETE while a mandatory GET CURRENT step is missing), **deep-work** (time-block planner refusing >4h deep demand, shallow-work budget auditor, focus-session logger), **meetings** (MEET/ASYNC/NOT-READY cost gate, outcome-required agenda builder, action-item extractor with ORPHAN/NO-DUE flags). **Unreleased (post-v2.11.1)** added **productivity/fable-goal** — converts a rambling description of a desired outcome into one polished, copy-paste `/goal` prompt for a fresh autonomous session (ported from `duncan-buildroom/freeskills`). **v2.11.1 (complete)** upgrades **product-team/** and **project-management/** into agent-harness domains: both prose routers rebuilt as `context: fork` orchestrators with deterministic goal routers (exit-code route/ask/refuse), a Jira MCP snapshot bridge (Kanban-Guide-2025 flow metrics + seeded Monte Carlo forecasts, verified end-to-end into velocity_analyzer), a delegation-governance loop gate (human owner / reviewer / machine-checkable acceptance / close refusal), a Torres continuous-discovery cadence tracker + Opportunity Solution Tree linter, cs-pm-orchestrator + cs-product-orchestrator agents, and /cs-pm|grill-pm|pm-loop + /cs-product|grill-product|product-loop commands — plus the public audit record `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria). **v2.9.0 (complete)** added the **research-ops/** top-level domain — enterprise Research Operations (orchestrator + clinical-research + research-finance + market-research + product-research), the managed counterpart to the academic research/ domain, with `context: fork` orchestration and a Matt Pocock \"Forcing-question library\" in every SKILL.md plus `/cs-grill-research-ops`. **v2.8.0 (complete)** added 2 new top-level domains — **business-operations/** (7 internal-ops skills: orchestrator + process-mapper + vendor-management + capacity-planner + internal-comms + knowledge-ops + procurement-optimizer) and **commercial/** (8 per-deal-economics skills: orchestrator + pricing-strategist + deal-desk + partnerships-architect + channel-economics + commercial-policy + rfp-responder + commercial-forecaster) — with orchestrator skills using `context: fork` for chaining, Matt Pocock docs-anchored \"Forcing-question library\" in every SKILL.md, plus `/cs-grill-bizops` and `/cs-grill-commercial`. **v2.8.2** adds a productivity-shaped `handoff` skill (sibling to engineering/handoff) inspired by Matt Pocock — first-run setup with configurable save location, redaction linter, SessionStart + SessionEnd hooks, fidelity self-check, `--refresh` flag. **v2.8.1** upgraded the engineering role-skills (senior-fullstack / senior-frontend / senior-backend) with karpathy-coder + Matt Pocock decision engines + per-role forcing questions. v2.7.3 ports `alirezarezvani/aeo-box` — AEO (Answer Engine Optimization) skill into marketing-skill/ + security-guidance PreToolUse hook into engineering/. v2.7.0 added 13 Path-B skills across 3 top-level domains (productivity, marketing, research). v2.6.0 added 4 Matt Pocock-derived productivity skills.\n\n**Key Distinction**: This is NOT a traditional application. It's a library of skill packages meant to be extracted and deployed by users into their own Claude workflows.\n\n## Maintainer-Local Folders (gitignored)\n\nThe following exist on the maintainer's disk but are excluded from the public GitHub tree so cloners only see production skill packages:\n\n- `documentation/` — sprint plans, strategy, implementation roadmaps\n- `eval-workspace/` — Tessl evaluation outputs\n- `megaprompts/` — pre-skill draft specs (Path-B source material)\n- `tests/` — pytest suite (run locally; not in CI)\n- `.autoresearch/` — autoresearch agent workspace\n- `AUDIT_REPORT.md` — internal audit snapshots\n\n**Distinct from the above:** the top-level `audit/` directory (e.g.\n`audit/newgen-2026-06/`) is an **intentional, public** audit record — rubric +\nper-domain reports with per-skill verification criteria that follow-up PRs use\nas acceptance gates. It is excluded from headline counters by\n`scripts/derive_counters.py`, but it is committed and visible to cloners.\n`AUDIT_REPORT.md` (gitignored, above) is the older internal-snapshot format.\n\nIn-repo references to paths under these folders (e.g. `documentation/implementation/...`) resolve locally for the maintainer but appear as dead links on GitHub. This is intentional.\n\n## Navigation Map\n\nThis repository uses **modular documentation**. For domain-specific guidance, see:\n\n| Domain | CLAUDE.md Location | Focus |\n|--------|-------------------|-------|\n| **Agent Development** | [agents/CLAUDE.md](agents/CLAUDE.md) | cs-* agent creation, YAML frontmatter, relative paths |\n| **Marketing Skills** | [marketing-skill/CLAUDE.md](marketing-skill/CLAUDE.md) | Content creation, SEO, ASO, demand gen, campaign analytics |\n| **Product Team** | [product-team/CLAUDE.md](product-team/CLAUDE.md) | RICE, OKRs, user stories, UX research, SaaS scaffolding |\n| **Engineering (Core)** | [engineering-team/CLAUDE.md](engineering-team/CLAUDE.md) | Fullstack, AI/ML, DevOps, security, data, QA tools |\n| **Engineering (POWERFUL)** | [engineering/](engineering/) | Agent design, RAG, MCP, CI/CD, database, observability |\n| **C-Level Advisory** | [c-level-advisor/CLAUDE.md](c-level-advisor/CLAUDE.md) | CEO/CTO strategic decision-making |\n| **Project Management** | [project-management/CLAUDE.md](project-management/CLAUDE.md) | Atlassian MCP, Jira/Confluence integration |\n| **RA/QM Compliance** | [ra-qm-team/CLAUDE.md](ra-qm-team/CLAUDE.md) | ISO 13485, MDR, FDA, GDPR, ISO 27001 compliance |\n| **Business & Growth** | [business-growth/CLAUDE.md](business-growth/CLAUDE.md) | Customer success, sales engineering, revenue operations |\n| **Finance** | [finance/CLAUDE.md](finance/CLAUDE.md) | Financial analysis, DCF valuation, budgeting, forecasting, SaaS metrics |\n| **Research Operations** | [research-ops/CLAUDE.md](research-ops/CLAUDE.md) | Clinical study design, R&D finance, market research, product research (enterprise counterpart to academic research/) |\n| **Markdown → HTML** | [markdown-html/CLAUDE.md](markdown-html/CLAUDE.md) | Markdown-to-interactive-HTML converter (orchestrator + design-system foundation; md-document/review/slides v2.10.1). Inspired by Shihipar's \"Claude Code HTML output\" essay |\n| **Agent Launcher** | [agent-launcher/CLAUDE.md](agent-launcher/CLAUDE.md) | Claude Managed Agent (CMA) launcher — session-goal orchestrator + interview / stage-launch / grade-iterate / run-without-you / wrap-up; deterministic BYOK-curl scaffolders; bounded grade→iterate + cron deployment loops. Re-implements anthropics/launch-your-agent (Apache-2.0) |\n| **Standards Library** | [standards/CLAUDE.md](standards/CLAUDE.md) | Communication, quality, git, security standards |\n| **Templates** | [templates/CLAUDE.md](templates/CLAUDE.md) | Template system usage |\n\n## Architecture Overview\n\n### Repository Structure\n\n```\nclaude-code-skills/\n├── .claude-plugin/            # Plugin registry (marketplace.json)\n├── agents/                    # 32 standalone agents (cs-* + 7 personas); 51+ cs-* agents repo-wide\n├── commands/                  # slash commands (changelog, tdd, saas-health, prd, code-to-prd, plugin-audit, sprint-plan, slo-design, etc.); 87+ repo-wide\n├── engineering-team/          # 51 core engineering skills + Playwright Pro + Self-Improving Agent + Security Suite\n├── engineering/               # 81 POWERFUL-tier advanced skills (incl. AgentHub, autoresearch-agent, self-eval, llm-wiki, tc-tracker, ship-gate, slo-architect, write-a-skill, caveman, grill-me, handoff, agent-harness)\n├── product-team/              # 17 product skills (incl. apple-hig-expert) + Python tools\n├── marketing-skill/           # 46 marketing skills (8 pods) + Python tools\n├── c-level-advisor/           # 66 C-level advisory skills (full C-suite + founder-mode agents + orchestration)\n├── project-management/        # 9 PM skills + bundled Atlassian Remote MCP (.mcp.json)\n├── ra-qm-team/                # 18 RA/QM compliance skills\n├── compliance-os/             # 9 compliance-OS skills\n├── business-growth/           # 5 business & growth skills + Python tools\n├── business-operations/       # 7 internal-ops skills (orchestrator + 6 sub-skills)\n├── commercial/                # 8 per-deal-economics skills (orchestrator + 7 sub-skills)\n├── finance/                   # 4 finance skills + Python tools\n├── research/                  # 8 academic research skills (orchestrator + 7 specialists)\n├── research-ops/              # 5 research-ops skills (orchestrator + clinical-research + research-finance + market-research + product-research)\n├── markdown-html/             # 2 markdown-to-HTML skills v2.10.0 foundation (orchestrator + design-system); md-document/review/slides land in v2.10.1\n├── agent-launcher/            # 6 CMA-launcher skills (session-goal orchestrator + 5 phase skills; 18 BYOK-curl scaffolder tools, opt-in SessionStart goal hook)\n├── eval-workspace/            # Skill evaluation results (Tessl)\n├── standards/                 # 5 standards library files\n├── templates/                 # Reusable templates\n├── docs/                      # MkDocs Material documentation site\n├── scripts/                   # Build scripts (docs generation)\n└── documentation/             # Implementation plans, sprints, delivery\n```\n\n### Skill Package Pattern\n\nEach skill follows this structure:\n```\nskill-name/\n├── SKILL.md              # Master documentation\n├── scripts/              # Python CLI tools (no ML/LLM calls)\n├── references/           # Expert knowledge bases\n└── assets/               # User templates\n```\n\n**Design Philosophy**: Skills are self-contained packages. Each includes executable tools (Python scripts), knowledge bases (markdown references), and user-facing templates. Teams can extract a skill folder and use it immediately.\n\n**Key Pattern**: Knowledge flows from `references/` → into `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\n## Git Workflow\n\n**Branch Strategy:** feature → dev → main (PR only)\n\n> **⛔ HARD RULE — PR TARGET IS ALWAYS `dev`, NEVER `main`.**\n> Every PR (human or AI-created) must use `--base dev`. Nothing merges into `main`\n> directly — `main` only receives periodic `dev → main` promotion PRs opened by the\n> maintainer. If you find a PR targeting `main`, retarget it to `dev` before review.\n> AI agents (Claude Code included): set the base branch explicitly when creating PRs;\n> never rely on the repository default branch.\n\n**Branch Protection Active:** Main branch requires PR approval. Direct pushes blocked.\n\n### Quick Start\n\n```bash\n# 1. Always start from dev\ngit checkout dev\ngit pull origin dev\n\n# 2. Create feature branch\ngit checkout -b feature/agents-{name}\n\n# 3. Work and commit (conventional commits)\nfeat(agents): implement cs-{agent-name}\nfix(tool): correct calculation logic\ndocs(workflow): update branch strategy\n\n# 4. Push and create PR to dev\ngit push origin feature/agents-{name}\ngh pr create --base dev --head feature/agents-{name}\n\n# 5. After approval, PR merges to dev\n# 6. Periodically, dev merges to main via PR\n```\n\n**Branch Protection Rules:**\n- ✅ Main: Requires PR approval, no direct push\n- ✅ Dev: Unprotected, but PRs recommended\n- ✅ All: Conventional commits enforced\n\nSee [documentation/WORKFLOW.md](documentation/WORKFLOW.md) for complete workflow guide.\nSee [standards/git/git-workflow-standards.md](standards/git/git-workflow-standards.md) for commit standards.\n\n## Development Environment\n\n**No build system or test frameworks** - intentional design choice for portability.\n\n**Python Scripts:**\n- Use standard library only (minimal dependencies)\n- CLI-first design for easy automation\n- Support both JSON and human-readable output\n- No ML/LLM calls (keeps skills portable and fast)\n\n**If adding dependencies:**\n- Keep scripts runnable with minimal setup (`pip install package` at most)\n- Document all dependencies in SKILL.md\n- Prefer standard library implementations\n\n## Current Version\n\n**Version:** v2.14.1 (audit fix release: all 104 plugins bumped so `claude plugin update` reaches existing installs, new version-bump gate G11, category-scoped Codex installer, `${CLAUDE_PLUGIN_ROOT}` script paths, productivity handoff renamed session-handoff. See CHANGELOG.md [2.14.1].)\n\n**Previously: v2.14.0** (audit skills release: agent-regression-evals, coding-agent-rollout and month-end-close plugins, open-source-first youtube-full, claude-coach plugin renamed to power-user-coach with a one-time reinstall. See CHANGELOG.md [2.14.0].)\n\n**Previously: v2.13.0** (October triage and quality-audit release: runnable command names, self-contained c-level-agents/compliance-os, hivemind as an opt-in plugin, six new skills from the community backlog. See CHANGELOG.md [2.13.0].)\n\n**Previously: v2.12.0** (consolidated release — 20 domains, 380 skills; full reported-issue triage sweep; first tag since v2.9.0. See CHANGELOG.md [2.12.0].)\n\n---\n\n**Previously: v2.11.2** (skillopt-sleep — vendored nightly self-improvement plugin from microsoft/SkillOpt)\n\n**v2.11.2 highlights — engineering/skillopt-sleep/:**\n\nVendors `engineering/skillopt-sleep/` — a byte-for-byte start from [microsoft/SkillOpt](https://github.com/microsoft/SkillOpt)'s `skillopt_sleep` engine (32 files, stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), following the same verbatim-vendor pattern as `loop-library/`. Gives a local agent a nightly gated self-improvement cycle: read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget.\n\n- **Deliberately not vendored:** the heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit.\n- **23 deviations from upstream (6 cosmetic, 17 safety/hardening)**, found across ten rounds of adversarial code review rather than assumed safe from the surface docs. The **numbered list in `engineering/skillopt-sleep/README.md`'s \"Deviations from upstream\" section is the single source of truth** — the plugin's `authoring-notes.json` `attribution.derivation_note` and this bullet are both summaries of it, kept in sync by hand; if any of the three ever disagree on the count again, README.md wins. Highlights: `redact_secrets()` now covers every artifact that goes live or persists — `proposed_SKILL.md`/`proposed_CLAUDE.md`, the cross-night task archive (`state.json`), `report.md`/`report.json` (previously only `diagnostics.json` was scrubbed, despite `report.md` being the file the SKILL.md's own workflow tells a human to read *first*), and — the gap that survived seven review rounds because every earlier fix was file-level — the CLI's own `cmd_run`/`cmd_harvest` console/`--json`/`--output` output, which read the same unredacted in-memory `Report`/`TaskRecord` objects and (via `scheduler.py`'s cron redirect) could leak straight into `cron.log`; the generated crontab line is fully `shlex.quote()`-d including the `extra` flags param, and `cron.log` itself is now `chmod 600` (previously uncovered by the state/staging chmod pass); `scheduler.py`'s per-project cron-line marker match is now anchored on end-of-line rather than a bare substring test, closing a real bug where scheduling/unscheduling one project could silently drop a sibling project's job whose path happened to be a prefix of it; the previously-dead `max_tokens_per_night` config key now sizes `dream_rollouts` down via the engine's own `plan_depth()` heuristic; a hardcoded internal Azure OpenAI backend (5 internal-looking endpoint hostnames + a Managed Identity client ID) was removed rather than carried forward; tool-shim names reachable via `--tasks-file` are now validated against a safe-identifier allowlist before use as a filename or shell text; `commands/skillopt-sleep.md` now tells the agent to confirm with the user before `schedule` (which installs a real crontab entry immediately, unlike every other action); every directory/file `state.py`/`staging.py` create is `chmod 0700`/`0600` rather than left at the world-readable process umask default.\n- One documented, opt-in exception to CLAUDE.md's \"no LLM calls in scripts\" anti-pattern (see that section) — `backend.py`'s `claude`/`codex` backends shell out to those CLIs only when a non-`mock` backend is explicitly selected.\n- Registered as its own installable marketplace plugin; **counters:** skills 358 → 359; tools 603 → 635; refs 732 (unchanged); commands 110 → 111; plugins 84 → 85 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**v2.14.0 — three audit-proposed skills (agent-regression-evals, coding-agent-rollout, month-end-close):**\n\nBuilt from the October quality audit's new-skill proposals, ranked by impact on teams. Each is a\nstandalone plugin mirrored into its domain bundle (`engineering/skills/`, `finance/skills/`), with\na cs-* agent, two `/cs-*` commands, stdlib scripts and three cited references; all three SKILL.md\nfiles pass the write-a-skill checklist. Evaluated with skill-creator (with-skill vs no-skill, one\nrealistic prompt each): 21/21 vs 17/21 assertions. The baseline's misses are why the skills exist:\nit called `bypassPermissions` in a project file \"YOLO mode for every engineer\" and `mcp__*` in\nallow \"all tools\", both of which Claude Code ignores, and it used a \"typical\" flux threshold\nwithout asking for the entity's policy.\n\n- **The evals changed the scripts, not just the scores.** Four fixes came from reading the runs:\n  the MCP inventory now scans `args` and `url` for credentials (a `postgresql://user:pass@`\n  string in `args` slipped past it); the reconciliation matcher names a carried-in\n  opening-balance difference before guessing transposition; the flux analyzer takes `--reviewer`\n  and blocks lines the reviewer owns; the flake detector warns when every failure lands in late\n  trials, the signature of state shared between trials.\n- **Rules these encode:** never compare single trials and never quarantine a critical case\n  (agent-regression-evals); policy that must hold for everyone goes in managed settings, not the\n  repo file (team-rollout); a reconciliation is a proof, a signature is not evidence of review\n  (PCAOB SAPA 11), and materiality thresholds are the entity's policy (month-end-close).\n- **Counters:** skills 392 → 398; tools 746 → 766; refs 859 → 877; agents 120 → 123;\n  commands 151 → 157; plugins 101 → 104 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/deep-learning-book (companion, not compilation):**\n\nNew `engineering/deep-learning-book/` plugin: a study companion for *Deep Learning* by\nGoodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org.\nRequested as \"convert this book into a skill\"; built as a **companion** instead, and the\nreasoning is the reusable part.\n\n- **Why not `book-to-skill`.** That skill's rights gate refuses a `shareable` package without\n  `public-domain` / `open-license` / `internal-docs` / `author-permission` — none applies to an\n  MIT Press title whose own site states the HTML-only format exists as a friction against\n  copying under the authors' contract — and its `rights_and_provenance.md` lists publishing a\n  compiled skill of a copyrighted book to a public marketplace under **Do not**. Its hard rule 1\n  also forbids scraping a book from the web, so the pipeline could not have run against a URL.\n  **The rule this sets:** when a user asks to convert a copyrighted work into a *shareable*\n  skill, build a companion that indexes and updates the source, not a compilation that\n  reproduces it; compile only when the gate clears, and keep the output local when it does not.\n  Recorded in `skills/deep-learning-book/references/rights_and_use.md`.\n- **What it is.** The compiled-skill *shape* (master SKILL.md at ~2.0k tokens with a chapter\n  index and topic index, `chapters/ch01..ch20`, glossary, patterns, cheatsheet) filled with\n  original synthesis — no passages, figures, or per-paragraph paraphrase — each chapter file\n  linking to the official free chapter. Passes `book_to_skill`'s own `book_skill_validator.py`\n  clean and every file is inside `token_budget_estimator.py`'s caps.\n- **The differentiator is the delta layer.** A static compilation freezes a source at its\n  publication date; this one dates it. Every chapter carries \"What changed after 2016\", and\n  `references/book_to_2026_delta.md` gives five corrections with primary citations and per-claim\n  confidence levels: double descent qualifying Ch 5's U-curve, AdamW splitting weight decay from\n  L2 (Ch 7 treats them as interchangeable), transformers displacing Ch 10's recurrence (keep the\n  gradient analysis, drop the architecture advice), diffusion growing out of Ch 14's denoising\n  autoencoders and Ch 18's score matching, and self-supervised learning vindicating Ch 15 while\n  replacing every method it names. Two claims are marked contested rather than propagated (batch\n  norm's \"internal covariate shift\" mechanism; the strong lottery-ticket form) and two named as\n  folklore. The stated rule: **the conflict is almost always in the recommendation, not the\n  analysis.**\n- **4 stdlib tools, each with a real refusal.** `reading_path_planner.py` (goal → prerequisite\n  closure over the book's actual dependency graph, ordered, priced in weeks; exit 3 for a goal\n  the book does not cover, naming what does; exit 4 with forcing questions when unroutable),\n  `training_diagnostics.py` (Ch 11's rules in priority order, so a NaN is never reported as\n  overfitting; exit 4 rather than diagnosing with no instruments), `capacity_planner.py`\n  (regularization ladder in cost order, with \"shrink the model\" pushed **last** in the\n  overparameterized regime per double descent; exit 4 on a val-below-train split),\n  `model_arithmetic.py` (params/FLOPs/activation memory per example for conv, linear, MHA and\n  LSTM/GRU stacks; exit 5 naming the layer whose shapes do not connect).\n- 4 references citing 7-8 sources each, 3 assets, `cs-deep-learning-tutor` agent, `/cs-deep-learning`\n  + `/cs-dl-reading-path` + `/cs-dl-diagnose`. **Counters:** skills 386 → 387; tools 723 → 727;\n  refs 838 → 842; agents 116 → 117; commands 146 → 149; plugins 97 → 98 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — marketing/linkedin (organic LinkedIn presence, platform rules in code):**\n\nNew `marketing/linkedin/` plugin answering [discussion #934](https://github.com/alirezarezvani/claude-skills/discussions/934), which asked for a strategic assistant for growing a LinkedIn presence organically rather than a post generator. Six skills (orchestrator + profile + strategy + content + engagement + analytics), 17 stdlib-only tools, 15 references, 2 agents, 8 `/cs-*` commands.\n\n- **The design constraint is the differentiator.** No LinkedIn credentials, no API calls, no scraping, nothing auto-sent — automated posting/connecting/commenting are prohibited by LinkedIn's User Agreement §8.2, and a restricted account ends a compounding asset. `linkedin_policy_gate.py` runs before any drafting and refuses seven request classes (automation, scraping, engagement pods, bulk messaging, fake identity, fabricated proof, named third-party automation platforms), each carrying the policy anchor **and a compliant substitute** — the gate never just says no. Orchestrator is `context: fork` with a deterministic five-lane router (route 0 / ask 2 / no-signal 3) and cross-lane prerequisites.\n- **Refusals are real, not warnings.** Cadence under 90 min/week returns a comment-only plan rather than a schedule that dies in week five; a newsletter whose six-month cost exceeds the budget is refused before the promise is made; an experiment needing more posts than a quarter allows is reported infeasible rather than quietly re-sized; the pattern miner refuses to test anything below 10 posts and reports `NOTHING_SURVIVED` as a finding.\n- **Evidence discipline — two popular claims corrected rather than propagated** (the `andreessen` precedent). (1) \"A personalised note triples connection acceptance (~45% vs ~15%)\" is not supported by the largest samples, which show acceptance close to identical either way (~26.4%); what a note actually moves is the **post-accept reply rate** (~5.4% → ~9.4%) — which is why `outreach_message_builder.py` refuses an ask in a first-touch note. (2) The ~19% in-body external-link reach reduction has **never been confirmed by LinkedIn as a penalty** and has a plausible dwell-time explanation, so it is a warning, not a block. Every reference carries per-claim confidence levels (🟢 LinkedIn-official / 🟡 third-party study / 🔴 folklore, named as folklore).\n- **Accessibility is a blocking lint finding, not a footnote.** Unicode pseudo-bold (the output of \"bold text generators\") fails the linter: screen readers announce those characters as mathematical symbols and LinkedIn search does not index them as words. Engagement bait is also blocking, per the Professional Community Policies. `pattern_miner.py` adds multiple-comparisons accounting and mirrored-candidate de-duplication that no comparable tool implements.\n- All six SKILL.md files are a full **6/6 PASS** on the write-a-skill checklist (binding for post-v2.6.0 skills). Every tool supports `--help`/`--sample`/`--output json` with typed exit codes. **Counters:** skills 380 → 386; tools 706 → 723; refs 823 → 838; agents 114 → 116; commands 138 → 146; plugins 96 → 97 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/spinning-up-deep-rl (the first book compiled by book-to-skill):**\n\nThe first knowledge-base plugin produced end-to-end by `engineering/book-to-skill`, from OpenAI's\n[Spinning Up in Deep RL](https://spinningup.openai.com/) (MIT, © 2018 OpenAI; primarily developed by\nJoshua Achiam). Source obtained by cloning `openai/spinningup` and compiling its `docs/` reStructuredText\ntree — 38 files, ~37k words, ~49K tokens — through the full pipeline: `extract_document.py --mode technical`\n→ analysis → 20 chapter files → glossary / patterns / cheatsheet → master `SKILL.md` → `book_skill_validator.py`\n→ `skill_plugin_emitter.py`. Validator passes clean **in `--strict` mode**; every file is inside budget\n(resident core 2,101 / 4,000 tokens; 20 chapters averaging ~1,256 tokens each, loaded on demand).\n\n- **Rights basis is `open-license`, not fair use.** The emitter's Step-11 gate refuses a shareable package\n  without one; MIT permits derivative distribution. Upstream's notice is reproduced in full in the plugin's\n  `LICENSE` alongside this package's own, and the README names the source, the author and the commit-era —\n  a sidecar JSON is not a license notice.\n- **Chapter structure follows the source's own `toctree`**, not a heading scan: user documentation (ch01-06),\n  Introduction to RL Parts 1-3 (ch07-09), resources — the researcher essay, key papers, exercises, benchmarks\n  (ch10-13), one chapter per algorithm in lineage order (ch14-19: VPG → TRPO → PPO, DDPG → TD3 → SAC), and the\n  logger/MPI/ExperimentGrid utilities (ch20).\n- **The cheatsheet carries what a glossary cannot**: the debug-turnaround threshold (under 5 minutes), the seed\n  minimums (3, ideally 10+), the benchmark network defaults that differ by algorithm family ((64,32)/tanh\n  on-policy vs (256,256)/relu off-policy), and Spinning Up's own **parity disclosure** — DDPG/TD3/SAC are\n  research-grade, VPG/TRPO/PPO are not, and the docs say to use OpenAI Baselines for those instead.\n- **One emitter defect found and fixed in the same change.** `skill_plugin_emitter.py` was writing its `source`\n  provenance block into `plugin.json`, which this repo's own `scripts/check_plugin_json.py` hard-fails\n  (issue #954 — Claude Code rejects the whole manifest on any unrecognized key). Its inline comment claimed\n  `source`/`attribution` were \"approved extension fields,\" which had been true and no longer was. The manifest\n  builder now emits spec fields only and a new `_authoring_notes()` writes `.claude-plugin/authoring-notes.json`.\n  Every future `book-to-skill` package gets a manifest that passes CI; the one emitted here was the first to\n  catch it.\n- **write-a-skill checklist: 4/6, and the two remaining are structural, not defects.** A compiled\n  knowledge base is not a hand-authored instruction skill. (2) \"SKILL.md under 100 lines\" conflicts\n  with the format's mandatory 20-row Chapter Index plus Topic Index; the binding budget here is\n  `book_skill_validator.py`'s 4,000-token cap, and the file sits at 2,101 — trimming to 100 lines\n  would delete exactly the navigation that `budget.over_cap` exists to protect. (3) \"no\n  time-sensitive info\" fires on \"January 2020\", which is a **provenance pin on a frozen source**\n  (Spinning Up's last update), not a staleness claim — removing it would make the skill less honest\n  about what it covers. (5) was a real gap and is fixed: the resident core now carries a worked\n  invocation block.\n- **No new Python tools** — a compiled knowledge base ships notes, not scripts, so the tools and references\n  counters are unchanged. **Counters:** skills 387 → 388; agents 117 → 118; commands 149 → 150; plugins\n  98 → 99, on top of `deep-learning-book` which merged into `dev` first (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/skill-doctor (grade the agent setup from real sessions):**\n\nRebuild of [warpdotdev/common-skills](https://github.com/warpdotdev/common-skills)' `skill-doctor` (MIT, © Denver Technologies, Inc., pinned at `f3b58c81`) as a full plugin. Harvests the last N days of local Claude Code / Codex sessions scoped to one repo, has the agent judge each condensed transcript against two verbatim-preserved rubrics (efficiency, code quality — labels only, closed tables), measures which installed skills actually fired, and proposes only the skill edits the evidence justifies — one local, self-contained HTML report; nothing is ever uploaded.\n\n- **22 numbered deviations from upstream** — `engineering/skill-doctor/README.md`'s list is authoritative; `authoring-notes.json` summarizes it. Headline additions: **`score_aggregator.py`, a deterministic gate with no upstream counterpart** — upstream let the scoring LLM average its own scores and assemble `report.json`; here labels map to scores via embedded tables mirroring the rubrics, scores for unsampled sessions are rejected as fabrications, reasons are length-checked, and a suggestion that cites no scored session id (or carries no diff) fails at exit 4. **Collector hardening:** always-on 12-pattern secret redaction before any transcript touches disk (no off switch; per-label counts land in the inventory and report), `chmod 0700/0600` artifacts, plugin-layout skill discovery (`*/skills/*/SKILL.md`), slash-command usage detection mined from `<command-name>` markers before the injection filter drops them. **Renderer replaced:** zero JavaScript (upstream embeds a 1,531-line prebuilt diff bundle + canvas share-image) — pure-CSS diff coloring, native `<details>` collapse, `prefers-color-scheme`, print-to-PDF; Warp branding and the `warp.dev/factories` CTA removed. **Dropped:** the Warp `warp.sqlite` source and its 392-line hand-rolled protobuf decoder (unauditable vendored binary-format code; Warp users should run upstream).\n- Preserved verbatim: both scoring rubrics (`scorers/`) and the skill-improvement filing bar (\"would a competent agent with the current instructions still fail this way?\"), now §1–§2 of `references/skill_edit_governance.md`. Zero suggestions clearing the bar is a valid, reportable success; proposed edits stay staged under the run's scratch dir until an explicit per-skill yes, and proposals for this repo's skills must pass write-a-skill's 6-item checklist.\n- 3 stdlib tools (all `--help`/`--sample`/`--output json`, typed exit codes; the pipeline smoke-tests end-to-end from `--sample` fixtures including a planted fake secret), 3 references citing 7 sources each, 3 handoff-shape assets, `cs-skill-doctor` agent, `/cs-skill-doctor` command. SKILL.md is a full 6/6 PASS on the write-a-skill checklist. Distinct from `skillopt-sleep` (automated nightly loop; this is one interactive graded pass), `write-a-skill` (authors from expertise; this improves from evidence), and self-eval (grades the current session; this grades a window). **Counters** (this branch merged `dev` after `agent-memory` landed, so these deltas sit on top of it): skills 378 → 379; tools 703 → 706; refs 820 → 823; agents 110 → 111; commands 130 → 131; plugins 95 → 96 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/book-to-skill (document → knowledge-base skill → plugin):**\n\nDerived from [virgiliojr94/book-to-skill](https://github.com/virgiliojr94/book-to-skill) (MIT). Compiles a book, documentation folder, or spec collection (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into an agent skill: a resident master `SKILL.md` (core frameworks + chapter index + topic index, capped at 4k tokens) plus on-demand `chapters/chNN-*.md`, `glossary.md`, `patterns.md`, and a decision `cheatsheet.md`. The agent reads the core, then one chapter — never the whole source again.\n\n- **Vendored close to verbatim:** the extraction library (`scripts/book_to_skill/` — config, exceptions, sanitize, dependencies, utils + 7 per-format parsers) keeps upstream's format chains, chapter detection across Latin/Roman/Chinese/Thai/Korean heading styles, invisible-Unicode (Trojan Source) sanitization and DOCX entity-expansion guard.\n- **26 numbered deviations from upstream** — the list in `engineering/book-to-skill/README.md` is authoritative; the plugin's `authoring-notes.json` `attribution.derivation_note` summarizes it. Highlights: (5) `--install-missing` now defaults to `report` — it prints the pip command and uses the stdlib fallback instead of upstream's TTY prompt that runs `pip install` into the caller's environment; (6) a **rights gate** — `skill_plugin_emitter.py --distribution shareable` refuses without `--rights` from `public-domain|open-license|internal-docs|author-permission`, with `fair-use` deliberately excluded (a defence, not a licence); (10) the two upstream validators merged into one four-family gate, adding **budget** and **index** families — dead chapter links, unindexed chapter files and dangling topic refs are the failure that silently breaks navigation while the skill still looks complete, and upstream had no check for it; (11) folded YAML scalars now parse, so a wrapped description no longer under-reports its length past the 1024-char cap; (12) `discovery_tax.py` → `token_budget_estimator.py` with the optional `tiktoken` path dropped, a post-flight budget audit added, and an explicit **worth-converting verdict** that says \"just read it\" when the source is under ~3× the compiled skill.\n- **Repo-native addition with no upstream counterpart — Step 11 / `/cs-book-to-plugin`:** upstream stops at a bare folder in `~/.claude/skills/`, which this library cannot route to. `skill_plugin_emitter.py` wraps a compiled skill as a full plugin package (manifest + `cs-<slug>` agent + `/cs-<slug>` command + README) and prints the marketplace entry; it never edits `marketplace.json` itself, and refuses to wrap a skill carrying validation errors.\n- **Cross-linked into `engineering/write-a-skill`** (\"author first, compile second\" — that skill authors from expertise in your head, this one compiles from a document on disk).\n- 4 stdlib-only tools (all `--help` / `--sample` / `--output json`), 5 references citing 7–8 sources each, 3 assets, `cs-book-to-skill` agent, 2 commands. **Counters:** skills 362 → 363; tools 644 → 663; refs 741 → 746; agents 102 → 103; commands 116 → 118; plugins 88 → 89 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/memory-engineering (engineer the forgetting, not the remembering):**\n\nNew `engineering/memory-engineering/` plugin. Fills a real gap: the repo had no\nskill for designing, pricing, or auditing an **agent memory system** (nearest\nneighbours `llm-wiki`, `skillopt-sleep`, `agent-harness` all bound something\nelse — a vault, a loop, a task plan). Framing synthesized from *\"How to be a\nMemory Engineer, from the perspective of Stanford, Microsoft, Anthropic and\nNvidia\"* by [@N01ennn](https://x.com/N01ennn/status/2083971749079581120), with\nevery quantitative claim re-cited to the primary source.\n\n- **4 stdlib scripts, one per lens.** `memory_cost_profiler.py` (construction vs\n  query split, **cost per correct answer**, amortization, co-location warning →\n  WRITE-PATH-DOMINANT / UNDER-AMORTIZED / NEEDS-SCHEDULING-FIX);\n  `memory_architecture_picker.py` (scores the paper's four paradigm families,\n  disqualifies on hard constraints, **names the cost the choice makes you pay**,\n  and exits 2 refusing to pick when the top two are within 0.06 — printing the\n  tie-breaking question instead); `memory_density_auditor.py` (classifies every\n  record **FACT / SKILL / LOG / PROSE**, near-duplicates via word-shingle\n  Jaccard, staleness + volatile-wording flags, knowledge density per 1k tokens;\n  runs on a real `--dir` **or** `--jsonl`); `forgetting_policy_linter.py` — **the\n  gate**: 8 checks with **F1** (explicit forgetting rule) and **F4**\n  (contradictions surfaced, never auto-merged) blocking at exit 4.\n- **Evidence discipline — two of the source article's paraphrases are corrected\n  in the references rather than propagated.** (1) The 47× energy figure is the\n  *spread across ten evaluated systems* (BM25 at 4,145 J/correct answer vs\n  A-Mem/MIRIX at 115–197 kJ, a \"28–47× premium\"), **not** \"two systems with\n  identical accuracy.\" (2) The 97% first-pass-error reduction is **Rakuten's\n  named vendor-published customer testimonial** (Yusuke Kaji, at 27% lower cost\n  / 34% lower latency), not a controlled study or a general property of the\n  approach. Every reference carries per-claim confidence levels, per the\n  `andreessen` precedent.\n- **Two classifier defects found and fixed during the build**, both of which\n  would have produced garbage on any real repo: markdown headings *inside*\n  fenced code blocks were splitting records (fixed by masking fences before\n  heading detection — dropped 258 phantom records to 107 on a real directory),\n  and short fragments trivially matched at 1.00 Jaccard (fixed with a\n  20-word floor for duplicate candidacy, eliminating 41 false-positive\n  \"duplicates\"). A third fix added the **PROSE** class: an earlier version\n  labeled every signal-less block LOG, firing LOG_HEAVY at 74% on a prose\n  documentation folder.\n- 4 references citing 7 sources each (arXiv:2606.06448 Stanford characterization;\n  MSR PlugMem; arXiv:2604.09852 MEMENTO + OpenMementos; Anthropic managed-agents\n  memory), 3 assets (seven-question forcing worksheet, combined example spec\n  consumed by all three spec-taking scripts, fillable F1–F8 policy template),\n  `cs-memory-engineer` agent, `/cs-memory-engineering` + `/cs-forgetting-audit`.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist (binding for\n  post-v2.6.0 skills). **Counters** (this branch merged `dev` after\n  `book-to-skill` landed, so these deltas sit on top of it): skills 363 → 364;\n  tools 663 → 667; refs 746 → 750; agents 103 → 104; commands 118 → 120;\n  plugins 89 → 90 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/agent-memory (promotion is earned, not asserted):**\n\nNew `engineering/agent-memory/` plugin. Concept derived from\n[TencentCloud/TencentDB-Agent-Memory](https://github.com/TencentCloud/TencentDB-Agent-Memory)\n(MIT) — **no upstream code included**. A four-tier ladder over Claude Code's own\nhooks: **L0** raw transcripts (never injected) → **L1** candidate atoms\n(gitignored, recalled on lexical relevance per prompt) → **L2** project context\n(committed after adopt, loaded every session start) → **L3** stable persona\n(always loaded). Tiers are distinguished by *injection policy*, not storage\nformat.\n\n- **Three upstream choices deliberately rejected**, each for a repo rule rather\n  than taste: the managed **database** (self-contained-package rule → one\n  append-oriented JSONL per project, capped at 500 atoms); a **proxy layer**\n  between agent and model (Claude Code already exposes the three interception\n  points — adding a proxy to obtain hooks the platform provides buys nothing and\n  adds a failure mode on the critical path); **LLM-based extraction** (the\n  no-LLM-in-scripts anti-pattern, and a model call cannot run in an async\n  teardown hook on a latency budget, nor reproduce its output from the\n  transcript, which would break \"cite, don't invent\").\n- **The gates are the design.** L1→L2 needs ≥3 distinct sessions spanning ≥2\n  distinct calendar days (`stated` = 2 sessions, day rule *still applies*;\n  `verified` = 1 observation and is the only day-exempt path); L2→L3 needs ≥2\n  distinct projects + 30 days. Thresholds are tuned toward refusing because the\n  error costs are asymmetric: under-promotion is self-healing (the user restates\n  it, which is itself an observation), over-promotion silently steers every\n  future session.\n- **Two gates refuse rather than guess.** `redacted: true` blocks promotion on\n  *any* volume of evidence — a **durability-independent barrier**, since a\n  secret restated over five sessions passes every recurrence gate; the flag\n  firing means the text was altered, and a lexical filter finding one secret is\n  not proof it found all of them, while L2/L3 are committed to git. An open\n  contradiction freezes both claims, found by **reverse join** (the newer atom\n  carries no flag) rather than a mirrored field.\n- **Three hooks, all fail-open.** `SessionStart` injects L2+L3 and marks\n  L2↔L3 collisions the project-scoped detector structurally cannot see;\n  `UserPromptSubmit` recalls on a **100 ms internal budget** against a monotonic\n  clock (the 1 s hook `timeout` is a wedged-process backstop, not the budget);\n  `SessionEnd` is async and captures → redacts → merges → detects → stages.\n  Measured: spawn+recall p50 ≈ 29 ms / p95 ≈ 31 ms, scoring itself 2–3 ms over\n  500 atoms — **interpreter cold start is the entire cost**, which is why the\n  in-script loop is not worth optimizing further.\n- **Nothing reaches a `CLAUDE.md` without a human.** Promotions land in\n  `.memory/staged/`; `/cs-memory adopt` walks them one at a time and backs both\n  files up first. `cs-memory-curator` refuses to adopt a redacted claim, an\n  unresolvable citation, or to resolve a contradiction itself.\n- 5 stdlib scripts + 3 hooks (`memory_core.py` is a deviation from `DESIGN.md`\n  §10's four-script tree — the **`README.md` deviations list is authoritative**,\n  and §10.1's stale `+6` tool estimate is corrected to `+8` there and in\n  `DESIGN.md`), 3 references citing 6–7 sources each with per-claim confidence\n  levels, a 69-check example validator, and `DESIGN.md` — ~1,400 lines, 44\n  review rounds, open decisions ranked by what they gate, including the one that\n  permits deleting the folder if rule-based recall proves too low.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist. **Counters:**\n  skills 377 → 378; tools 695 → 703 (+8: 5 scripts + 3 hooks); refs 817 → 820;\n  agents 109 → 110; commands 129 → 130; plugins 94 → 95 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.1) — productivity/fable-goal (ramble → autonomous /goal prompt):**\n\nImproved port of `duncan-buildroom/freeskills` `fable-goal` (informal \"free to use and modify\" grant — quoted, not relicensed; see the `attribution` block). Converts a rambling description of a desired outcome into one polished, copy-paste /goal prompt for a fresh autonomous session — the prompt is the deliverable, never the build. Adds over upstream: wrong-tool check, observable-done principle, six-slot extraction (deliverable/quantity/stakes/tools/quality/destination), per-medium verification defaults, six-point pre-delivery self-check, anti-pattern list + failure-mode catalog reference, second worked example in a non-web medium. Ships `goal_prompt_self_check.py` (stdlib runner for the mechanically checkable self-check subset — word count 150–350, goal line, autonomy directive, verification/freedom/destination language; exit 0/1, `--sample`, `--output json`), `/cs-fable-goal` command. Intentionally no `agents/`/`assets/` (single reasoning pass; see plugin README design notes). SKILL.md is a full PASS on the write-a-skill 6-item checklist. Counters: skills 357 → 358 (this PR also trues up pre-existing engineering-row drift 355 → 357); tools 602 → 603; refs 731 → 732; commands 109 → 110; plugins 83 → 84.\n\n---\n\n**Version:** v2.11.1 (pm/product agent-harness domains — deep audit + orchestrated loops for product-team & project-management)\n\n**v2.11.1 highlights — both PM/product routers become agent harnesses:**\n\nExtends the v2.11.0 agent-harness layer to the two people-process domains. Public audit record at `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria).\n\n- **project-management → delivery loop:** `pm-skills` rebuilt as a `context: fork` orchestrator with 3 stdlib tools — `pm_goal_router.py`\n\n<!-- [TRUNCATED AT 50KB] -->","agent-launcher/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2F.claude-plugin%2Fplugin.json -->","agent-launcher/CLAUDE.md":"# CLAUDE.md — agent-launcher domain\n\nGuidance for working inside `agent-launcher/`. See the root `CLAUDE.md` for\nrepo-wide rules.\n\n## What this domain is\n\nA plugin that scaffolds and launches **Claude Managed Agents (CMA)** in the user's\nown Anthropic account, organized around a **per-session goal** that compiles into a\n**loop or workflow**. Inspired by `anthropics/launch-your-agent` (Apache-2.0);\nindependent re-implementation, not a fork.\n\n## Non-negotiable rules (enforced by SPEC.md + validators)\n\n1. **Deterministic scaffolders only.** Every script under `skills/*/scripts/` is\n   stdlib-only and makes **no** network/API calls. Live launches are emitted as\n   BYOK curl. Do not add `requests`, `anthropic`, or any network client.\n2. **Never surface the API key.** Launch scripts read `$ANTHROPIC_API_KEY`; no\n   tool echoes/logs/writes a key. `payload_validator.py` and reviewers check this.\n3. **CMA limits are law.** Keep `references/cma-primitives.md` as the source of\n   truth for ceilings; validators must match it.\n4. **Bounded loops only.** `loop_compiler.py` never emits a grade→iterate loop\n   without a `max_iterations` cap (1..20).\n5. **The hook is opt-in and crash-proof.** Gated by `AGENT_LAUNCHER_SESSION=1`;\n   exits 0 on any error. Never make it fire unconditionally.\n6. **The folder is the user's.** All artifacts go under `./my-agent/`; scripts\n   accept `--out-dir` and default there. Never write into the plugin folder.\n\n## Structure\n\n- `skills/agent-launcher-orchestrator/` — `context: fork` goal router\n  (`goal_router.py`, `goal_state.py`, `loop_compiler.py`).\n- `skills/{interview,stage-launch,grade-iterate,run-without-you,wrap-up}/` — one\n  phase each, 3 tools each.\n- `agents/` — `cs-agent-launcher-orchestrator` + 3 phase specialists.\n- `commands/` — 8 `/cs-*` commands.\n- `hooks/` — opt-in `session_start.py` / `session_end.py` + `hooks.json`.\n- `references/` — 5 shared docs. `assets/` — schema + templates + example.\n\n## Tool conventions\n\n- Every tool: `argparse` with real `--help`, a `--sample` that runs a deterministic\n  demo and exits 0, and JSON output via `--json` where a machine reads it.\n- Default output dir `./my-agent/`; never assume network access.\n- Import shared logic via relative `sys.path` insert (see how the orchestrator\n  tools import `goal_state`).\n\n## Forcing-question discipline\n\nEvery SKILL.md ships a \"Forcing-question library\" (Matt Pocock grill-with-docs):\nwalk one question at a time, recommend an answer, cite the reference. The\n`/cs-grill-agent-launcher` command surfaces them.\n\n## When editing\n\n- Changing a CMA limit → update `references/cma-primitives.md` **and** every\n  validator in lockstep.\n- Adding a loop shape → update `loop_compiler.py` **and**\n  `references/loops-and-workflows.md`.\n- Keep `SPEC.md` authoritative; if you ship something different, record it in the\n  delivery report.\n","agent-launcher/skills/agent-launcher-orchestrator/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fagent-launcher-orchestrator%2FREADME.md -->","agent-launcher/skills/agent-launcher-orchestrator/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fagent-launcher-orchestrator%2FSKILL.md -->","agent-launcher/skills/grade-iterate/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fgrade-iterate%2FREADME.md -->","agent-launcher/skills/grade-iterate/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fgrade-iterate%2FSKILL.md -->","agent-launcher/skills/interview/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Finterview%2FREADME.md -->","agent-launcher/skills/interview/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Finterview%2FSKILL.md -->","agent-launcher/skills/run-without-you/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Frun-without-you%2FREADME.md -->","agent-launcher/skills/run-without-you/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Frun-without-you%2FSKILL.md -->","agent-launcher/skills/stage-launch/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fstage-launch%2FREADME.md -->","agent-launcher/skills/stage-launch/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fstage-launch%2FSKILL.md -->","agent-launcher/skills/wrap-up/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fwrap-up%2FREADME.md -->","agent-launcher/skills/wrap-up/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fwrap-up%2FSKILL.md -->","agents/CLAUDE.md":"# Agent Development Guide\n\nThis guide provides comprehensive instructions for creating **cs-* prefixed agents** that seamlessly integrate with the 346 production skills in this repository (count derived via `scripts/derive_counters.py`).\n\n## Agent Architecture\n\n### What are cs-* Agents?\n\n**cs-* agents** are specialized Claude Code agents that orchestrate the repository's 346 skills. Each agent:\n- References skills via relative paths (`../marketing-skill/`)\n- Executes Python automation tools from skill packages\n- Follows established workflows and templates\n- Maintains skill portability and independence\n\n**Key Principle**: Agents ORCHESTRATE skills, they don't replace them. Skills remain self-contained and portable.\n\n### ClawHub Publishing Constraints\n\nWhen skills are published to **ClawHub** (clawhub.com):\n- **cs- prefix for slug conflicts only** — applies only on the ClawHub registry when another publisher already owns the slug. Repo folder names and local skill names are never renamed.\n- **No paid/commercial service dependencies** — skills must not require paid third-party API keys or commercial services unless provided by the project itself.\n- **plugin.json** — ONLY fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills: \"./\"`.\n- **Rate limit:** 5 new skills/hour on ClawHub. Use drip publishing for bulk operations.\n\n### Production Agents\n\n**33 agents live in this folder** (93 agent files repo-wide, including plugin-bundled agents). A representative selection:\n\n| Agent | Domain | Description |\n|-------|--------|-------------|\n| [cs-content-creator](marketing/cs-content-creator.md) | Marketing | AI-powered content creation with brand voice consistency and SEO optimization |\n| [cs-demand-gen-specialist](marketing/cs-demand-gen-specialist.md) | Marketing | Demand generation and customer acquisition specialist |\n| [cs-ceo-advisor](c-level/cs-ceo-advisor.md) | C-Level | Strategic leadership advisor for CEOs |\n| [cs-cto-advisor](c-level/cs-cto-advisor.md) | C-Level | Technical leadership advisor for CTOs |\n| [cs-product-manager](product/cs-product-manager.md) | Product | RICE prioritization and customer discovery |\n| [cs-product-strategist](product/cs-product-strategist.md) | Product | Product strategy, OKR cascades, market positioning |\n| [cs-agile-product-owner](product/cs-agile-product-owner.md) | Product | Agile product ownership and backlog management |\n| [cs-ux-researcher](product/cs-ux-researcher.md) | Product | UX research, usability testing, design insights |\n| [cs-product-analyst](product/cs-product-analyst.md) | Product | Product analytics, KPI design, experiment design |\n| [cs-engineering-lead](engineering-team/cs-engineering-lead.md) | Engineering | Engineering team coordination and incident management |\n| [cs-workspace-admin](engineering-team/cs-workspace-admin.md) | Engineering | Google Workspace administration via gws CLI |\n| [cs-senior-engineer](engineering/cs-senior-engineer.md) | Engineering | Architecture decisions, code review, CI/CD setup |\n| [cs-fullstack-engineer](engineering/cs-fullstack-engineer.md) | Engineering | Fullstack orchestrator (v2.8.1): walks 7 Matt Pocock forcing questions, picks profile via deterministic engine, forks (`context: fork`) into api-design-reviewer / database-designer / slo-architect / ci-cd-pipeline-builder. Invokable via `/cs-fullstack-review` or `Agent({subagent_type:\"cs-fullstack-engineer\"})`. |\n| [cs-frontend-engineer](engineering/cs-frontend-engineer.md) | Engineering | Frontend orchestrator (v2.8.1): walks 7 forcing questions (device, LCP target, rendering, bundle, SEO, design system, WCAG), picks framework profile, forks into a11y-audit / performance-profiler / epic-design / apple-hig-expert. Invokable via `/cs-frontend-review`. |\n| [cs-backend-engineer](engineering/cs-backend-engineer.md) | Engineering | Backend orchestrator (v2.8.1): walks 7 forcing questions (read/write + QPS, tenancy, sync vs async, sensitivity, pattern, RPO/RTO, SLO), picks language + pattern profile, forks into api-design-reviewer / database-designer / migration-architect / slo-architect / observability-designer. Invokable via `/cs-backend-review`. |\n| [cs-growth-strategist](business-growth/cs-growth-strategist.md) | Business | Growth strategy and revenue optimization |\n| [cs-financial-analyst](finance/cs-financial-analyst.md) | Finance | Financial analysis, DCF valuation, SaaS metrics |\n| [cs-project-manager](project-management/cs-project-manager.md) | PM | Project management with Atlassian integration |\n| [cs-quality-regulatory](ra-qm-team/cs-quality-regulatory.md) | RA/QM | Regulatory affairs and quality management |\n\n**Template Available**: [templates/agent-template.md](../templates/agent-template.md) (318 lines) - Use this to create new agents\n\n### Agent vs Skill\n\n| Aspect | Agent (cs-*) | Skill |\n|--------|-------------|-------|\n| **Purpose** | Orchestrate and execute workflows | Provide tools, knowledge, templates |\n| **Location** | `agents/domain/` | `domain-skill/skill-name/` |\n| **Structure** | Single .md file with YAML frontmatter | SKILL.md + scripts/ + references/ + assets/ |\n| **Integration** | References skills via `../../` | Self-contained, no dependencies |\n| **Naming** | cs-content-creator, cs-ceo-advisor | content-creator, ceo-advisor |\n\n## Agent File Structure\n\n### Required YAML Frontmatter\n\nEvery agent file must start with valid YAML frontmatter:\n\n```yaml\n---\nname: cs-agent-name\ndescription: One-line description of what this agent does\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n```\n\n**Field Definitions:**\n- **name**: Agent identifier with `cs-` prefix (e.g., `cs-content-creator`)\n- **description**: Single sentence describing agent's purpose\n- **No `skills:` field.** Claude Code preloads every skill listed there into the subagent's context on each spawn (resolved by `plugin:skill` name, not by path). This repo's agents are lightweight routers, so name the skill folder in the agent body instead and let the agent load it on demand (decision recorded on PR #939).\n- **domain**: Domain category (marketing, product, engineering, c-level, pm, ra-qm)\n- **model**: Claude model to use (sonnet, opus, haiku)\n- **tools**: Array of Claude Code tools agent can use\n\n### Required Markdown Sections\n\nAfter YAML frontmatter, include these sections:\n\n1. **Purpose** (2-3 paragraphs)\n2. **Skill Integration** (with subsections)\n   - Skill Location\n   - Python Tools\n   - Knowledge Bases\n   - Templates\n3. **Workflows** (minimum 3 workflows)\n4. **Integration Examples** (concrete code/command examples)\n5. **Success Metrics** (how to measure effectiveness)\n6. **Related Agents** (cross-references)\n7. **References** (links to documentation)\n\n## Relative Path Resolution\n\n### Path Pattern\n\nAll skill references use the `../../` pattern:\n\n```markdown\n**Skill Location:** `../marketing-skill/skills/content-creator/`\n\n### Python Tools\n\n1. **Brand Voice Analyzer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py content.txt`\n\n2. **SEO Optimizer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/seo_optimizer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"keyword\"`\n```\n\n### Why `../../`?\n\nFrom agent location: `agents/marketing/cs-content-creator.md`\nTo skill location: `marketing-skill/content-creator/`\n\nNavigation: `agents/marketing/` → `../../` (up to root) → `marketing-skill/content-creator/`\n\n**Always test paths resolve correctly!**\n\n## Python Tool Integration\n\n### Execution Pattern\n\nAgents execute Python tools from skill packages:\n\n```bash\n# From agent context\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt\n\n# With JSON output\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt json\n\n# With arguments\npython ../product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n```\n\n### Tool Requirements\n\nAll Python tools must:\n- Use standard library only (or minimal dependencies documented in SKILL.md)\n- Support both JSON and human-readable output\n- Provide `--help` flag with usage information\n- Return appropriate exit codes (0 = success, 1 = error)\n- Handle missing arguments gracefully\n\n### Error Handling\n\nWhen Python tools fail:\n1. Check file path resolution\n2. Verify input file exists\n3. Check Python version compatibility (3.8+)\n4. Review tool's `--help` output\n5. Inspect error messages in stderr\n\n## Workflow Documentation\n\n### Workflow Structure\n\nEach workflow must include:\n\n```markdown\n### Workflow 1: [Clear Descriptive Name]\n\n**Goal:** One-sentence description\n\n**Steps:**\n1. **[Action]** - Description with specific commands/tools\n2. **[Action]** - Description with specific commands/tools\n3. **[Action]** - Description with specific commands/tools\n\n**Expected Output:** What success looks like\n\n**Time Estimate:** How long this workflow takes\n\n**Example:**\n\\`\\`\\`bash\n# Concrete example command\npython ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"primary keyword\"\n\\`\\`\\`\n```\n\n### Minimum Requirements\n\nEach agent must document **at least 3 workflows** covering:\n1. Primary use case (most common scenario)\n2. Advanced use case (complex scenario)\n3. Integration use case (combining multiple tools)\n\n## Agent Template\n\nUse this template when creating new agents:\n\n```markdown\n---\nname: cs-agent-name\ndescription: One-line description\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n\n# Agent Name\n\n## Purpose\n\n[2-3 paragraphs describing what this agent does, why it exists, and who it serves]\n\n## Skill Integration\n\n**Skill Location:** \\`../../domain-skill/skill-name/\\`\n\n### Python Tools\n\n1. **Tool Name**\n   - **Purpose:** What it does\n   - **Path:** \\`../../domain-skill/skill-name/scripts/tool.py\\`\n   - **Usage:** \\`python ../../domain-skill/skill-name/scripts/tool.py [args]\\`\n\n### Knowledge Bases\n\n1. **Reference Name**\n   - **Location:** \\`../../domain-skill/skill-name/references/file.md\\`\n   - **Content:** What's inside\n\n### Templates\n\n1. **Template Name**\n   - **Location:** \\`../../domain-skill/skill-name/assets/template.md\\`\n   - **Use Case:** When to use\n\n## Workflows\n\n### Workflow 1: [Name]\n\n**Goal:** Description\n\n**Steps:**\n1. Step 1\n2. Step 2\n3. Step 3\n\n**Expected Output:** Success criteria\n\n**Example:**\n\\`\\`\\`bash\npython ../../domain-skill/skill-name/scripts/tool.py input.txt\n\\`\\`\\`\n\n### Workflow 2: [Name]\n[Same structure]\n\n### Workflow 3: [Name]\n[Same structure]\n\n## Integration Examples\n\n[Concrete examples with actual commands and expected outputs]\n\n## Success Metrics\n\n- Metric 1: How to measure\n- Metric 2: How to measure\n- Metric 3: How to measure\n\n## Related Agents\n\n- [cs-related-agent](../<domain>/cs-related-agent.md) - How they relate\n\n## References\n\n- [Skill Documentation](../../domain-skill/skill-name/SKILL.md)\n- [Domain Roadmap](../../<domain-skill>/roadmap.md)\n```\n\n## Quality Standards\n\n### Agent Quality Checklist\n\nBefore committing an agent:\n\n- [ ] YAML frontmatter valid (no parsing errors)\n- [ ] All required fields present (name, description, skills, domain, model, tools)\n- [ ] cs-* prefix used for agent naming\n- [ ] Relative paths resolve correctly (../../ pattern)\n- [ ] Skill location documented and accessible\n- [ ] Python tools referenced with correct paths\n- [ ] At least 3 workflows documented\n- [ ] Integration examples provided and tested\n- [ ] Success metrics defined\n- [ ] Related agents cross-referenced\n\n### Testing Agent Integration\n\nTest these aspects:\n\n**1. Path Resolution**\n```bash\n# From agent directory\ncd agents/marketing/\nls ../marketing-skill/skills/content-creator/  # Should list contents\n```\n\n**2. Python Tool Execution**\n```bash\n# Create test input\necho \"Test content\" > test-input.txt\n\n# Execute tool\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py test-input.txt\n\n# Verify output\n```\n\n**3. Knowledge Base Access**\n```bash\n# Verify reference files exist\ncat ../marketing-skill/skills/content-creator/references/brand_guidelines.md\n```\n\n## Domain-Specific Guidelines\n\n### Marketing Agents (agents/marketing/)\n- Focus on content creation, SEO, demand generation\n- Reference: `../marketing-skill/`\n- Tools: brand_voice_analyzer.py, seo_optimizer.py\n\n### Product Agents (agents/product/)\n- Focus on prioritization, user research, agile workflows\n- Reference: `../product-team/`\n- Tools: rice_prioritizer.py, user_story_generator.py, okr_cascade_generator.py\n\n### C-Level Agents (agents/c-level/)\n- Focus on strategic decision-making\n- Reference: `../c-level-advisor/`\n- Tools: Strategic analysis and planning tools\n\n### Engineering Agents (agents/engineering/)\n- Focus on scaffolding, code quality, fullstack development\n- Reference: `engineering-team/`\n- Tools: project_scaffolder.py, code_quality_analyzer.py\n\n## Common Pitfalls\n\n**Avoid these mistakes:**\n\n❌ Hardcoding absolute paths\n❌ Skipping YAML frontmatter validation\n❌ Forgetting to test relative paths\n❌ Documenting workflows without examples\n❌ Creating agent dependencies (keep them independent)\n❌ Duplicating skill content in agent files\n❌ Using LLM calls instead of referencing Python tools\n\n## Next Steps\n\nAfter creating an agent:\n\n1. Test all relative paths resolve\n2. Execute all Python tools from agent context\n3. Verify all workflows with concrete examples\n4. Update agent catalog in main README.md\n5. Create GitHub issue for agent testing\n6. Commit with conventional commit message: `feat(agents): implement cs-agent-name`\n\n---\n\n**Last Updated:** June 10, 2026\n**Current:** 33 agents in this folder across 10 domain subfolders (93 agent files repo-wide)\n**Related:** See [main CLAUDE.md](../CLAUDE.md) for repository overview\n","agents/personas/README.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agents%2Fpersonas%2FREADME.md -->","business-growth/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2F.claude-plugin%2Fplugin.json -->","business-growth/CLAUDE.md":"# Business & Growth Skills - Claude Code Guidance\n\nThis guide covers the 5 production-ready business and growth skills and their Python automation tools.\n\n## Business & Growth Skills Overview\n\n**Available Skills:**\n1. **customer-success-manager/** - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)\n2. **sales-engineer/** - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)\n3. **revenue-operations/** - Pipeline analysis, forecast accuracy, GTM efficiency metrics (3 Python tools)\n\n**Total Tools:** 9 Python automation tools, 9 knowledge bases, 19+ templates\n\n## Python Automation Tools\n\n### Customer Success Manager Tools\n\n#### 1. Health Score Calculator (`customer-success-manager/scripts/health_score_calculator.py`)\n\n**Purpose:** Multi-dimensional customer health scoring with trend analysis\n\n**Features:**\n- Weighted scoring across 4 dimensions (usage, engagement, support, relationship)\n- Red/Yellow/Green classification with configurable thresholds\n- Trend analysis comparing current vs previous period\n- Segment-aware benchmarking (Enterprise/Mid-Market/SMB)\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json --format json\n```\n\n#### 2. Churn Risk Analyzer (`customer-success-manager/scripts/churn_risk_analyzer.py`)\n\n**Purpose:** Identify at-risk accounts with intervention recommendations\n\n**Features:**\n- Risk scoring based on behavioral signals\n- Warning signal detection and categorization\n- Tier-appropriate intervention playbooks\n- Urgency-based prioritization\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json --format json\n```\n\n#### 3. Expansion Opportunity Scorer (`customer-success-manager/scripts/expansion_opportunity_scorer.py`)\n\n**Purpose:** Identify upsell and cross-sell opportunities\n\n**Features:**\n- Adoption depth analysis across product modules\n- Whitespace mapping for unused features\n- Revenue opportunity estimation\n- Priority ranking by effort and impact\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json --format json\n```\n\n### Sales Engineer Tools\n\n#### 4. RFP Response Analyzer (`sales-engineer/scripts/rfp_response_analyzer.py`)\n\n**Purpose:** Score RFP/RFI coverage and identify gaps\n\n**Features:**\n- Requirement coverage scoring (Full/Partial/Planned/Gap)\n- Effort estimation per requirement\n- Gap identification with mitigation strategies\n- Overall bid/no-bid recommendation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json --format json\n```\n\n#### 5. Competitive Matrix Builder (`sales-engineer/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Generate feature comparison matrices and competitive positioning\n\n**Features:**\n- Feature-by-feature comparison matrix\n- Competitive scoring with weighted categories\n- Differentiator identification\n- Battlecard-ready output\n\n**Usage:**\n```bash\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json --format json\n```\n\n#### 6. POC Planner (`sales-engineer/scripts/poc_planner.py`)\n\n**Purpose:** Plan proof-of-concept engagements\n\n**Features:**\n- Timeline estimation based on scope\n- Resource allocation planning\n- Success criteria definition\n- Evaluation scorecard generation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/poc_planner.py poc_data.json\npython sales-engineer/scripts/poc_planner.py poc_data.json --format json\n```\n\n### Revenue Operations Tools\n\n#### 7. Pipeline Analyzer (`revenue-operations/scripts/pipeline_analyzer.py`)\n\n**Purpose:** Analyze sales pipeline health and velocity\n\n**Features:**\n- Coverage ratio calculation (pipeline/quota)\n- Stage conversion rate analysis\n- Sales velocity metrics (4-lever model)\n- Deal aging analysis\n\n**Usage:**\n```bash\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json --format json\n```\n\n#### 8. Forecast Accuracy Tracker (`revenue-operations/scripts/forecast_accuracy_tracker.py`)\n\n**Purpose:** Measure and improve forecast accuracy\n\n**Features:**\n- MAPE (Mean Absolute Percentage Error) calculation\n- Forecast bias detection (over/under-forecasting)\n- Period-over-period trend analysis\n- Category-level accuracy breakdown\n\n**Usage:**\n```bash\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json --format json\n```\n\n#### 9. GTM Efficiency Calculator (`revenue-operations/scripts/gtm_efficiency_calculator.py`)\n\n**Purpose:** Calculate go-to-market efficiency metrics\n\n**Features:**\n- Magic number calculation\n- LTV:CAC ratio analysis\n- CAC payback period\n- Burn multiple assessment\n- Industry benchmarking\n\n**Usage:**\n```bash\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json --format json\n```\n\n## Quality Standards\n\n**All business & growth Python tools must:**\n- Use standard library only (no external dependencies)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **Marketing:** Content creation, demand generation -> `../marketing-skill/`\n- **Product Team:** User research, feature prioritization -> `../product-team/`\n- **C-Level:** Strategic planning -> `../c-level-advisor/`\n- **Engineering:** Technical implementation -> `../engineering-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 5/5 business & growth skills production-ready\n**Total Tools:** 9 Python automation tools\n","business-growth/skills/business-growth-skills/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fbusiness-growth-skills%2FSKILL.md -->","business-growth/skills/contract-and-proposal-writer/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcontract-and-proposal-writer%2FSKILL.md -->","business-growth/skills/customer-success-manager/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcustomer-success-manager%2FSKILL.md 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/api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fsales-engineer%2Freferences%2Fpoc-best-practices.md -->","business-growth/skills/sales-engineer/references/rfp-response-guide.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fsales-engineer%2Freferences%2Frfp-response-guide.md -->","business-operations/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2F.claude-plugin%2Fplugin.json -->","business-operations/CLAUDE.md":"# Business Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `business-operations/`.\n\n## Purpose\n\nThe Business Operations domain ships skills that help **internal operators** (BizOps lead, COO direct reports, vendor management office, IT ops) run the company day-to-day. This is **not strategy** (that's `c-level-advisor/`) and **not external sales** (that's `business-growth/`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Job-to-be-done | `context: fork`? |\n|---|---|---|\n| `business-operations-skills` | Domain orchestrator — routes inquiries to the 6 sub-skills | YES |\n| `process-mapper` | BPMN-style process docs + bottleneck + cycle-time (Lean / TOC canon) | YES |\n| `vendor-management` | Vendor scoring + SLA + third-party risk (NIST SP 800-161 / ISO 27036) | YES |\n| `capacity-planner` | Erlang-C queueing math for ops teams (NOT engineering capacity) | NO |\n| `internal-comms` | ADKAR + Kotter 8-step change comms (NOT marketing) | NO |\n| `knowledge-ops` | SOPs + runbooks with 5W2H validation + KB hygiene (NOT personal PKM) | YES |\n| `procurement-optimizer` | UNSPSC-aligned spend categorization + supplier consolidation | NO |\n\n## Build pattern\n\nPath-B 11-file contract per skill (Matt Pocock-derived discipline preserved):\n\n```\nskill/\n├── SKILL.md                  # YAML frontmatter + workflow + forcing-question library\n├── scripts/                  # 3 stdlib-only Python CLI tools\n├── references/               # 3 ref docs, ≥ 7 cited sources each\n└── assets/                   # ≥ 1 user-customizable template\n```\n\n## Hard rules\n\n1. **Stdlib-only Python** — no `requests`, `pandas`, `numpy`. Just `argparse`, `json`, `sys`, `pathlib`, `statistics`, `dataclasses`, `enum`, `datetime`, `math`, `re`, `collections`.\n2. **Deterministic logic** — no LLM calls in scripts. Same input → same output. Erlang-C math implemented in log-space to avoid factorial overflow.\n3. **Industry tuning** — every scoring tool exposes `--profile {saas,services,manufacturing,healthcare,…}` for threshold calibration.\n4. **Matt Pocock grill discipline** — orchestrator routes via one-question-per-turn with a recommended answer + canon citation. Never bundles. Never auto-routes silently after a question. Every SKILL.md ships a \"Forcing-question library\" section with 5-7 cited canon-anchored questions.\n5. **Output is recommendation, not approval** — `vendor-management` never says \"replace this vendor\"; `procurement-optimizer` never auto-consolidates suppliers; the human always decides.\n\n## Agent + command pattern\n\n- `cs-bizops-orchestrator` — the persona agent. Voice: \"Where does the work spend most of its time waiting?\" (Theory of Constraints anchor).\n- `/cs-bizops <inquiry>` — top-level router.\n- `/cs-grill-bizops <plan>` — Matt-style docs-anchored grilling **before** routing.\n- `/cs-process-map`, `/cs-vendor-review`, `/cs-capacity-plan`, `/cs-internal-comms`, `/cs-knowledge-ops`, `/cs-procurement` — direct per-skill invocation.\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/*` (external sales motion) — BizOps is **internal**\n- ❌ Skills that overlap `c-level-advisor/coo-advisor` — that's strategic; BizOps is tactical\n- ❌ \"Process improvement consultant\" generic skills — every skill must answer a SPECIFIC question (e.g., \"where's the bottleneck?\", \"is this vendor delivering?\", \"are we sized to peak demand?\", not \"how can we improve operations?\")\n- ❌ Tools without `--profile` tuning — every score must be industry-tunable\n- ❌ Bundled questions in the orchestrator — Matt's rule: one at a time, with a recommended answer\n- ❌ Engineering-specific framing in capacity-planner — that's vpe-advisor's lane\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-me`, `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/coo-advisor`\n","business-operations/skills/business-operations-skills/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fbusiness-operations-skills%2FSKILL.md -->","business-operations/skills/capacity-planner/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2FSKILL.md -->","business-operations/skills/capacity-planner/assets/capacity_brief_template.md":"<!-- Skill available on-demand via 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layer that surfaces 8 cs-* persona agents and 17 `/cs-*` slash commands on top of the skills.\n\n## Architecture\n\n```\n/cs-onboard setup (Founder Interview) → company-context.md\n                │\n        Chief of Staff (Router)\n                │\n    ┌───────────┼───────────┐\n    10 Roles    6 Cross-Cut  6 Culture\n    │           │            │\n    └───────────┼────────────┘\n                │\n        Executive Mentor (Critic)\n                │\n        Decision Logger (Two-Layer Memory)\n```\n\n## Skills Overview\n\n### C-Suite Roles (15)\n\n| Role | Folder | Reasoning Technique | Scripts |\n|------|--------|-------------------|---------|\n| **CEO** | `ceo-advisor/` | Tree of Thought | strategy_analyzer, financial_scenario_analyzer |\n| **CTO** | `cto-advisor/` | ReAct | tech_debt_analyzer, team_scaling_calculator |\n| **COO** | `coo-advisor/` | Step by Step | ops_efficiency_analyzer, okr_tracker |\n| **CPO** | `cpo-advisor/` | First Principles | pmf_scorer, portfolio_analyzer |\n| **CMO** | `cmo-advisor/` | Recursion of Thought | marketing_budget_modeler, growth_model_simulator |\n| **CFO** | `cfo-advisor/` | Chain of Thought | burn_rate_calculator, unit_economics_analyzer, fundraising_model |\n| **CRO** | `cro-advisor/` | Chain of Thought | revenue_forecast_model, churn_analyzer |\n| **CISO** | `ciso-advisor/` | Risk-Based | risk_quantifier, compliance_tracker |\n| **CHRO** | `chro-advisor/` | Empathy + Data | hiring_plan_modeler, comp_benchmarker |\n| **General Counsel** | `general-counsel-advisor/` | Risk-Based | contract_risk_scanner, term_sheet_analyzer |\n| **Chief Data Officer** | `chief-data-officer-advisor/` | Decision-Driven | ai_training_data_audit, data_product_strategy_picker, data_asset_valuator |\n| **Chief AI Officer** | `chief-ai-officer-advisor/` | Eval-Demanding | model_buildvsbuy_calculator, ai_risk_classifier, ai_cost_economics |\n| **Chief Customer Officer** | `chief-customer-officer-advisor/` | Retention-Obsessed | retention_decomposition_analyzer, customer_segmentation_designer, cs_coverage_calculator |\n| **VP of Engineering** ⭐ NEW v2.5.5 | `vpe-advisor/` | Throughput-First | delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer |\n| **Executive Mentor** | `executive-mentor/` | Adversarial | decision_matrix_scorer, stakeholder_mapper |\n\n### Orchestration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **C-Suite Onboard** | `cs-onboard/` | Founder interview → company-context.md |\n| **Chief of Staff** | `chief-of-staff/` | Routes questions, triggers board meetings |\n| **Board Meeting** | `board-meeting/` | 6-phase multi-agent deliberation |\n| **Decision Logger** | `decision-logger/` | Two-layer memory (raw + approved) |\n| **Agent Protocol** | `agent-protocol/` | Inter-agent invocation, loop prevention, quality loop |\n| **Context Engine** | `context-engine/` | Company context loading + anonymization |\n\n### Cross-Cutting Capabilities (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Board Deck Builder** | `board-deck-builder/` | Assembles board/investor updates |\n| **Scenario War Room** | `scenario-war-room/` | Multi-variable what-if modeling |\n| **Competitive Intel** | `competitive-intel/` | Systematic competitor tracking |\n| **Org Health Diagnostic** | `org-health-diagnostic/` | Cross-functional health scoring |\n| **M&A Playbook** | `ma-playbook/` | Acquiring or being acquired |\n| **International Expansion** | `intl-expansion/` | Market entry strategy |\n\n### Culture & Collaboration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Culture Architect** | `culture-architect/` | Build and operationalize culture |\n| **Company OS** | `company-os/` | EOS/Scaling Up operating system |\n| **Founder Coach** | `founder-coach/` | Founder development and growth |\n| **Strategic Alignment** | `strategic-alignment/` | Strategy cascade, silo detection |\n| **Change Management** | `change-management/` | ADKAR-based change rollout |\n| **Internal Narrative** | `internal-narrative/` | One story across all audiences |\n\n## c-level-agents Plugin (v1.0.0 — new in v2.5.0)\n\nA separate plugin at the repo's top-level `c-level-agents/` directory (moved out of `c-level-advisor/` in #949 so the two marketplace sources no longer overlap) that wraps the 10 C-roles with persona agents and slash commands. Founder-mode entry layer.\n\n### 13 cs-* Agents (in `../c-level-agents/agents/`)\n\n| Agent | Voice | Wraps Skill |\n|---|---|---|\n| cs-cfo-advisor | Numerate skeptic | cfo-advisor |\n| cs-cmo-advisor | Narrative-first | cmo-advisor |\n| cs-cro-advisor | Pipeline-paranoid | cro-advisor |\n| cs-cpo-advisor | JTBD-driven | cpo-advisor |\n| cs-coo-advisor | Execution OS | coo-advisor |\n| cs-chro-advisor | People-systems | chro-advisor |\n| cs-ciso-advisor | Risk-paranoid | ciso-advisor |\n| cs-chief-of-staff | Router & synthesist | chief-of-staff |\n| cs-general-counsel-advisor | Risk-paranoid (legal) | general-counsel-advisor |\n| cs-cdo-advisor | Decision-driven (data) | chief-data-officer-advisor |\n| cs-caio-advisor | Eval-demanding (AI) | chief-ai-officer-advisor |\n| cs-cco-advisor | Retention-obsessed (customer) | chief-customer-officer-advisor |\n| cs-vpe-advisor ⭐ NEW v2.5.5 | Throughput-first (engineering ops) | vpe-advisor |\n\nExisting `cs-ceo-advisor` and `cs-cto-advisor` live in `/agents/c-level/` and integrate with the same protocol.\n\n### 17 /cs-* Slash Commands (in `../c-level-agents/skills/`)\n\n**Forcing-question office hours (8):** `/c-level-agents:office-hours`, `/c-level-agents:cfo-review`, `/c-level-agents:cmo-review`, `/c-level-agents:cpo-review`, `/c-level-agents:cro-review`, `/c-level-agents:cto-review`, `/c-level-agents:ciso-review`, `/c-level-agents:gc-review`\n\n**Strategic sprint pipeline (5):** `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`\n\n**Meta + safety (4):** `/c-level-agents:founder-mode` (auto-router), `/cs-onboard` (founder interview), `/c-level-agents:cross-eval` (multi-model consensus), `/c-level-agents:freeze` (cooldown lock)\n\nSee [c-level-agents/README.md](../c-level-agents/README.md) for the full plugin guide and [c-level-agents/references/persona-voices.md](../c-level-agents/references/persona-voices.md) for voice specs.\n\n## Executive Mentor Slash Commands\n\nThe only skill with a `plugin.json` (namespace: `em`) because it has slash commands. Other skills are invoked by name through the Chief of Staff router or directly by the user. This is intentional — only add `plugin.json` when a skill has dedicated slash commands that need a namespace.\n\n| Command | Purpose |\n|---------|---------|\n| `/em:challenge` | Pre-mortem analysis of any plan |\n| `/em:board-prep` | Board meeting preparation |\n| `/em:hard-call` | Framework for hard decisions |\n| `/em:stress-test` | Stress-test any assumption |\n| `/em:postmortem` | Honest retrospective |\n\n## Key Design Decisions\n\n- **Two-layer memory:** Raw transcripts (reference) + approved decisions only (feeds future meetings). Prevents hallucinated consensus.\n- **Phase 2 isolation:** During board meetings, agents think independently before cross-examination.\n- **Internal Quality Loop:** Self-verify → peer-verify → critic pre-screen → present. No unverified output reaches the founder.\n- **Proactive triggers:** Every role has context-driven early warnings that surface issues without being asked.\n- **User Communication Standard:** Bottom Line → What → Why → How to Act → Your Decision. Results only, no process narration.\n\n## Python Tools (25 total)\n\nAll scripts are stdlib-only, CLI-first, with JSON output and embedded sample data.\n\n```bash\n# Examples\npython cfo-advisor/scripts/burn_rate_calculator.py\npython cro-advisor/scripts/churn_analyzer.py\npython cpo-advisor/scripts/pmf_scorer.py\npython org-health-diagnostic/scripts/health_scorer.py\npython strategic-alignment/scripts/alignment_checker.py\npython decision-logger/scripts/decision_tracker.py\n```\n\n## Integration with Other Domains\n\n| C-Level Role | Layers Above |\n|-------------|-------------|\n| CMO | marketing-skill/ (content, demand gen, ASO execution) |\n| CFO | finance/financial-analyst (spreadsheets, DCF) |\n| CRO | business-growth/ (revenue ops, sales engineering) |\n| CISO | ra-qm-team/ (ISO 27001 checklists, ISMS audits) |\n| CPO | product-team/ (PM toolkit, user stories, sprint planning) |\n\n---\n\n**Last Updated:** 2026-05-13\n**Skills Deployed:** 33 skills (15 roles incl. 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/api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Ffounder-mode%2FSKILL.md -->","c-level-agents/skills/freeze/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Ffreeze%2FSKILL.md -->","c-level-agents/skills/gc-review/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fgc-review%2FSKILL.md -->","c-level-agents/skills/office-hours/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Foffice-hours%2FSKILL.md -->","c-level-agents/skills/onboard/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fonboard%2FSKILL.md -->","c-level-agents/skills/post-mortem/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fpost-mortem%2FSKILL.md -->","c-level-agents/skills/vpe-review/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fvpe-review%2FSKILL.md -->","commercial/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2F.claude-plugin%2Fplugin.json -->","commercial/CLAUDE.md":"# Commercial — Domain Guide\n\nThis file provides domain-specific guidance for skills in `commercial/`.\n\n## Purpose\n\nThe Commercial domain ships skills that help **deal-desk operators, pricing teams, partner managers, RFP responders, and commercial forecasters** make per-deal and packaging decisions. This is **not strategy** (`c-level-advisor/cro-advisor`), **not sales execution** (`business-growth/sales-engineer`), and **not financial close** (`finance/financial-analysis`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `commercial-skills` | Domain orchestrator — routes to 7 sub-skills | YES |\n| `pricing-strategist` | Pricing model picker + Van Westendorp WTP + packaging | NO |\n| `deal-desk` | Per-deal scorer + discount approval routing + redline | NO |\n| `partnerships-architect` | 5-tier classifier + joint GTM + revshare modeler | NO |\n| `channel-economics` | Cost-to-serve + ROI + channel mix optimizer | NO |\n| `commercial-policy` | Data-backed discount matrix + exception flow + policy linter | NO |\n| `rfp-responder` | Shipley-method structured RFP/RFI/RFQ response | YES |\n| `commercial-forecaster` | 4Q-weighted bookings + cohort NRR/GRR + funnel-confidence | NO |\n\n## Hard rules (domain-specific)\n\n1. **Pricing outputs: model + range, never a specific number.** The human picks the number.\n2. **Deal outputs: score + named human approver. Never auto-approve.** Even at 0% discount.\n3. **Forecast outputs: surface the conversion assumption explicitly.** Pipeline math without disclosed assumptions is theatre.\n4. **RFP responses: never invent claims for GAP requirements.** Surface the gap; leadership decides bid/no-bid.\n5. **Partnership tiers: insist on independent-demand evidence for STRATEGIC.** Forrester: channel-led deals from your own pipeline cost more than direct.\n6. **Channel ROI requires retention differential.** CAC alone is meaningless without channel-level retention.\n7. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n8. **Industry tuning** via `--profile {saas,api,enterprise-software,marketplace,services,hardware}` on every scoring tool.\n9. **Matt Pocock grill discipline** — `/cs-grill-commercial` interrogates plan against SaaS pricing canon before any sub-skill runs.\n\n## Build pattern\n\nPath-B 11-file contract per skill. SKILL.md includes a \"Forcing-question library\" section that grills the user with cited canon (Skok, Tunguz, Bessemer, Ramanujam, ProfitWell, Winning by Design, Shipley, APMP).\n\n## Agent + command pattern\n\n- `cs-commercial-orchestrator` — margin-protective Commercial lead. Voice: \"What's the margin at full discount, AND what does next quarter's pipeline look like at the same terms?\"\n- `/cs-commercial <inquiry>` — top-level router\n- `/cs-grill-commercial <plan>` — Matt-style grilling first\n- `/cs-pricing-strategy`, `/cs-deal-review`, `/cs-partner-tier`, `/cs-channel-econ`, `/cs-commercial-policy`, `/cs-rfp-respond`, `/cs-commercial-forecast` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/contract-and-proposal-writer` (prose authoring) — Commercial is **decision logic + structured response**\n- ❌ Skills that overlap `c-level-advisor/cro-advisor` — that's strategic CRO judgment\n- ❌ Skills that recommend a specific price — recommend model + range\n- ❌ Skills that auto-approve deals — score + route to named human\n- ❌ Forecasting tools that hide conversion assumptions\n- ❌ RFP responder that invents claims — surface GAPs, leadership decides\n- ❌ Partnership classifier that grants STRATEGIC tier without independent-demand evidence\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/cro-advisor`\n- Sales execution complement: `business-growth/sales-engineer`\n","commercial/skills/channel-economics/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2FSKILL.md -->","commercial/skills/channel-economics/assets/channel_data_template.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Fassets%2Fchannel_data_template.md -->","commercial/skills/channel-economics/references/channel_anti_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Freferences%2Fchannel_anti_patterns.md 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/api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-claude-settings-lint.md -->","docs/commands/cs-clinical-research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-clinical-research.md -->","docs/commands/cs-commercial-forecast.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-commercial-forecast.md -->","docs/commands/cs-commercial-policy.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-commercial-policy.md -->","docs/commands/cs-commercial.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-commercial.md -->","docs/commands/cs-deal-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-deal-review.md -->","docs/commands/cs-deep-learning.md":"<!-- Skill available on-demand via 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/api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-dossier.md -->","docs/commands/cs-engineer-grill.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-engineer-grill.md -->","docs/commands/cs-eval-gate.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-eval-gate.md -->","docs/commands/cs-fable-goal.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-fable-goal.md -->","docs/commands/cs-flux-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-flux-review.md -->","docs/commands/cs-forgetting-audit.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-forgetting-audit.md -->","docs/commands/cs-frontend-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-frontend-review.md -->","docs/commands/cs-fullstack-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-fullstack-review.md -->","docs/commands/cs-goal.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-goal.md -->","docs/commands/cs-grade.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grade.md -->","docs/commands/cs-grants.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grants.md -->","docs/commands/cs-grill-agent-launcher.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-agent-launcher.md -->","docs/commands/cs-grill-bizops.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-bizops.md -->","docs/commands/cs-grill-commercial.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-commercial.md -->","docs/commands/cs-grill-linkedin.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-linkedin.md -->","docs/commands/cs-grill-markdown-html.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-markdown-html.md -->","docs/commands/cs-grill-me.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-me.md -->","docs/commands/cs-grill-pm.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-pm.md -->","docs/commands/cs-grill-product.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-product.md -->","docs/commands/cs-grill-research-ops.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-research-ops.md -->","docs/commands/cs-grill-with-docs.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-with-docs.md -->","docs/commands/cs-handoff-setup.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-handoff-setup.md -->","docs/commands/cs-handoff.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-handoff.md -->","docs/commands/cs-harness.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-harness.md -->","docs/commands/cs-human-gate.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-human-gate.md -->","docs/commands/cs-inbox-setup.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-inbox-setup.md -->","docs/commands/cs-inbox-triage.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-inbox-triage.md -->","docs/commands/cs-internal-comms.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-internal-comms.md -->","docs/commands/cs-interview-mapper.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-interview-mapper.md -->","docs/commands/cs-interview.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-interview.md -->","docs/commands/cs-knowledge-ops.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-knowledge-ops.md -->","docs/commands/cs-landing.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-landing.md -->","docs/commands/cs-launch.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-launch.md -->","docs/commands/cs-linkedin-analyze.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-analyze.md -->","docs/commands/cs-linkedin-outreach.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-outreach.md -->","docs/commands/cs-linkedin-plan.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-plan.md -->","docs/commands/cs-linkedin-post.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-post.md -->","docs/commands/cs-linkedin-profile.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-profile.md -->","docs/commands/cs-linkedin-repurpose.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-repurpose.md -->","docs/commands/cs-linkedin.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin.md -->","docs/commands/cs-litreview.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-litreview.md -->","docs/commands/cs-markdown-html.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-markdown-html.md -->","docs/commands/cs-market-research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-market-research.md -->","docs/commands/cs-md-document.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-md-document.md -->","docs/commands/cs-md-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-md-review.md -->","docs/commands/cs-md-slides.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-md-slides.md -->","docs/commands/cs-meeting-actions.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-meeting-actions.md -->","docs/commands/cs-meeting-prep.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-meeting-prep.md -->","docs/commands/cs-memory-engineering.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-memory-engineering.md -->","docs/commands/cs-memory.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-memory.md -->","docs/commands/cs-month-end-close.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-month-end-close.md -->","docs/commands/cs-notebooklm.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-notebooklm.md -->","docs/commands/cs-partner-tier.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-partner-tier.md -->","docs/commands/cs-patent.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-patent.md -->","docs/commands/cs-pm-loop.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pm-loop.md -->","docs/commands/cs-pm.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pm.md -->","docs/commands/cs-pmf-check.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pmf-check.md -->","docs/commands/cs-pricing-strategy.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pricing-strategy.md -->","docs/commands/cs-process-map.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-process-map.md -->","docs/commands/cs-procurement.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-procurement.md -->","docs/commands/cs-product-loop.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-product-loop.md -->","docs/commands/cs-product-research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-product-research.md -->","docs/commands/cs-product.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-product.md -->","docs/commands/cs-pulse.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pulse.md -->","docs/commands/cs-reflect.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-reflect.md -->","docs/commands/cs-research-finance.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-research-finance.md -->","docs/commands/cs-research-ops.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-research-ops.md -->","docs/commands/cs-research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-research.md -->","docs/commands/cs-rfp-respond.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-rfp-respond.md -->","docs/commands/cs-roast.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-roast.md -->","docs/commands/cs-run-without-you.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-run-without-you.md -->","docs/commands/cs-scrape.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-scrape.md -->","docs/commands/cs-skill-doctor.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-skill-doctor.md -->","docs/commands/cs-spinning-up-deep-rl.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-spinning-up-deep-rl.md -->","docs/commands/cs-stage-launch.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-stage-launch.md -->","docs/commands/cs-syllabus.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-syllabus.md -->","docs/commands/cs-time-block.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-time-block.md -->","docs/commands/cs-vendor-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-vendor-review.md -->","docs/commands/cs-webinar.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-webinar.md -->","docs/commands/cs-weekly-review.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-weekly-review.md -->","docs/commands/cs-workflow-build.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-workflow-build.md -->","docs/commands/cs-wrap-up.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-wrap-up.md -->","docs/commands/cs-write-a-skill.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-write-a-skill.md -->","docs/commands/financial-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ffinancial-health.md -->","docs/commands/flag-cleanup.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fflag-cleanup.md -->","docs/commands/focused-fix.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ffocused-fix.md -->","docs/commands/google-workspace.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fgoogle-workspace.md -->","docs/commands/index.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Findex.md -->","docs/commands/karpathy-check.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fkarpathy-check.md -->","docs/commands/okr.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fokr.md -->","docs/commands/operator-audit.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Foperator-audit.md -->","docs/commands/persona.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fpersona.md -->","docs/commands/pipeline.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fpipeline.md -->","docs/commands/plugin-audit.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fplugin-audit.md -->","docs/commands/prd.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fprd.md -->","docs/commands/project-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fproject-health.md -->","docs/commands/retro.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fretro.md -->","docs/commands/rice.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Frice.md -->","docs/commands/saas-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsaas-health.md -->","docs/commands/seo-auditor.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fseo-auditor.md -->","docs/commands/skillopt-sleep.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fskillopt-sleep.md -->","docs/commands/slo-design.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fslo-design.md -->","docs/commands/sprint-health.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsprint-health.md -->","docs/commands/sprint-plan.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsprint-plan.md -->","docs/commands/tc.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ftc.md -->","docs/commands/tdd.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ftdd.md -->","docs/commands/tech-debt.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Ftech-debt.md -->","docs/commands/user-story.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fuser-story.md -->","docs/commands/wiki-ingest.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-ingest.md -->","docs/commands/wiki-init.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-init.md -->","docs/commands/wiki-lint.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-lint.md -->","docs/commands/wiki-log.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-log.md -->","docs/commands/wiki-query.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fwiki-query.md -->","docs/llms-full.txt":"# Claude Code Skills & Agent Plugins — Full Repository Description\n\n> A comprehensive, self-contained description of the `alirezarezvani/claude-skills` repository, written for AI agents and LLM crawlers. This file follows the [llms.txt](https://llmstxt.org) convention (`llms-full.txt` variant: the expanded, single-file version). For the concise index, see [llms.txt](https://alirezarezvani.github.io/claude-skills/llms.txt).\n\n- **Project:** Claude Code Skills & Agent Plugins\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Documentation site:** https://alirezarezvani.github.io/claude-skills/\n- **Author:** Alireza Rezvani\n- **License:** MIT (free to extract, deploy, adapt, and redistribute)\n- **Distribution:** Claude Code plugin marketplace (`.claude-plugin/marketplace.json`) and the ClawHub registry (clawhub.com)\n\n---\n\n## What this repository is\n\nThis is a **library of skill packages** for Claude AI and Claude Code — reusable, production-ready modules that bundle domain expertise, best practices, deterministic analysis tools, and strategic frameworks. It is **not a traditional application**. It is a catalog of self-contained skill folders meant to be extracted and deployed by users into their own AI-agent workflows.\n\nTeams download a skill folder and use it immediately: the skill's `SKILL.md` teaches the agent the workflow, the `scripts/` provide deterministic Python CLI tools, the `references/` supply expert knowledge bases, and the `assets/` give ready-to-customize templates.\n\n### Headline scale (derived from the tree by `scripts/derive_counters.py`)\n\n| Metric | Count |\n|--------|-------|\n| Production-ready skills | 354 |\n| Marketplace plugins | 82 |\n| Top-level domains | 18 |\n| Python automation tools | 593 |\n| Reference guides | 722 |\n| Agents (cs-* + personas) | 96 |\n| Slash commands | 102 |\n\nCounters are generated from the actual file tree; run `python3 scripts/derive_counters.py --check` to verify the docs still match the tree.\n\n---\n\n## Cross-tool compatibility\n\nSkills are authored once and made portable across many AI coding agents via sync scripts in `scripts/`. Supported targets include:\n\n- **Claude Code** (primary) — plugins, agents, slash commands, MCP servers, hooks\n- **OpenAI Codex** — `scripts/sync-codex-skills.py`, `~/.codex/`\n- **Gemini CLI** — `scripts/sync-gemini-skills.py`\n- **Cursor** — rules-format export\n- **Hermes Agent** — `scripts/sync-hermes-skills.py`\n- **Mistral Vibe** — `scripts/sync-vibe-skills.py`, `~/.vibe/skills/`\n- **Codebuff** — `scripts/sync-codebuff-skills.py`\n- **OpenClaw**, **Aider**, **Windsurf**, **Kilo Code**, **OpenCode**, **Augment**, **Antigravity** — documented in the Multi-Tool Integrations guide.\n\n---\n\n## Design principles\n\n1. **Skills are products.** Each skill is deployable as a standalone package with no dependency on other skills.\n2. **Documentation-driven.** Success depends on clear, actionable `SKILL.md` docs.\n3. **Algorithm over AI.** Analysis tools use deterministic Python (standard library only) — **no LLM/ML calls inside scripts**. This keeps skills portable, fast, and reproducible.\n4. **Template-heavy.** Skills ship ready-to-use templates users customize.\n5. **Platform-specific.** Specific, actionable frameworks beat generic advice.\n\n### Anti-patterns the repo deliberately avoids\n- Dependencies between skills (each stays self-contained)\n- Complex build systems or test frameworks (portability first)\n- Generic advice instead of specific frameworks\n- LLM calls in scripts (defeats portability and speed)\n\n---\n\n## Skill package pattern\n\nEvery skill follows this structure:\n\n```\nskill-name/\n├── SKILL.md        # Master documentation: the workflow the agent follows\n├── scripts/        # Python CLI tools (stdlib-only, no LLM calls; support --help and JSON output)\n├── references/     # Expert knowledge bases (markdown), each citing 5-8 authoritative sources\n└── assets/         # User-facing templates\n```\n\nKnowledge flows: `references/` → informs `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\nEach `SKILL.md` carries YAML frontmatter with a `name` and a `description` whose trigger phrasing (e.g. \"Use when…\") tells the agent when to invoke the skill.\n\n---\n\n## Repository structure\n\n```\nclaude-skills/\n├── .claude-plugin/        # Plugin registry (marketplace.json — 82 plugins)\n├── agents/                # cs-* agents + 7 personas\n├── commands/              # Slash commands\n├── engineering-team/      # Core engineering skills\n├── engineering/           # POWERFUL-tier advanced engineering skills\n├── product-team/          # Product skills\n├── marketing-skill/       # Marketing skills (8 pods incl. AEO)\n├── marketing/             # Landing-page generator skill\n├── c-level-advisor/       # C-level advisory skills (full C-suite + founder-mode)\n├── project-management/    # PM skills + bundled Atlassian Remote MCP\n├── ra-qm-team/            # Regulatory / quality-management compliance skills\n├── compliance-os/         # Compliance audit-prep orchestrator + sub-skills\n├── business-growth/       # Customer success, sales eng, revops\n├── business-operations/   # Internal-ops skills (orchestrator + sub-skills)\n├── commercial/            # Per-deal-economics skills (orchestrator + sub-skills)\n├── finance/               # Finance skills\n├── research/              # Academic research skills (orchestrator + specialists)\n├── research-ops/          # Enterprise research operations (orchestrator + sub-skills)\n├── productivity/          # Capture, email, reflect, handoff, andreessen\n├── markdown-html/         # Markdown-to-interactive-HTML converter suite\n├── standards/             # Communication, quality, git, security standards\n├── templates/             # Reusable templates\n├── docs/                  # This MkDocs Material documentation site\n└── scripts/               # Build, sync, and validation scripts\n```\n\n---\n\n## The 18 domains in detail\n\n### Engineering — Core (`engineering-team/`)\nFullstack, AI/ML, DevOps, security, data, and QA skills. Includes senior-role skills (architect, backend, frontend, fullstack, DevOps, data engineer/scientist, ML, computer vision, prompt, QA, security, SecOps), cloud architects (AWS/Azure/GCP), a full security suite (adversarial reviewer, AI security, cloud security, incident response, red team, threat detection, pen testing), Playwright Pro (10 sub-skills), a Self-Improving Agent suite, Snowflake development, and Stripe integration.\n\n### Engineering — POWERFUL (`engineering/`)\nAdvanced, higher-leverage engineering skills: agent design, RAG architecture, MCP server building, CI/CD pipelines, database/schema design, observability, SLO architecture, chaos engineering, Kubernetes operators, feature-flags, migration architecture, performance profiling, dependency auditing, and meta-skills for **authoring skills** (`write-a-skill`), token compression (`caveman`), plan interrogation (`grill-me`), and conversation continuity (`handoff`). Also hosts AgentHub, the autoresearch-agent (Karpathy file-optimization loop), the LLM Wiki, ship-gate, and a PreToolUse security-guidance hook.\n\n### Product (`product-team/`)\nRICE prioritization, OKRs, user stories, UX research and design, product discovery/strategy, competitive teardowns, experiment design, product analytics, SaaS scaffolding, code-to-PRD, spec-to-repo, and an Apple HIG expert.\n\n### Marketing (`marketing-skill/`)\nEight pods spanning content creation, copywriting/editing, SEO, **AEO (Answer Engine Optimization)**, ASO (app-store optimization), demand generation, paid ads, CRO (conversion-rate optimization across page/form/signup/paywall/popup/onboarding), social media, email sequences, pricing strategy, launch strategy, schema markup, and campaign analytics.\n\n### Marketing — Landing Pages (`marketing/`)\nA single-file HTML landing-page generator with multiple design styles, brand-palette validation, and GSAP animation patterns.\n\n### Project Management (`project-management/`)\nJira and Confluence experts, Atlassian admin/templates, scrum master, senior PM, meeting analyzer, and team communications. Ships a bundled Atlassian Remote MCP (`.mcp.json`, SSE transport, OAuth handled by Claude Code).\n\n### C-Level Advisory (`c-level-advisor/`)\nA full C-suite of opinionated advisor skills (CEO, CFO, CMO, CPO, CRO, COO, CTO, CHRO, CISO, CDO, CAIO, CCO, VP Engineering, General Counsel) plus a **Founder-Mode** operating system: `/c-level-agents:office-hours`, `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`, plus onboarding, cross-eval, and decision-freeze commands. Includes an Executive Mentor suite and strategic frameworks (RICE, JTBD, OKR, ADKAR, Wardley mapping). Memory is Markdown-only (no database dependency).\n\n### Regulatory & Quality (`ra-qm-team/`)\nISO 13485, EU MDR 2017/745, FDA, GDPR/DSGVO, ISO 27001, SOC 2, CAPA, risk management, and QMS/ISMS audit skills for regulated industries (notably medical devices).\n\n### Compliance OS (`compliance-os/`)\nAn orchestrator plus audit-prep sub-skills for SOC 2, ISO 13485, ISO 27001, GDPR, FDA QSR, EU AI Act readiness, and ISO 42001 (AIMS).\n\n### Business & Growth (`business-growth/`)\nCustomer success management, sales engineering, revenue operations, and contract/proposal writing.\n\n### Business Operations (`business-operations/`)\nInternal-ops skills for BizOps leads and COO direct reports: process mapping (BPMN + bottleneck + cycle-time), vendor management (scorecard + SLA + third-party risk), capacity planning (Erlang-C), internal comms (ADKAR + Kotter), knowledge ops (SOP/runbook hygiene), and procurement optimization. Orchestrator uses `context: fork` chaining. Every output is a recommendation routed to a named human — never an auto-decision.\n\n### Commercial (`commercial/`)\nPer-deal-and-packaging skills: pricing strategist (model picker + Van Westendorp PSM + packaging), deal desk (scorer + approval router + redliner), partnerships architect, channel economics, commercial policy, RFP responder (Shipley method), and commercial forecaster. Pricing outputs a model and a range (never a single number); deal outputs route to a named approver (never auto-approve).\n\n### Finance (`finance/`)\nFinancial analysis, DCF valuation, budgeting/forecasting, business investment advisory, and SaaS-metrics coaching.\n\n### Research (`research/`)\nAcademic/literature research: an orchestrator (hybrid router) plus specialists for recency+sentiment pulse, literature review, NIH grants, entity dossiers, patent/prior-art landscapes, course-reading syllabi, and NotebookLM browser automation.\n\n### Research Operations (`research-ops/`)\nThe enterprise counterpart to `research/`: clinical study design (sample size, endpoints, phase-gate — estimates confirmed by a named clinical owner), R&D program finance (budget, burn/runway, CapEx-vs-OpEx routing), market research (TAM/SAM/SOM with method + assumptions, never a single number), and product research (study design, saturation planning, insight synthesis requiring recurrence across independent participants).\n\n### Productivity (`productivity/`)\nCapture (brain-dump-to-action), email (inbox setup + triage, drafts-only), reflect (light-prompt journaling), handoff (conversation continuity with redaction linting and session hooks), and andreessen (market-first decision engine).\n\n### Markdown to HTML (`markdown-html/`)\nA converter suite operationalizing Thariq Shihipar's thesis that markdown collapses past ~100 lines and HTML restores density/clarity/shareability. Ships an orchestrator (doctype router), a design-system onboarding wizard (WCAG-AA-validated brand palette), and three converters: `md-document` (long-form → single-file HTML with TOC/search/code-copy/scrollspy), `md-review` (code-review markdown → 2-column diff + severity annotations), and `md-slides` (markdown deck → single-file HTML presentation with keyboard nav, presenter mode, and print-to-PDF). Output is single-file HTML (Google Fonts + Prism.js CDN the only permitted externals).\n\n---\n\n## Agents and slash commands\n\n- **Agents (`agents/`):** 96 total, mostly `cs-*` prefixed personas (e.g. `cs-ceo-advisor`, `cs-senior-engineer`, `cs-aeo`, domain orchestrators) plus 7 general personas. Agents orchestrate skills and carry a distinct operating voice.\n- **Slash commands (`commands/`):** 102 total, including `/prd`, `/rice`, `/okr`, `/tdd`, `/changelog`, `/slo-design`, `/chaos-experiment`, `/plugin-audit`, `/seo-auditor`, and the `/cs-*` family (office-hours, boardroom, bizops, commercial, research-ops, markdown-html routers, and per-skill commands).\n\n---\n\n## Plugin distribution\n\nPlugins are registered in `.claude-plugin/marketplace.json` (82 plugins) across these categories: development (34), leadership (9), research (9), productivity (6), marketing (5), compliance (4), product (4), finance (2), and one each of project-management, business-growth, design, knowledge, operations, commercial, research-ops, documentation, and engineering.\n\n### plugin.json rules (for anyone extending the library)\n- Required fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills`.\n- Two approved extension fields: `source` (provenance for megaprompt-derived skills) and `attribution` (credit for MIT-licensed external derivations).\n- Skill paths are relative to the plugin root and start with `./`. Canonical forms: single-skill = `[\"./\"]`; `skills/` subdir = `\"./skills\"`; multi-skill domain = explicit `[\"./sub1\", \"./sub2\", ...]`.\n- Validation: `scripts/check_plugin_json.py --all` runs in CI on every PR.\n\n---\n\n## Git and contribution workflow\n\n- **Branch strategy:** feature → dev → main. **All PRs target `dev`, never `main`.** `main` receives only periodic `dev → main` promotion PRs from the maintainer.\n- **Conventional commits** are enforced (e.g. `feat(agents): …`, `fix(tool): …`, `docs(workflow): …`).\n- **Branch protection:** `main` requires PR approval; direct pushes are blocked.\n\n### ClawHub publishing constraints\n- The `cs-` prefix is used only on the ClawHub registry when a slug conflicts with another publisher — repo folder names and local skill names are never renamed.\n- No paid/commercial service dependencies; free-tier APIs and bring-your-own-key patterns are acceptable.\n- Rate limit: 5 new skills per hour.\n- Package versions match the repo release version.\n\n---\n\n## How an agent should use this repository\n\n1. **Find a matching skill** by browsing the [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/) or a domain index, matching the task to a skill's `description` trigger.\n2. **Read the skill's `SKILL.md`** to learn the workflow.\n3. **Run the skill's Python tools** (`scripts/*.py`, stdlib-only, all support `--help` and most support JSON output) for deterministic analysis.\n4. **Consult `references/`** for the expert knowledge underpinning the workflow.\n5. **Apply the `assets/` templates** to produce the deliverable.\n\nTo install as a plugin, add the marketplace and install the relevant plugin via Claude Code; see [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/) and [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/) for non-Claude tools.\n\n---\n\n*Generated to make the repository accessible to AI agents. Counters reflect `scripts/derive_counters.py` at the time of writing; the repository evolves — the GitHub repository and documentation site are the authoritative sources.*\n","docs/llms.txt":"# Claude Code Skills & Agent Plugins\n\n> An open-source (MIT) library of 354 production-ready agent skills, 82 installable plugins, 96 agents, and 102 slash commands across 18 domains — engineering, product, marketing, compliance, finance, research, and more. Each skill is a self-contained package bundling domain expertise, deterministic Python tools (stdlib-only, no LLM calls), reference knowledge bases, and ready-to-use templates. Skills are portable across Claude Code, OpenAI Codex, Gemini CLI, Cursor, Hermes Agent, Mistral Vibe, OpenClaw, and 6+ more AI coding tools.\n\nThis file follows the [llms.txt](https://llmstxt.org) convention. For a full, self-contained description of the entire repository, see [llms-full.txt](https://alirezarezvani.github.io/claude-skills/llms-full.txt).\n\nKey facts for agents:\n- **License:** MIT. Free to extract, deploy, and adapt.\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Distribution:** Claude Code plugin marketplace + ClawHub registry.\n- **Design philosophy:** Algorithm over AI (deterministic code, not LLM calls in tools), documentation-driven, template-heavy, self-contained skills.\n- **Skill package shape:** `SKILL.md` (master doc) + `scripts/` (Python CLI tools) + `references/` (knowledge bases) + `assets/` (templates).\n\n## Getting started\n\n- [Home](https://alirezarezvani.github.io/claude-skills/): Overview and value proposition.\n- [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/): Install and use skills/plugins.\n- [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/): Using skills with Codex, Gemini CLI, Cursor, Hermes, Vibe, OpenClaw, and more.\n- [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/): Index of all 354 skills by domain.\n- [Plugins](https://alirezarezvani.github.io/claude-skills/plugins/): The 82 installable marketplace plugins.\n- [Agents](https://alirezarezvani.github.io/claude-skills/agents/): The 96 cs-* agents and personas.\n- [Commands](https://alirezarezvani.github.io/claude-skills/commands/): The 102 slash commands.\n\n## Domains\n\n- [Engineering — Core](https://alirezarezvani.github.io/claude-skills/skills/engineering-team/): Fullstack, AI/ML, DevOps, security, data, QA.\n- [Engineering — POWERFUL](https://alirezarezvani.github.io/claude-skills/skills/engineering/): Agent design, RAG, MCP, CI/CD, observability, SLOs, skill authoring.\n- [Product](https://alirezarezvani.github.io/claude-skills/skills/product-team/): RICE, OKRs, user stories, UX research, SaaS scaffolding.\n- [Marketing](https://alirezarezvani.github.io/claude-skills/skills/marketing-skill/): Content, SEO, AEO, ASO, demand gen, campaign analytics.\n- [Project Management](https://alirezarezvani.github.io/claude-skills/skills/project-management/): Jira/Confluence, Atlassian MCP, scrum.\n- [C-Level Advisory](https://alirezarezvani.github.io/claude-skills/skills/c-level-advisor/): Full C-suite advisors + founder-mode orchestration.\n- [Regulatory & Quality](https://alirezarezvani.github.io/claude-skills/skills/ra-qm-team/): ISO 13485, MDR, FDA, GDPR, ISO 27001.\n- [Compliance OS](https://alirezarezvani.github.io/claude-skills/skills/compliance-os/): Audit-prep orchestrator for SOC 2, ISO, GDPR, EU AI Act.\n- [Business & Growth](https://alirezarezvani.github.io/claude-skills/skills/business-growth/): Customer success, sales engineering, revenue operations.\n- [Business Operations](https://alirezarezvani.github.io/claude-skills/skills/business-operations/): Process mapping, vendor management, capacity planning.\n- [Commercial](https://alirezarezvani.github.io/claude-skills/skills/commercial/): Pricing, deal desk, partnerships, RFP response.\n- [Finance](https://alirezarezvani.github.io/claude-skills/skills/finance/): Financial analysis, DCF valuation, SaaS metrics.\n- [Research](https://alirezarezvani.github.io/claude-skills/skills/research/): Literature review, grants, patents, entity dossiers.\n- [Research Operations](https://alirezarezvani.github.io/claude-skills/skills/research-ops/): Clinical study design, R&D finance, market/product research.\n- [Productivity](https://alirezarezvani.github.io/claude-skills/skills/productivity/): Capture, email triage, reflection, handoff.\n- [Markdown to HTML](https://alirezarezvani.github.io/claude-skills/skills/markdown-html/): Markdown-to-interactive-HTML converter suite.\n\n## Optional\n\n- [Guides](https://alirezarezvani.github.io/claude-skills/guides/best-claude-code-plugins/): Best plugins, per-tool skill guides (Codex, Gemini CLI, Cursor, OpenClaw).\n- [Orchestration](https://alirezarezvani.github.io/claude-skills/orchestration/): How skills chain together.\n- [Custom GPTs](https://alirezarezvani.github.io/claude-skills/custom-gpts/): Using the library with custom GPTs.\n- [Personas](https://alirezarezvani.github.io/claude-skills/personas/): Startup CTO, Growth Marketer, Solo Founder bundles.\n","docs/plugins/index.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fplugins%2Findex.md -->","docs/skills/agent-launcher/agent-launcher-orchestrator.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fagent-launcher-orchestrator.md -->","docs/skills/agent-launcher/grade-iterate.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fgrade-iterate.md -->","docs/skills/agent-launcher/index.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Findex.md -->","docs/skills/agent-launcher/interview.md":"<!-- Skill available 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fpulse.md -->","docs/skills/research/research.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fresearch.md -->","docs/skills/research/syllabus.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fsyllabus.md -->","engineering-team/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2F.claude-plugin%2Fplugin.json -->","engineering-team/CLAUDE.md":"# Engineering Team Skills - Claude Code Guidance\n\nThis guide covers the 32 production-ready engineering skills and their Python automation tools.\n\n## Engineering Skills Overview\n\n**Core Engineering (16 skills):**\n- senior-architect, senior-frontend, senior-backend, senior-fullstack\n- senior-qa, senior-devops, senior-secops\n- code-reviewer, senior-security\n- aws-solution-architect, ms365-tenant-manager, google-workspace-cli, tdd-guide, tech-stack-evaluator, epic-design\n- **a11y-audit** — WCAG 2.2 accessibility audit and fix (a11y_scanner.py, contrast_checker.py)\n- **azure-cloud-architect** — Azure infrastructure design, ARM/Bicep templates, landing zones\n- **gcp-cloud-architect** — GCP infrastructure design, Terraform modules, cloud-native patterns\n- **security-pen-testing** — Penetration testing methodology, vulnerability assessment, exploit analysis\n- **snowflake-development** — Snowflake data warehouse development, SQL optimization, data pipeline patterns\n\n**Security (5 skills):**\n- **adversarial-reviewer** — Adversarial code review with 3 hostile personas (Saboteur, New Hire, Security Auditor)\n- **threat-detection** — Hypothesis-driven threat hunting, IOC sweep generation, z-score anomaly detection\n- **incident-response** — SEV1-SEV4 triage, 14-type incident taxonomy, NIST SP 800-61 forensics\n- **cloud-security** — IAM privilege escalation paths, S3 public access checks, security group detection\n- **red-team** — MITRE ATT&CK kill-chain planning, effort scoring, choke point identification\n- **ai-security** — ATLAS-mapped prompt injection detection, model inversion & data poisoning risk scoring\n\n**AI/ML/Data (5 skills):**\n- senior-data-scientist, senior-data-engineer, senior-ml-engineer\n- senior-prompt-engineer, senior-computer-vision\n\n**Total Tools:** 39+ Python automation tools\n\n## Core Engineering Tools\n\n### 1. Project Scaffolder (`senior-fullstack/scripts/project_scaffolder.py`)\n\n**Purpose:** Production-ready project scaffolding for modern stacks\n\n**Supported Stacks:**\n- Next.js + GraphQL + PostgreSQL\n- React + REST + MongoDB\n- Vue + GraphQL + MySQL\n- Express + TypeScript + PostgreSQL\n\n**Features:**\n- Docker Compose configuration\n- CI/CD pipeline (GitHub Actions)\n- Testing infrastructure (Jest, Cypress)\n- TypeScript + ESLint + Prettier\n- Database migrations\n\n**Usage:**\n```bash\n# Create new project\npython senior-fullstack/scripts/project_scaffolder.py my-project --type nextjs-graphql\n\n# Start services\ncd my-project && docker-compose up -d\n```\n\n### 2. Code Quality Analyzer (`senior-fullstack/scripts/code_quality_analyzer.py`)\n\n**Purpose:** Comprehensive code quality analysis and metrics\n\n**Features:**\n- Security vulnerability scanning\n- Performance issue detection\n- Test coverage assessment\n- Documentation quality\n- Dependency analysis\n- Actionable recommendations\n\n**Usage:**\n```bash\n# Analyze project\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project\n\n# JSON output\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project --json\n```\n\n**Output:**\n```\nCode Quality Report:\n- Overall Score: 85/100\n- Security: 90/100 (2 medium issues)\n- Performance: 80/100 (3 optimization opportunities)\n- Test Coverage: 75% (target: 80%)\n- Documentation: 88/100\n\nRecommendations:\n1. Update lodash to 4.17.21 (CVE-2020-8203)\n2. Optimize database queries in UserService\n3. Add integration tests for payment flow\n```\n\n### 3. Fullstack Scaffolder (`senior-fullstack/scripts/fullstack_scaffolder.py`)\n\n**Purpose:** Rapid fullstack application generation\n\n**Usage:**\n```bash\npython senior-fullstack/scripts/fullstack_scaffolder.py my-app --stack nextjs-graphql\n```\n\n## AI/ML/Data Tools\n\n### Data Science Tools\n\n**Experiment Designer** (`senior-data-scientist/scripts/experiment_designer.py`)\n- A/B test design\n- Statistical power analysis\n- Sample size calculation\n\n**Feature Engineering Pipeline** (`senior-data-scientist/scripts/feature_engineering_pipeline.py`)\n- Automated feature generation\n- Correlation analysis\n- Feature selection\n\n**Statistical Analyzer** (`senior-data-scientist/scripts/statistical_analyzer.py`)\n- Hypothesis testing\n- Causal inference\n- Regression analysis\n\n### Data Engineering Tools\n\n**Pipeline Orchestrator** (`senior-data-engineer/scripts/pipeline_orchestrator.py`)\n- Airflow DAG generation\n- Spark job templates\n- Data quality checks\n\n**Data Quality Validator** (`senior-data-engineer/scripts/data_quality_validator.py`)\n- Schema validation\n- Null check enforcement\n- Anomaly detection\n\n**ETL Generator** (`senior-data-engineer/scripts/etl_generator.py`)\n- Extract-Transform-Load workflows\n- CDC (Change Data Capture) patterns\n- Incremental loading\n\n### ML Engineering Tools\n\n**Model Deployment Pipeline** (`senior-ml-engineer/scripts/model_deployment_pipeline.py`)\n- Containerized model serving\n- REST API generation\n- Load balancing config\n\n**MLOps Setup Tool** (`senior-ml-engineer/scripts/mlops_setup_tool.py`)\n- MLflow configuration\n- Model versioning\n- Drift monitoring\n\n**LLM Integration Builder** (`senior-ml-engineer/scripts/llm_integration_builder.py`)\n- OpenAI API integration\n- Prompt templates\n- Response parsing\n\n### Prompt Engineering Tools\n\n**Prompt Optimizer** (`senior-prompt-engineer/scripts/prompt_optimizer.py`)\n- Prompt A/B testing\n- Token optimization\n- Few-shot example generation\n\n**RAG System Builder** (`senior-prompt-engineer/scripts/rag_system_builder.py`)\n- Vector database setup\n- Embedding generation\n- Retrieval strategies\n\n**Agent Orchestrator** (`senior-prompt-engineer/scripts/agent_orchestrator.py`)\n- Multi-agent workflows\n- Tool calling patterns\n- State management\n\n### Computer Vision Tools\n\n**Vision Model Trainer** (`senior-computer-vision/scripts/vision_model_trainer.py`)\n- Object detection (YOLO, Faster R-CNN)\n- Semantic segmentation\n- Transfer learning\n\n**Inference Optimizer** (`senior-computer-vision/scripts/inference_optimizer.py`)\n- Model quantization\n- TensorRT optimization\n- ONNX export\n\n**Video Processor** (`senior-computer-vision/scripts/video_processor.py`)\n- Frame extraction\n- Object tracking\n- Scene detection\n\n## Tech Stack Patterns\n\n### Frontend (React/Next.js)\n- TypeScript strict mode\n- Component-driven architecture\n- Atomic design patterns\n- State management (Zustand/Jotai)\n- Testing (Jest + React Testing Library)\n\n### Backend (Node.js/Express)\n- Clean architecture\n- Dependency injection\n- Repository pattern\n- Domain-driven design\n- Testing (Jest + Supertest)\n\n### Fullstack Integration\n- GraphQL for API layer\n- REST for external services\n- WebSocket for real-time\n- Redis for caching\n- PostgreSQL for persistence\n\n## Development Workflows\n\n### Workflow 1: New Project Setup\n\n```bash\n# 1. Scaffold project\npython senior-fullstack/scripts/project_scaffolder.py my-app --type nextjs-graphql\n\n# 2. Start services\ncd my-app && docker-compose up -d\n\n# 3. Run migrations\nnpm run migrate\n\n# 4. Start development\nnpm run dev\n```\n\n### Workflow 2: Code Quality Check\n\n```bash\n# 1. Analyze codebase\npython senior-fullstack/scripts/code_quality_analyzer.py ./\n\n# 2. Fix security issues\nnpm audit fix\n\n# 3. Run tests\nnpm test\n\n# 4. Build production\nnpm run build\n```\n\n### Workflow 3: ML Model Deployment\n\n```bash\n# 1. Setup MLOps infrastructure\npython senior-ml-engineer/scripts/mlops_setup_tool.py\n\n# 2. Deploy model\npython senior-ml-engineer/scripts/model_deployment_pipeline.py model.pkl\n\n# 3. Monitor performance\n# Check MLflow dashboard\n```\n\n## Quality Standards\n\n**All engineering tools must:**\n- Support modern tech stacks (Next.js, React, Vue, Express)\n- Generate production-ready code\n- Include testing infrastructure\n- Provide Docker configurations\n- Support CI/CD integration\n\n## Integration Patterns\n\n### GitHub Actions CI/CD\n\nAll scaffolders generate GitHub Actions workflows:\n```yaml\n.github/workflows/\n├── test.yml          # Run tests on PR\n├── build.yml         # Build and lint\n└── deploy.yml        # Deploy to production\n```\n\n### Docker Compose\n\nMulti-service development environment:\n```yaml\nservices:\n  - app (Next.js)\n  - api (GraphQL)\n  - db (PostgreSQL)\n  - redis (Cache)\n```\n\n## Additional Resources\n\n- **Quick Start:** `START_HERE.md`\n- **Team Structure:** `TEAM_STRUCTURE_GUIDE.md`\n- **Engineering Roadmap:** `engineering_skills_roadmap.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 32 engineering skills production-ready\n**Total Tools:** 39+ Python automation tools across core + AI/ML/Data + epic-design + a11y\n\n---\n\n## epic-design\n\nBuild cinematic 2.5D interactive websites with scroll storytelling, parallax depth, and premium animations. Includes asset inspection pipeline, 45+ techniques across 8 categories, and accessibility built-in.\n\n**Key features:**\n- 6-layer depth system with automatic parallax\n- 13 text animation techniques, 9 scroll patterns\n- Asset inspection with background judgment rules\n- Python tool for automated image analysis\n- WCAG 2.1 AA compliant (reduced-motion)\n\n**Use for:** Product launches, portfolio sites, SaaS marketing pages, event sites, Apple-style animations\n\n**Live demo:** [epic-design-showcase.vercel.app](https://epic-design-showcase.vercel.app/)\n","engineering-team/a11y-audit/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fa11y-audit%2F.claude-plugin%2Fplugin.json -->","engineering-team/a11y-audit/skills/a11y-audit/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fa11y-audit%2Fskills%2Fa11y-audit%2FSKILL.md 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guidance\n4. **passive-deal-screener/** - Screens private deals from the passive LP perspective: equity syndications, preferred equity, hard money / bridge funds, and private credit, pasted from any source. Stress-tests returns against public benchmarks plus an illiquidity premium, converts the fee stack to gross-to-net drag, and surfaces red flags, missing disclosures, and GP questions with bad-answer signals (2 Python tools: `fee_drag_calculator.py`, `benchmark_comparator.py`)\n5. **month-end-close/** - Runs the accounting close: close calendar on its critical path with owner and reviewer checks, reconciliation proof with aging and transposition hints, and a flux gate that refuses boilerplate explanations (3 Python tools: `close_calendar_planner.py`, `reconciliation_matcher.py`, `flux_analyzer.py`; standalone plugin with `/cs-month-end-close` and `/cs-flux-review`)\n\n**Total Tools:** 12 Python automation tools; 5 knowledge bases and 6 templates across skills 1-3, plus 5 reference files in passive-deal-screener\n\n**Commands:** 2 (`/financial-health`, `/saas-health`)\n\n## Python Automation Tools\n\n### 1. Ratio Calculator (`financial-analyst/scripts/ratio_calculator.py`)\n\n**Purpose:** Calculate and interpret financial ratios from statement data\n\n**Features:**\n- Profitability ratios (ROE, ROA, Gross/Operating/Net Margin)\n- Liquidity ratios (Current, Quick, Cash)\n- Leverage ratios (Debt-to-Equity, Interest Coverage, DSCR)\n- Efficiency ratios (Asset/Inventory/Receivables Turnover, DSO)\n- Valuation ratios (P/E, P/B, P/S, EV/EBITDA, PEG)\n- Built-in interpretation and benchmarking\n\n**Usage:**\n```bash\npython financial-analyst/scripts/ratio_calculator.py financial_data.json\npython financial-analyst/scripts/ratio_calculator.py financial_data.json --format json\n```\n\n### 2. DCF Valuation (`financial-analyst/scripts/dcf_valuation.py`)\n\n**Purpose:** Discounted Cash Flow enterprise and equity valuation\n\n**Features:**\n- Revenue and cash flow projections\n- WACC calculation (CAPM-based)\n- Terminal value (perpetuity growth and exit multiple methods)\n- Enterprise and equity value derivation\n- Two-way sensitivity analysis\n- No external dependencies (uses math/statistics)\n\n**Usage:**\n```bash\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json --format json\n```\n\n### 3. Budget Variance Analyzer (`financial-analyst/scripts/budget_variance_analyzer.py`)\n\n**Purpose:** Analyze actual vs budget vs prior year performance\n\n**Features:**\n- Variance calculation (actual vs budget, actual vs prior year)\n- Materiality threshold filtering\n- Favorable/unfavorable classification\n- Department and category breakdown\n\n**Usage:**\n```bash\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json --format json\n```\n\n### 4. Forecast Builder (`financial-analyst/scripts/forecast_builder.py`)\n\n**Purpose:** Driver-based revenue forecasting and cash flow projection\n\n**Features:**\n- Driver-based revenue forecast model\n- 13-week cash flow projection\n- Scenario modeling (base/bull/bear)\n- Trend analysis from historical data\n\n**Usage:**\n```bash\npython financial-analyst/scripts/forecast_builder.py forecast_data.json\npython financial-analyst/scripts/forecast_builder.py forecast_data.json --format json\n```\n\n## Quality Standards\n\n**All finance Python tools must:**\n- Use standard library only (math, statistics, json, argparse)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **C-Level:** Strategic financial decision-making -> `../c-level-advisor/`\n- **Business & Growth:** Revenue operations, sales metrics -> `../business-growth/`\n- **Product Team:** Budget allocation, RICE scoring -> `../product-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 4 finance skills documented here (domain totals: `scripts/derive_counters.py`)\n**Total Tools:** 12 Python automation tools\n**Commands:** /financial-health, /saas-health\n","finance/business-investment-advisor/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fbusiness-investment-advisor%2F.claude-plugin%2Fplugin.json -->","finance/business-investment-advisor/skills/business-investment-advisor/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fbusiness-investment-advisor%2Fskills%2Fbusiness-investment-advisor%2FSKILL.md -->","finance/month-end-close/.claude-plugin/plugin.json":"<!-- Skill available on-demand via 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/api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fmortgage-reit-specialty-finance.md -->","finance/skills/stock-analysis/references/sectors/nbfc.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fnbfc.md -->","finance/skills/stock-analysis/references/sectors/oil-gas.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Foil-gas.md -->","finance/skills/stock-analysis/references/sectors/people-businesses.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fpeople-businesses.md -->","finance/skills/stock-analysis/references/sectors/pharma-healthcare.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fpharma-healthcare.md -->","finance/skills/stock-analysis/references/sectors/rail-freight.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Frail-freight.md -->","finance/skills/stock-analysis/references/sectors/realestate-reit.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Frealestate-reit.md -->","finance/skills/stock-analysis/references/sectors/retail-ecommerce.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fretail-ecommerce.md -->","finance/skills/stock-analysis/references/sectors/semiconductors.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fsemiconductors.md -->","finance/skills/stock-analysis/references/sectors/shipping-logistics.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fshipping-logistics.md -->","finance/skills/stock-analysis/references/sectors/telecom-media.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Ftelecom-media.md -->","finance/skills/stock-analysis/references/sectors/utilities-power.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Futilities-power.md -->","finance/skills/stock-analysis/references/sectors/waste-environmental.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fwaste-environmental.md -->","finance/skills/stock-analysis/scripts/benchmarks.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Fscripts%2Fbenchmarks.json -->","loop-library/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=loop-library%2F.claude-plugin%2Fplugin.json -->","loop-library/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=loop-library%2FSKILL.md -->","markdown-html/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2F.claude-plugin%2Fplugin.json -->","markdown-html/CLAUDE.md":"# Markdown → HTML — Domain Guide\n\nThis file provides domain-specific guidance for skills in `markdown-html/`.\n\n## Purpose\n\nThe markdown-html domain converts long markdown files (the actual artifacts produced inside a Claude project — specs, reports, RFCs, PR writeups, slide outlines) into world-class, single-file, lightly-interactive HTML. Inspired by Thariq Shihipar's argument (Medium, 2026): markdown collapses past ~100 lines because it lacks visual machinery for density and lateral navigation; HTML restores both.\n\nIt is **not** an interactive prompt-tuning playground (`/playground` plugin owns that lane), **not** a landing-page generator (`marketing/landing/`), **not** a session-handoff brief generator (`engineering/handoff/` + `productivity/handoff/`), and **not** a static-site generator (single-file artifacts, not site indices).\n\n## Skills (v2.10.3 — domain complete)\n\n| Skill | Purpose | `context: fork`? | Status |\n|---|---|---|---|\n| `markdown-html-orchestrator` | Domain orchestrator — classifies doctype, gates on threshold + onboarding, routes to converter | YES | ✓ live |\n| `design-system` | One-time onboarding wizard + WCAG-AA-validated brand palette (12 CSS custom properties) + shared config | NO | ✓ live |\n| `md-document` | Long-form converter: sticky TOC, collapsibles, search, code-copy, scrollspy | NO | ✓ live |\n| `md-review` | Code-review converter: 2-col diff + severity-tagged margin annotations + jump-nav | NO | ✓ live |\n| `md-slides` | Slide-deck converter: arrow-key nav + presenter mode + print-to-PDF | NO | ✓ live |\n\nAll three converters are shipped. Routing always targets the converter skill's scripts — never hand-render HTML inline.\n\n## Hard rules (domain-specific)\n\n1. **Refuses input < 100 lines.** Markdown still wins below the threshold (Shihipar). Every converter (and the orchestrator) prints the line count and a \"keep as markdown\" recommendation.\n2. **Refuses without design-system onboarding.** The orchestrator's `route_explainer.py` checks `config_loader.setup_completed()`. If false, refuse and surface onboarding (`python3 markdown-html/skills/design-system/scripts/onboard.py`).\n3. **WCAG AA enforced.** `brand_palette_validator.py` rejects color combinations whose body-text contrast falls below 4.5:1 on bg. Link contrast is iteratively walked to 4.5:1 by adjusting luminance.\n4. **Single-file HTML output.** All CSS and JS inline. The only permitted external CDN entries are Google Fonts CSS and Prism.js. No bundler, no build step, no JS framework runtimes (vanilla JS + IntersectionObserver only).\n5. **Never silently chain converters.** \"Convert this markdown AND make slides from it AND a code review\" is three operations. Pick one, finish, ask before chaining.\n6. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n7. **Customization in use, not decoration.** Every converter MUST render differently when the user changes `design_style`, `brand.primary`, `code_theme`, or `toc.behavior`. If a token doesn't change behavior, it doesn't belong in the schema.\n8. **Onboarding-first.** The orchestrator surfaces onboarding the moment it detects a missing `setup_completed_at`. Don't render with placeholder defaults silently.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scripts + 3 references (each citing 5-7 sources) + (optional) 1 asset template. The orchestrator skill ships `context: fork` in its frontmatter. The `design-system` skill is the shared brand owner — every converter imports its `config_loader.py` via `sys.path.insert(0, .../design-system/scripts)`.\n\nEach SKILL.md ships a \"Forcing-question library\" section (cited-canon grilling, one question at a time) — same discipline as `research-ops`, `commercial`, and `business-operations`.\n\n## Agent + command pattern\n\n- `cs-markdown-html-orchestrator` — density-first markdown-to-HTML converter. Voice: \"What decision does this HTML drive — is the reader skimming, deciding, or presenting?\"\n- `/cs-markdown-html <path>.md` — top-level router (classifier + route + recommend)\n- `/cs-grill-markdown-html <path>.md` — Matt-Pocock-style 5-question grill before conversion\n- `/cs-design-system` — surface the onboarding wizard\n\nPer-sub-skill commands (all live):\n- `/cs-md-document`, `/cs-md-review`, `/cs-md-slides`\n\n## Anti-patterns (domain-level)\n\n- ❌ Converting markdown < 100 lines — markdown still wins. Refuse + cite Shihipar.\n- ❌ Skipping onboarding because \"the user wants it done now.\" Surface onboarding — it's 60 seconds.\n- ❌ Multi-file output (separate CSS / JS / image folders). Single file or nothing.\n- ❌ External JS framework runtimes (React, Vue, Svelte, Alpine). Vanilla JS + IntersectionObserver only.\n- ❌ Silently overwriting existing output files. `output_path_resolver.py` suffixes `-2`, `-3`, … by default.\n- ❌ Setting `MARKDOWN_HTML_NO_CONFIG=1` silently for an interactive user.\n- ❌ Decorative tokens — every token must change at least one converter's output.\n- ❌ Inventing brand colors when the user hasn't onboarded.\n- ❌ A skill that overlaps Anthropic's official Playground plugin (sliders/knobs/prompt-copy-back).\n- ❌ A skill that overlaps `marketing/landing/` (landing-page generation from scratch).\n\n## Customization pipeline\n\n1. User runs `python3 markdown-html/skills/design-system/scripts/onboard.py`.\n2. Wizard validates brand colors via `brand_palette_validator.py`, derives 12-token palette.\n3. Result written to `~/.config/markdown-html/design-system.json` (or `./.markdown-html/design-system.json` with `--scope project`).\n4. Every converter sub-skill imports `config_loader.py` and calls `load_config()` to read project > global > defaults.\n5. Each converter's renderer emits a single `<style>` block with `:root { --md-bg: ...; }` for all 12 tokens, then references those variables throughout the CSS.\n6. Result: change a single field via `--set brand.primary=#FF6B35` → next conversion re-renders with the new brand.\n\n## References\n\n- Spec: Thariq Shihipar — *Claude Code HTML output: Why Markdown Lost and How to Switch* (Medium, 2026)\n- Forking pattern source: `research-ops/skills/research-ops-skills/SKILL.md` (`context: fork`, two-signal routing)\n- Onboarding pattern source: `research-ops/skills/clinical-research/scripts/onboard.py` + `config_loader.py`\n- Brand palette math source: `marketing/landing/skills/landing/scripts/brand_palette_validator.py`\n- Matt Pocock grill-with-docs: `engineering/grill-with-docs`\n- Single-file HTML discipline source: `marketing/landing/skills/landing/SKILL.md`\n","markdown-html/commands/cs-design-system.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fcommands%2Fcs-design-system.md -->","markdown-html/skills/design-system/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2FSKILL.md -->","markdown-html/skills/design-system/assets/design_system_schema.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Fassets%2Fdesign_system_schema.json -->","markdown-html/skills/design-system/references/design_token_canon.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Freferences%2Fdesign_token_canon.md -->","markdown-html/skills/design-system/references/typography_pairing.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Freferences%2Ftypography_pairing.md -->","markdown-html/skills/design-system/references/wcag_accessibility.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Freferences%2Fwcag_accessibility.md -->","markdown-html/skills/markdown-html-orchestrator/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2FSKILL.md -->","markdown-html/skills/markdown-html-orchestrator/references/information_density_canon.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Finformation_density_canon.md -->","markdown-html/skills/markdown-html-orchestrator/references/orchestrator_routing_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Forchestrator_routing_patterns.md -->","markdown-html/skills/markdown-html-orchestrator/references/single_file_html_discipline.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Fsingle_file_html_discipline.md -->","markdown-html/skills/md-document/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2FSKILL.md -->","markdown-html/skills/md-document/references/information_density_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Finformation_density_patterns.md -->","markdown-html/skills/md-document/references/single_file_html_discipline.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Fsingle_file_html_discipline.md -->","markdown-html/skills/md-document/references/toc_and_nav_ux.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Ftoc_and_nav_ux.md -->","markdown-html/skills/md-review/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2FSKILL.md -->","markdown-html/skills/md-review/references/diff_rendering_canon.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2Freferences%2Fdiff_rendering_canon.md -->","markdown-html/skills/md-review/references/pr_annotation_ux.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2Freferences%2Fpr_annotation_ux.md -->","markdown-html/skills/md-review/references/severity_coding.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2Freferences%2Fseverity_coding.md -->","markdown-html/skills/md-slides/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2FSKILL.md -->","markdown-html/skills/md-slides/references/keyboard_nav_patterns.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fkeyboard_nav_patterns.md -->","markdown-html/skills/md-slides/references/presentation_ux.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fpresentation_ux.md -->","markdown-html/skills/md-slides/references/single_file_deck_conventions.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fsingle_file_deck_conventions.md -->","marketing-skill/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2F.claude-plugin%2Fplugin.json -->","marketing-skill/CLAUDE.md":"# Marketing Skills — Agent Instructions\n\n## For All Agents (Claude Code, Codex CLI, OpenClaw)\n\nThis directory contains 44 marketing skills organized into 8 specialist pods (Content, SEO + AEO, CRO, Channels, Growth, Intelligence, Sales enablement, Marketing ops).\n\n### How to Use\n\n1. **Start with routing:** Read `marketing-ops/SKILL.md` — it has a routing matrix that maps user requests to the right skill.\n2. **Check context:** If `.claude/product-marketing-context.md` exists, read it first. It has brand voice, personas, and competitive landscape.\n3. **Load ONE skill:** Read only the specialist SKILL.md you need. Never bulk-load.\n\n### Skill Map\n\n- `marketing-context/` — Run first to capture brand context\n- `marketing-ops/` — Router (read this to know where to go)\n- `content-production/` — Write content (blog posts, articles, guides)\n- `content-strategy/` — Plan what content to create\n- `aeo/` — Answer Engine Optimization (E-E-A-T scoring, schema injection, citation tracking across LLMs)\n- `seo-audit/` — Traditional SEO audit\n- `page-cro/` — Conversion rate optimization\n- `pricing-strategy/` — Pricing and packaging\n- `content-humanizer/` — Fix AI-sounding content\n- `x-twitter-growth/` — X/Twitter audience growth, tweet composing, competitor analysis\n\n### Python Tools\n\n59 scripts, all stdlib-only. Run directly:\n```bash\npython3 <skill>/scripts/<tool>.py [args]\n```\nNo pip install needed. Scripts include embedded samples for demo mode (run with no args).\n\n### Anti-Patterns\n\n❌ Don't read all 44 SKILL.md files\n❌ Don't skip `.claude/product-marketing-context.md` if it exists\n❌ Don't use content-creator (deprecated → use content-production)\n❌ Don't install pip packages for Python tools\n","marketing-skill/skills/ab-test-setup/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2FSKILL.md -->","marketing-skill/skills/ab-test-setup/references/sample-size-guide.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2Freferences%2Fsample-size-guide.md -->","marketing-skill/skills/ab-test-setup/references/test-templates.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2Freferences%2Ftest-templates.md -->","marketing-skill/skills/ad-creative/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fad-creative%2FSKILL.md -->","marketing-skill/skills/ad-creative/references/creative-frameworks.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fad-creative%2Freferences%2Fcreative-frameworks.md -->","marketing-skill/skills/ad-creative/references/platform-specs.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fad-creative%2Freferences%2Fplatform-specs.md -->","marketing-skill/skills/aeo/.claude-plugin/authoring-notes.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2F.claude-plugin%2Fauthoring-notes.json -->","marketing-skill/skills/aeo/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2F.claude-plugin%2Fplugin.json -->","marketing-skill/skills/aeo/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2FSKILL.md -->","marketing-skill/skills/aeo/references/aeo_eeat_canon.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Faeo_eeat_canon.md -->","marketing-skill/skills/aeo/references/aeo_vs_seo.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Faeo_vs_seo.md -->","marketing-skill/skills/aeo/references/bot_access_and_monitoring.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Fbot_access_and_monitoring.md -->","marketing-skill/skills/aeo/references/extractable_content_patterns.md":"<!-- 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Freferences%2Fobjective_to_pillars.md -->","product-team/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2F.claude-plugin%2Fplugin.json -->","product-team/CLAUDE.md":"# Product Team Skills - Claude Code Guidance\n\nThis guide covers the 17 production-ready product management skills (13 bundled incl. the orchestrator + 4 standalone plugins) and their Python automation tools.\n\n## Orchestrator & Discovery Loop (product-skills)\n\n`skills/product-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a product goal deterministically across all 16 lanes (exit 0 route / 2 ask / 3 no signal)\npython3 skills/product-skills/scripts/product_goal_router.py --text \"help me prioritize features\"\n\n# Score the continuous-discovery cadence (Torres weekly habit; refuses on < 2 interviews)\npython3 skills/product-skills/scripts/discovery_cadence_tracker.py --input discovery_log.json\n\n# Lint the Opportunity Solution Tree (exit 2 blocks the tree from driving a roadmap)\npython3 skills/product-skills/scripts/ost_linter.py --input ost.json\n```\n\nCommands: `/cs-product` (router) · `/cs-grill-product` (canon-cited grilling) ·\n`/cs-product-loop` (the discovery loop). Agent: `cs-product-orchestrator`. Build-scale\ngoals compile through `engineering/agent-harness` with the `product-team.json` manifest.\nHard rules: no roadmap cites a tree that fails the linter; single-participant claims are\nanecdotes; AI features ship with eval specs (see\n`skills/product-skills/references/ai_product_evals.md`).\n\n## Product Skills Overview\n\n**Available Skills:**\n0. **product-skills/** - Domain orchestrator (`context: fork`) + continuous-discovery loop (3 tools: goal router, cadence tracker, OST linter)\n1. **product-manager-toolkit/** - RICE prioritization, customer interview analysis (2 tools)\n2. **agile-product-owner/** - User story generation, sprint planning (1 tool)\n3. **product-strategist/** - OKR cascade, strategic planning (1 tool)\n4. **ux-researcher-designer/** - Persona generation, user research (1 tool)\n5. **ui-design-system/** - Design token generation, component systems (1 tool)\n6. **competitive-teardown/** - Competitive matrix building, gap analysis (1 tool)\n7. **landing-page-generator/** - Landing page scaffolding (1 tool)\n8. **saas-scaffolder/** - SaaS project bootstrapping (1 tool)\n9. **product-analytics/** - KPI design, retention/cohort/funnel analysis (1 tool)\n10. **experiment-designer/** - Experiment design and sample size planning (1 tool)\n11. **product-discovery/** - Discovery frameworks and assumption mapping (1 tool)\n12. **roadmap-communicator/** - Roadmap communication and changelog generation (1 tool)\n13. **code-to-prd/** - Reverse-engineer any codebase into PRD (2 tools: codebase_analyzer, prd_scaffolder)\n14. **research-summarizer/** - Research synthesis and summarization (1 tool)\n15. **apple-hig-expert/** - Apple Human Interface Guidelines compliance and design (1 tool: hig_checker)\n16. **spec-to-repo/** - Convert a spec document into a scaffolded repository\n\n**Total Tools:** 22 Python automation tools\n\n**Agents:** 6 (cs-product-orchestrator, cs-product-manager, cs-agile-product-owner, cs-product-strategist, cs-ux-researcher, cs-product-analyst)\n\n**Slash Commands:** 11 (/cs-product, /cs-grill-product, /cs-product-loop, /rice, /okr, /persona, /user-story, /competitive-matrix, /prd, /sprint-plan, /code-to-prd)\n\n## Python Automation Tools\n\n### 1. RICE Prioritizer (`product-manager-toolkit/scripts/rice_prioritizer.py`)\n\n**Purpose:** RICE framework implementation for feature prioritization\n\n**Formula:** (Reach × Impact × Confidence) / Effort\n\n**Features:**\n- Portfolio analysis (quick wins vs big bets)\n- Quarterly roadmap generation\n- Capacity planning (story points or dev days)\n- CSV input/output for Jira/Linear integration\n- JSON export for dashboards\n\n**Usage:**\n```bash\n# Basic prioritization\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv\n\n# With capacity planning\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n\n# JSON output\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json\n```\n\n**CSV Format:**\n```csv\nfeature,reach,impact,confidence,effort\nUser Dashboard,500,3,0.8,5\nAPI Rate Limiting,1000,2,0.9,3\nDark Mode,300,1,1.0,2\n```\n\n### 2. Customer Interview Analyzer (`product-manager-toolkit/scripts/customer_interview_analyzer.py`)\n\n**Purpose:** NLP-based interview transcript analysis\n\n**Features:**\n- Pain point extraction with severity scoring\n- Feature request identification\n- Sentiment analysis\n- Theme extraction\n- Jobs-to-be-done pattern recognition\n\n**Usage:**\n```bash\n# Analyze transcript\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt\n\n# JSON output\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt json\n```\n\n### 3. User Story Generator (`agile-product-owner/scripts/user_story_generator.py`)\n\n**Purpose:** INVEST-compliant user story generation\n\n**Features:**\n- Sprint planning with capacity allocation\n- Epic breakdown into deliverable stories\n- Acceptance criteria generation\n- Story point estimation\n- Priority scoring\n\n**Usage:**\n```bash\n# Interactive mode\npython agile-product-owner/scripts/user_story_generator.py\n\n# Sprint planning (30 story points)\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### 4. OKR Cascade Generator (`product-strategist/scripts/okr_cascade_generator.py`)\n\n**Purpose:** Automated OKR hierarchy (company → product → team)\n\n**Features:**\n- Alignment scoring (vertical and horizontal)\n- Strategy templates (growth, retention, revenue, innovation)\n- Key result tracking\n- Progress visualization\n\n**Usage:**\n```bash\n# Growth strategy OKRs\npython product-strategist/scripts/okr_cascade_generator.py growth\n\n# Retention strategy\npython product-strategist/scripts/okr_cascade_generator.py retention\n```\n\n### 5. Persona Generator (`ux-researcher-designer/scripts/persona_generator.py`)\n\n**Purpose:** Data-driven persona creation from user research\n\n**Usage:**\n```bash\npython ux-researcher-designer/scripts/persona_generator.py\npython ux-researcher-designer/scripts/persona_generator.py --output json\n```\n\n### 6. Design Token Generator (`ui-design-system/scripts/design_token_generator.py`)\n\n**Purpose:** Complete design token system from brand color\n\n**Usage:**\n```bash\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern scss\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern json\n```\n\n### 7. Competitive Matrix Builder (`competitive-teardown/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Weighted competitive scoring with gap analysis\n\n**Usage:**\n```bash\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### 8. Landing Page Scaffolder (`landing-page-generator/scripts/landing_page_scaffolder.py`)\n\n**Purpose:** Generate production-ready landing pages as Next.js/React TSX components with Tailwind CSS (default) or plain HTML.\n\n**Features:**\n- TSX output (default): Next.js 14+ App Router components with Tailwind classes\n- 4 design styles: `dark-saas`, `clean-minimal`, `bold-startup`, `enterprise`\n- 7 section generators: nav, hero, features, testimonials, pricing, CTA, footer\n- Copy frameworks: PAS, AIDA, BAB\n\n**Usage:**\n```bash\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format html\n```\n\n### 9. Project Bootstrapper (`saas-scaffolder/scripts/project_bootstrapper.py`)\n\n**Purpose:** SaaS project scaffolding with auth, billing, and API setup\n\n**Usage:**\n```bash\npython saas-scaffolder/scripts/project_bootstrapper.py project_config.json\n```\n\n### 10. Metrics Calculator (`product-analytics/scripts/metrics_calculator.py`)\n\n**Purpose:** Product analytics — retention, cohort, and funnel analysis\n\n**Features:**\n- Retention curve analysis from event data\n- Funnel conversion tracking with stage-by-stage drop-off\n- Cohort grouping and comparison\n\n**Usage:**\n```bash\n# Retention analysis\npython product-analytics/scripts/metrics_calculator.py retention events.csv\n\n# Funnel analysis\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\n\n# KPI summary\npython product-analytics/scripts/metrics_calculator.py kpi metrics.csv --json\n```\n\n### 11. Sample Size Calculator (`experiment-designer/scripts/sample_size_calculator.py`)\n\n**Purpose:** Statistical sample size planning for A/B tests and experiments\n\n**Features:**\n- Minimum detectable effect (MDE) calculation\n- Absolute and relative effect size modes\n- Power analysis with configurable alpha/beta\n\n**Usage:**\n```bash\n# Absolute MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n\n# Relative MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.15 --mde-type relative\n\n# Custom power/significance\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --alpha 0.01 --power 0.9\n```\n\n### 12. Assumption Mapper (`product-discovery/scripts/assumption_mapper.py`)\n\n**Purpose:** Map and prioritize product assumptions for discovery validation\n\n**Features:**\n- Risk × uncertainty scoring for prioritization\n- CSV input with structured assumption fields\n- Categorization by assumption type (desirability, viability, feasibility, usability)\n\n**Usage:**\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\npython product-discovery/scripts/assumption_mapper.py assumptions.csv --json\n```\n\n### 13. Changelog Generator (`roadmap-communicator/scripts/changelog_generator.py`)\n\n**Purpose:** Generate structured changelogs from git commit history\n\n**Note:** Requires `git` on PATH — must be run inside a git repository.\n\n**Usage:**\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to v2.0.0 --json\n```\n\n## Product Workflows\n\n### Workflow 1: Feature Prioritization to Sprint Execution\n\n```bash\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### Workflow 2: Strategy to Team-Level OKRs\n\n```bash\npython product-strategist/scripts/okr_cascade_generator.py growth --json > okrs.json\n```\n\n### Workflow 3: Research to Persona Artifacts\n\n```bash\npython ux-researcher-designer/scripts/persona_generator.py json > personas.json\n```\n\n### Workflow 4: Brand-Aligned Landing Page\n\n```bash\npython ../marketing-skill/content-production/scripts/brand_voice_analyzer.py website_copy.txt --format json > voice.json\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### Workflow 5: Product Analytics and Experimentation\n\n```bash\npython product-analytics/scripts/metrics_calculator.py retention events.csv\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n```\n\n### Workflow 6: Discovery and Opportunity Validation\n\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\n```\n\n### Workflow 7: Roadmap and Release Communication\n\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\n```\n\n## Quality Standards\n\n**All product Python tools must:**\n- CLI-first design for automation\n- Support both interactive and batch modes\n- JSON output for tool integration\n- Standard library only (minimal dependencies)\n- Actionable recommendations\n\n## Additional Resources\n\n- **Main Documentation:** `../CLAUDE.md`\n- **Marketing Brand Voice:** `../marketing-skill/content-production/scripts/brand_voice_analyzer.py`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 17/17 product skills production-ready (product-skills is now a fork-orchestrator + discovery loop)\n**Total Tools:** 22 Python automation tools\n**Agents:** 6 | **Commands:** 11\n","product-team/agile-product-owner/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2F.claude-plugin%2Fplugin.json 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management skills, 15 Python automation tools, and bundled Atlassian Remote MCP integration (`.mcp.json` ships with the plugin — OAuth handled by Claude Code, no env vars required).\n\n## PM Skills Overview\n\n**Available Skills:**\n1. **pm-skills/** - Domain orchestrator (`context: fork`) + agentic delivery loop (3 scripts: goal router, Jira snapshot bridge, delivery loop gate)\n2. **senior-pm/** - Portfolio health, risk analysis, resource planning (3 scripts)\n3. **scrum-master/** - Sprint health, velocity forecasting, retrospectives (3 scripts)\n4. **jira-expert/** - JQL building, workflow validation (2 scripts)\n5. **confluence-expert/** - Space structure, content auditing (2 scripts)\n6. **atlassian-admin/** - Permission auditing (1 script)\n7. **atlassian-templates/** - Template scaffolding (1 script)\n8. **meeting-analyzer/** - Meeting transcript behavioral analysis (prompt-driven; scripts are follow-up work)\n9. **team-communications/** - 3P updates, newsletters, FAQs (reference-driven)\n\n**Total Tools:** 15 Python automation tools\n**Agents:** 2 — cs-pm-orchestrator (routing + delivery loop) and cs-project-manager (legacy per-skill orchestration)\n**Slash Commands:** 6 (/cs-pm, /cs-grill-pm, /cs-pm-loop, /sprint-health, /project-health, /retro)\n**Key Feature:** Atlassian MCP Server integration for direct Jira/Confluence operations\n\n## Orchestrator & Delivery Loop (pm-skills)\n\n`skills/pm-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a PM goal deterministically (exit 0 route / 2 ask / 3 no signal)\npython3 skills/pm-skills/scripts/pm_goal_router.py --text \"our sprints feel off\"\n\n# Bridge a saved searchJiraIssuesUsingJql result into analyzable inputs\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to flow --forecast 20\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to sprint > sprint_data.json\npython3 skills/scrum-master/scripts/velocity_analyzer.py sprint_data.json\n\n# Gate agent-executed delivery loops (G1 human owner … G6 exhausted budget = escalation)\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode plan   # exit 2 = blocked\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode close  # exit 4 = refused\n```\n\nMulti-task goals compile through the repo-wide harness\n(`engineering/agent-harness` with the `project-management.json` manifest). Hard rules:\nagents contribute, humans own; forecasts are Monte Carlo ranges, never dates; exhausted\nbudgets escalate — never reported as success. The five reusable PM loops (sprint-flow,\nhealth, retro-action, RAID-hygiene, comms) are documented in\n`skills/pm-skills/references/pm_loop_playbook.md`.\n\n## Atlassian MCP Integration\n\n**Purpose:** Direct integration with Jira and Confluence via Model Context Protocol (MCP)\n\n**Canonical tool list:** [references/atlassian-mcp-tools.md](references/atlassian-mcp-tools.md) — the single source of truth for real tool names. Never invent tool names; if a capability isn't in that list (project creation, sprint management, field configuration, automation rules, space creation, …), it is NOT available via MCP — use the Atlassian web UI or REST API.\n\n**Capabilities (real tools, camelCase):**\n- Jira issues: `createJiraIssue`, `getJiraIssue`, `editJiraIssue`, `searchJiraIssuesUsingJql`, `transitionJiraIssue`, `addCommentToJiraIssue`, `createIssueLink`\n- Confluence pages: `createConfluencePage`, `getConfluencePage`, `updateConfluencePage`, `searchConfluenceUsingCql`, `getConfluencePageDescendants`\n- Discovery: `getAccessibleAtlassianResources` (get `cloudId` first), `getVisibleJiraProjects`, `getConfluenceSpaces`\n\n**Setup:** Bundled `.mcp.json` registers the `atlassian` SSE server; tools surface as `mcp__atlassian__<toolName>`.\n\n**Usage Pattern:**\n```\n# Jira: create an issue (call getAccessibleAtlassianResources first to obtain cloudId)\nmcp__atlassian__createJiraIssue (cloudId, projectKey=\"PROJ\", issueTypeName=\"Story\", summary=\"New feature\")\n\n# Confluence: create a page (body must be storage-format XHTML or ADF, not wiki markup)\nmcp__atlassian__createConfluencePage (cloudId, space, title=\"Sprint Retrospective\", body=<storage-format XHTML>)\n```\n\n**Not available via MCP** (use web UI/REST API): project creation, sprints, boards, filters, space creation, page deletion, labels, field/workflow/permission configuration, user provisioning, automation rules.\n\n## Skill-Specific Guidance\n\n### Senior PM (`senior-pm/`)\n\n**Focus:** Project planning, stakeholder management, risk mitigation\n\n**Key Workflows:**\n- Project charter creation\n- Stakeholder analysis and communication plans\n- Risk register maintenance\n- Status reporting and escalation\n\n### Scrum Master (`scrum-master/`)\n\n**Focus:** Agile ceremonies, team coaching, impediment removal\n\n**Key Workflows:**\n- Sprint planning facilitation\n- Daily standup coordination\n- Sprint retrospectives\n- Backlog refinement\n\n### Jira Expert (`jira-expert/`)\n\n**Focus:** Jira configuration, custom workflows, automation rules\n\n**Scripts:**\n- `scripts/jql_query_builder.py` — Pattern-matching JQL builder from natural language\n- `scripts/workflow_validator.py` — Validates workflow definitions for anti-patterns\n\n**Key Workflows:**\n- Workflow customization\n- Automation rule creation\n- Board configuration\n- JQL query optimization\n\n### Confluence Expert (`confluence-expert/`)\n\n**Focus:** Documentation strategy, templates, knowledge management\n\n**Scripts:**\n- `scripts/space_structure_generator.py` — Generates space hierarchy from team description\n- `scripts/content_audit_analyzer.py` — Analyzes page inventory for stale/orphaned content\n\n**Key Workflows:**\n- Space architecture design\n- Template library creation\n- Documentation standards\n- Search optimization\n\n### Atlassian Admin (`atlassian-admin/`)\n\n**Focus:** Suite administration, user management, integrations\n\n**Scripts:**\n- `scripts/permission_audit_tool.py` — Analyzes permission schemes for security gaps\n\n**Key Workflows:**\n- User provisioning and permissions\n- SSO/SAML configuration\n- App marketplace management\n- Performance monitoring\n\n### Atlassian Templates (`atlassian-templates/`)\n\n**Focus:** Ready-to-use templates for common PM tasks\n\n**Scripts:**\n- `scripts/template_scaffolder.py` — Generates Confluence storage-format XHTML templates\n\n**Available Templates:**\n- Sprint planning template\n- Retrospective formats (Start-Stop-Continue, 4Ls, Mad-Sad-Glad)\n- Project charter\n- Risk register\n- Decision log\n\n## Integration Patterns\n\n### Pattern 1: Sprint Planning\n\n```bash\n# 1. Create the sprint in the Jira board UI (sprint creation is NOT available via MCP —\n#    use Jira Software UI or REST /rest/agile/1.0/sprint)\n\n# 2. Generate user stories (product-team integration)\npython ../product-team/agile-product-owner/scripts/user_story_generator.py sprint 30\n\n# 3. Import stories to Jira via MCP: one mcp__atlassian__createJiraIssue call per story\n#    (cloudId, projectKey, issueTypeName=\"Story\", summary, description)\n```\n\n### Pattern 2: Documentation Workflow\n\n```bash\n# 1. Scaffold storage-format XHTML, then create the Confluence page via MCP\npython skills/atlassian-templates/scripts/template_scaffolder.py meeting-notes\n#    → pass the emitted markup as the body of mcp__atlassian__createConfluencePage\n\n# 2. Link the page to a Jira issue: paste the page URL into the issue via\n#    mcp__atlassian__editJiraIssue or as a comment via mcp__atlassian__addCommentToJiraIssue\n#    (read existing links with mcp__atlassian__getJiraIssueRemoteIssueLinks)\n```\n\n## Python Automation Tools\n\n### New Scripts (Phase 2)\n\n```bash\n# JQL from natural language\npython jira-expert/scripts/jql_query_builder.py \"high priority bugs assigned to me\"\n\n# Validate Jira workflow\npython jira-expert/scripts/workflow_validator.py workflow.json\n\n# Generate Confluence space structure\npython confluence-expert/scripts/space_structure_generator.py team_info.json\n\n# Audit Confluence content health\npython confluence-expert/scripts/content_audit_analyzer.py pages.json\n\n# Audit Atlassian permissions\npython atlassian-admin/scripts/permission_audit_tool.py permissions.json\n\n# Scaffold Confluence templates\npython atlassian-templates/scripts/template_scaffolder.py meeting-notes\n```\n\n## Additional Resources\n\n- **Installation Guide:** `INSTALLATION_GUIDE.txt`\n- **Implementation Summary:** `IMPLEMENTATION_SUMMARY.md`\n- **Real-World Scenario:** `REAL_WORLD_SCENARIO.md`\n- **PM Overview:** `README.md`\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 9/9 PM skills production-ready (pm-skills is now a fork-orchestrator + delivery loop)\n**Total Tools:** 15 Python automation tools\n**Agents:** cs-pm-orchestrator, cs-project-manager | **Commands:** 6\n**Integration:** Atlassian Remote MCP Server (bundled via `.mcp.json`) for Jira/Confluence automation\n","project-management/skills/atlassian-admin/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-admin%2FSKILL.md -->","project-management/skills/atlassian-admin/assets/permission_scheme_template.json":"<!-- Skill available on-demand via 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EU MDR 2017/745 compliance, technical documentation\n- fda-consultant-specialist - FDA 510(k), PMA, QSR compliance\n\n**Audit & Compliance (4 skills):**\n- qms-audit-expert - Internal audits, ISO 13485 certification\n- isms-audit-expert - ISO 27001 audits, security assessments\n- gdpr-dsgvo-expert - GDPR/DSGVO compliance, data privacy\n- soc2-compliance - SOC 2 Type I/II compliance, trust service criteria, audit readiness\n\n**Total:** 14 specialized compliance skills for medical device industry\n\n## Compliance Frameworks\n\n### ISO 13485 (Medical Device Quality Management)\n\n**Managed by:** quality-manager-qms-iso13485, qms-audit-expert\n\n**Key Areas:**\n- Management responsibility\n- Resource management\n- Product realization\n- Measurement, analysis, improvement\n\n**Tools:**\n- QMS process mapping\n- Document control systems\n- Change management workflows\n\n### ISO 14971 (Medical Device Risk Management)\n\n**Managed by:** risk-management-specialist\n\n**Key Areas:**\n- Risk analysis and evaluation\n- Risk control measures\n- Residual risk evaluation\n- Risk management review\n\n**Tools:**\n- Risk assessment templates\n- FMEA/FMECA analysis\n- Risk-benefit analysis\n\n### MDR 2017/745 (EU Medical Device Regulation)\n\n**Managed by:** mdr-745-specialist\n\n**Key Areas:**\n- Technical documentation (Annex II, III)\n- Clinical evaluation (Annex XIV)\n- Post-market surveillance\n- UDI (Unique Device Identification)\n\n### FDA Regulations (US Medical Device Compliance)\n\n**Managed by:** fda-consultant-specialist\n\n**Key Areas:**\n- 510(k) premarket notification\n- PMA (Premarket Approval)\n- QSR (Quality System Regulation)\n- Post-market reporting\n\n### ISO 27001 (Information Security Management)\n\n**Managed by:** information-security-manager-iso27001, isms-audit-expert\n\n**Key Areas:**\n- ISMS establishment and maintenance\n- Risk assessment and treatment\n- Security controls (Annex A)\n- Continuous improvement\n\n### GDPR/DSGVO (Data Protection)\n\n**Managed by:** gdpr-dsgvo-expert\n\n**Key Areas:**\n- Data protection impact assessment (DPIA)\n- Privacy by design\n- Data subject rights\n- Breach notification\n\n## Regulatory Workflows\n\n### Workflow 1: New Medical Device Development\n\n```\n1. Risk Management (ISO 14971) → risk-management-specialist\n2. QMS Process Setup (ISO 13485) → quality-manager-qms-iso13485\n3. Technical Documentation (MDR) → mdr-745-specialist\n4. FDA Submission → fda-consultant-specialist\n5. Clinical Evaluation → regulatory-affairs-head\n```\n\n### Workflow 2: QMS Audit Preparation\n\n```\n1. Internal Audit → qms-audit-expert\n2. CAPA Implementation → capa-officer\n3. Document Review → quality-documentation-manager\n4. Management Review → quality-manager-qmr\n5. Certification Audit → qms-audit-expert\n```\n\n### Workflow 3: Data Protection Compliance\n\n```\n1. GDPR Assessment → gdpr-dsgvo-expert\n2. ISMS Implementation → information-security-manager-iso27001\n3. Security Audit → isms-audit-expert\n4. Continuous Monitoring → information-security-manager-iso27001\n```\n\n## Integration Patterns\n\n**RA/QM ↔ Engineering:** Regulatory requirements inform technical design decisions\n\n**RA/QM ↔ Product:** Compliance requirements shape product features and roadmap\n\n**RA/QM ↔ Security:** ISO 27001 aligns with security engineering practices\n\n## Additional Resources\n\n- **RA/QM Overview:** `README.md`\n- **Complete Skills Collection:** `final-complete-skills-collection.md`\n- **Start Here:** `START_HERE.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 14/14 RA/QM skills production-ready\n**Focus:** Medical device compliance (ISO 13485, MDR, FDA, ISO 27001, GDPR)\n","ra-qm-team/compliance-team-eu-ai-act/.claude-plugin/plugin.json":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2F.claude-plugin%2Fplugin.json 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-->","research-ops/CLAUDE.md":"# Research Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `research-ops/`.\n\n## Purpose\n\nThe Research Operations domain ships skills that help **R&D leads, clinical study teams, R&D finance/controllers, market-research analysts, and product-research / ResearchOps teams** plan, fund, scope, and synthesize research across enterprise workstreams. This is the **enterprise / cross-functional counterpart** to the academic `research/` domain (litreview, grants, patent, syllabus, pulse, dossier, notebooklm).\n\nIt is **not regulatory submission** (`ra-qm-team`), **not corporate financial close/valuation** (`finance/financial-analysis`), **not funding discovery** (`research/grants`), **not persona/journey/live-experiment design** (`product-team`), and **not campaign analytics** (`marketing-skill`).\n\n## Skills (v2.9.0)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `research-ops-skills` | Domain orchestrator — routes to 4 sub-skills | YES |\n| `clinical-research` | Study design: protocol synopsis + endpoint selection + sample-size/power + phase-gating | NO |\n| `research-finance` | R&D program budgeting + burn/runway + F&A rate modeling + capitalize-vs-expense routing | NO |\n| `market-research` | TAM/SAM/SOM (both methods) + survey/sampling design + segmentation + CI synthesis | NO |\n| `product-research` | Study design + saturation/sample method + insight repository synthesis | NO |\n\n## Hard rules (domain-specific)\n\n1. **clinical-research: outputs are study-design RECOMMENDATIONS signed by a named clinician/biostatistician/regulatory owner.** Power/sample-size is an ESTIMATE with stated assumptions — never presented as clinical fact. Every tool prints an \"ESTIMATE — confirm with a biostatistician\" banner.\n2. **research-finance: every budget output surfaces its assumptions block.** Capitalize-vs-expense routes to a NAMED finance owner and never auto-decides accounting treatment.\n3. **market-research: TAM/SAM/SOM always shows method (top-down AND bottoms-up) + assumptions.** Never a single unsourced number.\n4. **product-research: never fabricates user insight.** Sample-size/saturation guidance is method-based and surfaces confidence; single-source claims are flagged as anecdotes, not insights.\n5. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n6. **Industry tuning** via `--profile` on every scoring tool.\n7. **Matt Pocock grill discipline** — `/cs-grill-research-ops` interrogates the plan against the research canon (ICH E9, IAS 38, Cochran, Nielsen, Kotler) before any sub-skill runs.\n8. **Onboarding-first + customization-in-use.** Each sub-skill ships `scripts/onboard.py` (its own question set) + `scripts/config_loader.py`. Answers persist to `~/.config/research-ops/<skill>.json` (global) or `./.research-ops/<skill>.json` (project) and are consumed by every tool (CLI flags override; `RESEARCH_OPS_NO_CONFIG=1` bypasses). Customization must change behavior, not sit as decoration.\n9. **Autoresearch is opt-in + isolated.** Each sub-skill ships `scripts/ar_evaluator.py` — a per-skill, locked ground-truth bridge to `engineering/autoresearch-agent`. A loop is invoked ONLY on explicit user request and only edits the skill's input file, never the evaluator. No cross-skill coupling.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scoring scripts + 3 references (each citing 5-7 sources) + 1 asset template, **plus** 3 integration scripts — `onboard.py` (questionnaire), `config_loader.py` (customization loader, project→global→defaults precedence), and `ar_evaluator.py` (isolated autoresearch bridge). SKILL.md includes a \"Forcing-question library\" section (cited-canon grilling, one question at a time) and the \"Onboarding & customization\" + \"Optimize with autoresearch (opt-in)\" sections.\n\n## Agent + command pattern\n\n- `cs-research-ops-orchestrator` — evidence-first R&D operations lead. Voice: \"What decision does this research drive, and what's your confidence — show me the method and the assumptions before the number.\"\n- `/cs-research-ops <inquiry>` — top-level router\n- `/cs-grill-research-ops <plan>` — Matt-style grilling first\n- `/cs-clinical-research`, `/cs-research-finance`, `/cs-market-research`, `/cs-product-research` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `ra-qm-team` (regulatory/QM submission) — clinical-research designs the **study**, not the submission\n- ❌ Skills that overlap `finance/financial-analysis` (close/valuation) — research-finance manages **R&D program spend**\n- ❌ Skills that overlap `research/grants` (funding discovery) — research-finance manages **money already won**\n- ❌ Skills that overlap `product-team` (persona/journey/live experiments) — product-research is **method + repository discipline**\n- ❌ Skills that overlap `marketing-skill` (campaign analytics) — market-research is **upstream methodology**\n- ❌ A market size stated as a single unsourced number\n- ❌ A clinical power/endpoint output presented as fact rather than an estimate with a named owner\n- ❌ A product insight asserted from a single participant\n\n## References\n\n- Master plan: `documentation/implementation/research-ops-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Academic counterpart: `research/` (litreview, grants, patent)\n- Regulatory complement: `ra-qm-team`\n- Corporate-finance complement: `finance/financial-analysis`\n- Product complement: `product-team`\n","research-ops/skills/clinical-research/SKILL.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2FSKILL.md -->","research-ops/skills/clinical-research/assets/protocol_synopsis_template.md":"<!-- Skill available on-demand via 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-->","research/syllabus/skills/syllabus/references/bundled_script_pattern.md":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fsyllabus%2Fskills%2Fsyllabus%2Freferences%2Fbundled_script_pattern.md -->","standards/CLAUDE.md":"# Standards Library - Claude Code Guidance\n\nThis guide explains how to use the standards library for consistent quality across all skills and agents.\n\n## Standards Overview\n\n**Location:** `standards/`\n\n**Available Standards:**\n1. **communication/** - Communication principles and response protocols\n2. **quality/** - Code quality, testing, and validation standards\n3. **git/** - Git workflow, conventional commits, branching strategy\n4. **documentation/** - Markdown quality, structure consistency, living docs\n5. **security/** - Secret detection, dependency security, input validation\n\n## When to Reference Standards\n\n### Communication Standards\n\n**Reference when:**\n- Writing agent documentation\n- Creating SKILL.md files\n- Drafting user-facing content\n- Providing technical guidance\n\n**Key Principles:**\n- Absolute honesty - Direct assessments without cushioning\n- Zero fluff - Eliminate vague statements\n- Pragmatic focus - Actionable suggestions only\n- File economy - Edit existing files vs creating new ones\n\n**Location:** `communication/communication-standards.md`\n\n### Quality Standards\n\n**Reference when:**\n- Creating Python automation tools\n- Writing agent workflows\n- Implementing skill features\n- Testing integration points\n\n**Key Areas:**\n- Python tool quality (PEP 8, type hints, docstrings)\n- Agent workflow clarity (minimum 3 workflows documented)\n- Testing requirements (functional, integration, documentation)\n- Completion criteria (zero defect handoff, validation requirements)\n\n**Location:** `quality/quality-standards.md`\n\n### Git Workflow Standards\n\n**Reference when:**\n- Committing code changes\n- Creating feature branches\n- Tagging releases\n- Writing commit messages\n\n**Commit Format:**\n```bash\n<type>[optional scope]: <description>\n\n[optional body]\n\n[optional footer(s)]\n```\n\n**Types:** feat, fix, docs, style, refactor, perf, test, chore, ci\n\n**Examples:**\n```bash\nfeat(agents): implement cs-content-creator agent\nfix(seo-optimizer): correct keyword density calculation\ndocs(README): add agent catalog section\n```\n\n**Location:** `git/git-workflow-standards.md`\n\n### Documentation Standards\n\n**Reference when:**\n- Writing SKILL.md files\n- Creating agent documentation\n- Updating README files\n- Writing reference guides\n\n**Best Practices:**\n- Max 200 lines per CLAUDE.md file\n- Markdown formatting standards (headings, lists, code blocks)\n- Living documentation (README, CLAUDE, AGENTS updated regularly)\n- Link validation (no 404s, no broken references)\n\n**Location:** `documentation/documentation-standards.md`\n\n### Security Standards\n\n**Reference when:**\n- Writing Python scripts\n- Handling user input\n- Managing dependencies\n- Committing code\n\n**Critical Checks:**\n- No hardcoded API keys, passwords, or tokens\n- Environment variables for sensitive data\n- Input validation for all user input\n- Dependency security audits\n\n**Location:** `security/security-standards.md`\n\n## Standards Application Workflow\n\n### For New Skills\n\n```bash\n# 1. Reference communication standards\ncat standards/communication/communication-standards.md\n\n# 2. Review quality standards for Python tools\ncat standards/quality/quality-standards.md\n\n# 3. Follow documentation standards for SKILL.md\ncat standards/documentation/documentation-standards.md\n\n# 4. Apply security standards to scripts\ncat standards/security/security-standards.md\n\n# 5. Use git standards for commits\ncat standards/git/git-workflow-standards.md\n```\n\n### For New Agents\n\n```bash\n# 1. Communication: Write clear, actionable agent docs\n# 2. Quality: Minimum 3 workflows, tested relative paths\n# 3. Documentation: Follow agent template structure\n# 4. Git: Conventional commit with feat(agents) scope\n```\n\n## Standards Hierarchy\n\n**Priority Order:**\n1. **Security** - Non-negotiable, always enforced\n2. **Quality** - Zero defect handoff required\n3. **Git** - Conventional commits for all changes\n4. **Documentation** - Living docs stay current\n5. **Communication** - Clear, pragmatic, actionable\n\n## Standards Compliance Checklist\n\n### Before Committing Code\n\n- [ ] Communication: Documentation is clear and actionable\n- [ ] Quality: All tests passing, code reviewed\n- [ ] Git: Conventional commit message format\n- [ ] Documentation: Living docs updated if needed\n- [ ] Security: No secrets, input validated, dependencies secure\n\n### Before Creating PR\n\n- [ ] All standards compliance checks passed\n- [ ] Related documentation updated\n- [ ] Examples tested and working\n- [ ] No broken links or references\n\n## Related Documentation\n\n- **Main CLAUDE.md:** `../CLAUDE.md`\n- **Agent Development:** `../agents/CLAUDE.md`\n- **Domain Skills:** See navigation map in main CLAUDE.md\n\n---\n\n**Last Updated:** November 5, 2025\n**Standards Count:** 5 comprehensive standards\n**Enforcement:** Required for all skills and agents\n","templates/CLAUDE.md":"# Templates - Claude Code Guidance\n\nThis guide explains the template system for agents, commands, and standardized workflows.\n\n## Template Purpose\n\n**Location:** `templates/`\n\n**Purpose:** Reusable templates for consistent agent development, slash command creation, and workflow automation across all domains.\n\n## Available Templates\n\n### Agent Templates\n\n**Location:** `templates/agent-template.md`\n\n**Usage:** Starting point for creating new cs-* agents\n\n**Contains:**\n- YAML frontmatter structure\n- Required markdown sections\n- Workflow documentation format\n- Integration examples pattern\n\n**When to Use:** Creating any new agent in `agents/` directory\n\n### Command Templates and Workflow Templates\n\nNot yet created. There is no command template or workflow template file in `templates/` today — when creating slash commands, copy an existing command in `commands/` (e.g. `commands/cs-backend-review.md` for the argument-hint + gate pattern) instead of looking for a template here.\n\n## Template Usage Pattern\n\n```bash\n# 1. Copy template\ncp templates/agent-template.md agents/domain/cs-new-agent.md\n\n# 2. Customize for your agent\nvim agents/domain/cs-new-agent.md\n\n# 3. Follow template structure exactly\n\n# 4. Test relative paths and integrations\n\n# 5. Commit with conventional commit\ngit commit -m \"feat(agents): implement cs-new-agent from template\"\n```\n\n## Related Documentation\n\n- **Agent Development:** `../agents/CLAUDE.md` - Comprehensive agent creation guide\n- **Standards:** `../standards/CLAUDE.md` - Quality and consistency standards\n- **Main Documentation:** `../CLAUDE.md` - Repository overview\n\n---\n\n**Last Updated:** November 5, 2025\n**Purpose:** Consistent templates for rapid agent and workflow development\n"},"items":[{"name":"llms-full.txt","path":"docs/llms-full.txt","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/llms-full.txt","title":"docs - LLM Full Documentation Context","category":"root-instruction","format":"text","content":"# Claude Code Skills & Agent Plugins — Full Repository Description\n\n> A comprehensive, self-contained description of the `alirezarezvani/claude-skills` repository, written for AI agents and LLM crawlers. This file follows the [llms.txt](https://llmstxt.org) convention (`llms-full.txt` variant: the expanded, single-file version). For the concise index, see [llms.txt](https://alirezarezvani.github.io/claude-skills/llms.txt).\n\n- **Project:** Claude Code Skills & Agent Plugins\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Documentation site:** https://alirezarezvani.github.io/claude-skills/\n- **Author:** Alireza Rezvani\n- **License:** MIT (free to extract, deploy, adapt, and redistribute)\n- **Distribution:** Claude Code plugin marketplace (`.claude-plugin/marketplace.json`) and the ClawHub registry (clawhub.com)\n\n---\n\n## What this repository is\n\nThis is a **library of skill packages** for Claude AI and Claude Code — reusable, production-ready modules that bundle domain expertise, best practices, deterministic analysis tools, and strategic frameworks. It is **not a traditional application**. It is a catalog of self-contained skill folders meant to be extracted and deployed by users into their own AI-agent workflows.\n\nTeams download a skill folder and use it immediately: the skill's `SKILL.md` teaches the agent the workflow, the `scripts/` provide deterministic Python CLI tools, the `references/` supply expert knowledge bases, and the `assets/` give ready-to-customize templates.\n\n### Headline scale (derived from the tree by `scripts/derive_counters.py`)\n\n| Metric | Count |\n|--------|-------|\n| Production-ready skills | 354 |\n| Marketplace plugins | 82 |\n| Top-level domains | 18 |\n| Python automation tools | 593 |\n| Reference guides | 722 |\n| Agents (cs-* + personas) | 96 |\n| Slash commands | 102 |\n\nCounters are generated from the actual file tree; run `python3 scripts/derive_counters.py --check` to verify the docs still match the tree.\n\n---\n\n## Cross-tool compatibility\n\nSkills are authored once and made portable across many AI coding agents via sync scripts in `scripts/`. Supported targets include:\n\n- **Claude Code** (primary) — plugins, agents, slash commands, MCP servers, hooks\n- **OpenAI Codex** — `scripts/sync-codex-skills.py`, `~/.codex/`\n- **Gemini CLI** — `scripts/sync-gemini-skills.py`\n- **Cursor** — rules-format export\n- **Hermes Agent** — `scripts/sync-hermes-skills.py`\n- **Mistral Vibe** — `scripts/sync-vibe-skills.py`, `~/.vibe/skills/`\n- **Codebuff** — `scripts/sync-codebuff-skills.py`\n- **OpenClaw**, **Aider**, **Windsurf**, **Kilo Code**, **OpenCode**, **Augment**, **Antigravity** — documented in the Multi-Tool Integrations guide.\n\n---\n\n## Design principles\n\n1. **Skills are products.** Each skill is deployable as a standalone package with no dependency on other skills.\n2. **Documentation-driven.** Success depends on clear, actionable `SKILL.md` docs.\n3. **Algorithm over AI.** Analysis tools use deterministic Python (standard library only) — **no LLM/ML calls inside scripts**. This keeps skills portable, fast, and reproducible.\n4. **Template-heavy.** Skills ship ready-to-use templates users customize.\n5. **Platform-specific.** Specific, actionable frameworks beat generic advice.\n\n### Anti-patterns the repo deliberately avoids\n- Dependencies between skills (each stays self-contained)\n- Complex build systems or test frameworks (portability first)\n- Generic advice instead of specific frameworks\n- LLM calls in scripts (defeats portability and speed)\n\n---\n\n## Skill package pattern\n\nEvery skill follows this structure:\n\n```\nskill-name/\n├── SKILL.md        # Master documentation: the workflow the agent follows\n├── scripts/        # Python CLI tools (stdlib-only, no LLM calls; support --help and JSON output)\n├── references/     # Expert knowledge bases (markdown), each citing 5-8 authoritative sources\n└── assets/         # User-facing templates\n```\n\nKnowledge flows: `references/` → informs `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\nEach `SKILL.md` carries YAML frontmatter with a `name` and a `description` whose trigger phrasing (e.g. \"Use when…\") tells the agent when to invoke the skill.\n\n---\n\n## Repository structure\n\n```\nclaude-skills/\n├── .claude-plugin/        # Plugin registry (marketplace.json — 82 plugins)\n├── agents/                # cs-* agents + 7 personas\n├── commands/              # Slash commands\n├── engineering-team/      # Core engineering skills\n├── engineering/           # POWERFUL-tier advanced engineering skills\n├── product-team/          # Product skills\n├── marketing-skill/       # Marketing skills (8 pods incl. AEO)\n├── marketing/             # Landing-page generator skill\n├── c-level-advisor/       # C-level advisory skills (full C-suite + founder-mode)\n├── project-management/    # PM skills + bundled Atlassian Remote MCP\n├── ra-qm-team/            # Regulatory / quality-management compliance skills\n├── compliance-os/         # Compliance audit-prep orchestrator + sub-skills\n├── business-growth/       # Customer success, sales eng, revops\n├── business-operations/   # Internal-ops skills (orchestrator + sub-skills)\n├── commercial/            # Per-deal-economics skills (orchestrator + sub-skills)\n├── finance/               # Finance skills\n├── research/              # Academic research skills (orchestrator + specialists)\n├── research-ops/          # Enterprise research operations (orchestrator + sub-skills)\n├── productivity/          # Capture, email, reflect, handoff, andreessen\n├── markdown-html/         # Markdown-to-interactive-HTML converter suite\n├── standards/             # Communication, quality, git, security standards\n├── templates/             # Reusable templates\n├── docs/                  # This MkDocs Material documentation site\n└── scripts/               # Build, sync, and validation scripts\n```\n\n---\n\n## The 18 domains in detail\n\n### Engineering — Core (`engineering-team/`)\nFullstack, AI/ML, DevOps, security, data, and QA skills. Includes senior-role skills (architect, backend, frontend, fullstack, DevOps, data engineer/scientist, ML, computer vision, prompt, QA, security, SecOps), cloud architects (AWS/Azure/GCP), a full security suite (adversarial reviewer, AI security, cloud security, incident response, red team, threat detection, pen testing), Playwright Pro (10 sub-skills), a Self-Improving Agent suite, Snowflake development, and Stripe integration.\n\n### Engineering — POWERFUL (`engineering/`)\nAdvanced, higher-leverage engineering skills: agent design, RAG architecture, MCP server building, CI/CD pipelines, database/schema design, observability, SLO architecture, chaos engineering, Kubernetes operators, feature-flags, migration architecture, performance profiling, dependency auditing, and meta-skills for **authoring skills** (`write-a-skill`), token compression (`caveman`), plan interrogation (`grill-me`), and conversation continuity (`handoff`). Also hosts AgentHub, the autoresearch-agent (Karpathy file-optimization loop), the LLM Wiki, ship-gate, and a PreToolUse security-guidance hook.\n\n### Product (`product-team/`)\nRICE prioritization, OKRs, user stories, UX research and design, product discovery/strategy, competitive teardowns, experiment design, product analytics, SaaS scaffolding, code-to-PRD, spec-to-repo, and an Apple HIG expert.\n\n### Marketing (`marketing-skill/`)\nEight pods spanning content creation, copywriting/editing, SEO, **AEO (Answer Engine Optimization)**, ASO (app-store optimization), demand generation, paid ads, CRO (conversion-rate optimization across page/form/signup/paywall/popup/onboarding), social media, email sequences, pricing strategy, launch strategy, schema markup, and campaign analytics.\n\n### Marketing — Landing Pages (`marketing/`)\nA single-file HTML landing-page generator with multiple design styles, brand-palette validation, and GSAP animation patterns.\n\n### Project Management (`project-management/`)\nJira and Confluence experts, Atlassian admin/templates, scrum master, senior PM, meeting analyzer, and team communications. Ships a bundled Atlassian Remote MCP (`.mcp.json`, SSE transport, OAuth handled by Claude Code).\n\n### C-Level Advisory (`c-level-advisor/`)\nA full C-suite of opinionated advisor skills (CEO, CFO, CMO, CPO, CRO, COO, CTO, CHRO, CISO, CDO, CAIO, CCO, VP Engineering, General Counsel) plus a **Founder-Mode** operating system: `/c-level-agents:office-hours`, `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`, plus onboarding, cross-eval, and decision-freeze commands. Includes an Executive Mentor suite and strategic frameworks (RICE, JTBD, OKR, ADKAR, Wardley mapping). Memory is Markdown-only (no database dependency).\n\n### Regulatory & Quality (`ra-qm-team/`)\nISO 13485, EU MDR 2017/745, FDA, GDPR/DSGVO, ISO 27001, SOC 2, CAPA, risk management, and QMS/ISMS audit skills for regulated industries (notably medical devices).\n\n### Compliance OS (`compliance-os/`)\nAn orchestrator plus audit-prep sub-skills for SOC 2, ISO 13485, ISO 27001, GDPR, FDA QSR, EU AI Act readiness, and ISO 42001 (AIMS).\n\n### Business & Growth (`business-growth/`)\nCustomer success management, sales engineering, revenue operations, and contract/proposal writing.\n\n### Business Operations (`business-operations/`)\nInternal-ops skills for BizOps leads and COO direct reports: process mapping (BPMN + bottleneck + cycle-time), vendor management (scorecard + SLA + third-party risk), capacity planning (Erlang-C), internal comms (ADKAR + Kotter), knowledge ops (SOP/runbook hygiene), and procurement optimization. Orchestrator uses `context: fork` chaining. Every output is a recommendation routed to a named human — never an auto-decision.\n\n### Commercial (`commercial/`)\nPer-deal-and-packaging skills: pricing strategist (model picker + Van Westendorp PSM + packaging), deal desk (scorer + approval router + redliner), partnerships architect, channel economics, commercial policy, RFP responder (Shipley method), and commercial forecaster. Pricing outputs a model and a range (never a single number); deal outputs route to a named approver (never auto-approve).\n\n### Finance (`finance/`)\nFinancial analysis, DCF valuation, budgeting/forecasting, business investment advisory, and SaaS-metrics coaching.\n\n### Research (`research/`)\nAcademic/literature research: an orchestrator (hybrid router) plus specialists for recency+sentiment pulse, literature review, NIH grants, entity dossiers, patent/prior-art landscapes, course-reading syllabi, and NotebookLM browser automation.\n\n### Research Operations (`research-ops/`)\nThe enterprise counterpart to `research/`: clinical study design (sample size, endpoints, phase-gate — estimates confirmed by a named clinical owner), R&D program finance (budget, burn/runway, CapEx-vs-OpEx routing), market research (TAM/SAM/SOM with method + assumptions, never a single number), and product research (study design, saturation planning, insight synthesis requiring recurrence across independent participants).\n\n### Productivity (`productivity/`)\nCapture (brain-dump-to-action), email (inbox setup + triage, drafts-only), reflect (light-prompt journaling), handoff (conversation continuity with redaction linting and session hooks), and andreessen (market-first decision engine).\n\n### Markdown to HTML (`markdown-html/`)\nA converter suite operationalizing Thariq Shihipar's thesis that markdown collapses past ~100 lines and HTML restores density/clarity/shareability. Ships an orchestrator (doctype router), a design-system onboarding wizard (WCAG-AA-validated brand palette), and three converters: `md-document` (long-form → single-file HTML with TOC/search/code-copy/scrollspy), `md-review` (code-review markdown → 2-column diff + severity annotations), and `md-slides` (markdown deck → single-file HTML presentation with keyboard nav, presenter mode, and print-to-PDF). Output is single-file HTML (Google Fonts + Prism.js CDN the only permitted externals).\n\n---\n\n## Agents and slash commands\n\n- **Agents (`agents/`):** 96 total, mostly `cs-*` prefixed personas (e.g. `cs-ceo-advisor`, `cs-senior-engineer`, `cs-aeo`, domain orchestrators) plus 7 general personas. Agents orchestrate skills and carry a distinct operating voice.\n- **Slash commands (`commands/`):** 102 total, including `/prd`, `/rice`, `/okr`, `/tdd`, `/changelog`, `/slo-design`, `/chaos-experiment`, `/plugin-audit`, `/seo-auditor`, and the `/cs-*` family (office-hours, boardroom, bizops, commercial, research-ops, markdown-html routers, and per-skill commands).\n\n---\n\n## Plugin distribution\n\nPlugins are registered in `.claude-plugin/marketplace.json` (82 plugins) across these categories: development (34), leadership (9), research (9), productivity (6), marketing (5), compliance (4), product (4), finance (2), and one each of project-management, business-growth, design, knowledge, operations, commercial, research-ops, documentation, and engineering.\n\n### plugin.json rules (for anyone extending the library)\n- Required fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills`.\n- Two approved extension fields: `source` (provenance for megaprompt-derived skills) and `attribution` (credit for MIT-licensed external derivations).\n- Skill paths are relative to the plugin root and start with `./`. Canonical forms: single-skill = `[\"./\"]`; `skills/` subdir = `\"./skills\"`; multi-skill domain = explicit `[\"./sub1\", \"./sub2\", ...]`.\n- Validation: `scripts/check_plugin_json.py --all` runs in CI on every PR.\n\n---\n\n## Git and contribution workflow\n\n- **Branch strategy:** feature → dev → main. **All PRs target `dev`, never `main`.** `main` receives only periodic `dev → main` promotion PRs from the maintainer.\n- **Conventional commits** are enforced (e.g. `feat(agents): …`, `fix(tool): …`, `docs(workflow): …`).\n- **Branch protection:** `main` requires PR approval; direct pushes are blocked.\n\n### ClawHub publishing constraints\n- The `cs-` prefix is used only on the ClawHub registry when a slug conflicts with another publisher — repo folder names and local skill names are never renamed.\n- No paid/commercial service dependencies; free-tier APIs and bring-your-own-key patterns are acceptable.\n- Rate limit: 5 new skills per hour.\n- Package versions match the repo release version.\n\n---\n\n## How an agent should use this repository\n\n1. **Find a matching skill** by browsing the [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/) or a domain index, matching the task to a skill's `description` trigger.\n2. **Read the skill's `SKILL.md`** to learn the workflow.\n3. **Run the skill's Python tools** (`scripts/*.py`, stdlib-only, all support `--help` and most support JSON output) for deterministic analysis.\n4. **Consult `references/`** for the expert knowledge underpinning the workflow.\n5. **Apply the `assets/` templates** to produce the deliverable.\n\nTo install as a plugin, add the marketplace and install the relevant plugin via Claude Code; see [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/) and [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/) for non-Claude tools.\n\n---\n\n*Generated to make the repository accessible to AI agents. Counters reflect `scripts/derive_counters.py` at the time of writing; the repository evolves — the GitHub repository and documentation site are the authoritative sources.*\n","isInternal":false,"tokens":3687,"sizeBytes":15780},{"name":"llms.txt","path":"docs/llms.txt","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/llms.txt","title":"docs - LLM Index & Context Digest","category":"root-instruction","format":"text","content":"# Claude Code Skills & Agent Plugins\n\n> An open-source (MIT) library of 354 production-ready agent skills, 82 installable plugins, 96 agents, and 102 slash commands across 18 domains — engineering, product, marketing, compliance, finance, research, and more. Each skill is a self-contained package bundling domain expertise, deterministic Python tools (stdlib-only, no LLM calls), reference knowledge bases, and ready-to-use templates. Skills are portable across Claude Code, OpenAI Codex, Gemini CLI, Cursor, Hermes Agent, Mistral Vibe, OpenClaw, and 6+ more AI coding tools.\n\nThis file follows the [llms.txt](https://llmstxt.org) convention. For a full, self-contained description of the entire repository, see [llms-full.txt](https://alirezarezvani.github.io/claude-skills/llms-full.txt).\n\nKey facts for agents:\n- **License:** MIT. Free to extract, deploy, and adapt.\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Distribution:** Claude Code plugin marketplace + ClawHub registry.\n- **Design philosophy:** Algorithm over AI (deterministic code, not LLM calls in tools), documentation-driven, template-heavy, self-contained skills.\n- **Skill package shape:** `SKILL.md` (master doc) + `scripts/` (Python CLI tools) + `references/` (knowledge bases) + `assets/` (templates).\n\n## Getting started\n\n- [Home](https://alirezarezvani.github.io/claude-skills/): Overview and value proposition.\n- [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/): Install and use skills/plugins.\n- [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/): Using skills with Codex, Gemini CLI, Cursor, Hermes, Vibe, OpenClaw, and more.\n- [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/): Index of all 354 skills by domain.\n- [Plugins](https://alirezarezvani.github.io/claude-skills/plugins/): The 82 installable marketplace plugins.\n- [Agents](https://alirezarezvani.github.io/claude-skills/agents/): The 96 cs-* agents and personas.\n- [Commands](https://alirezarezvani.github.io/claude-skills/commands/): The 102 slash commands.\n\n## Domains\n\n- [Engineering — Core](https://alirezarezvani.github.io/claude-skills/skills/engineering-team/): Fullstack, AI/ML, DevOps, security, data, QA.\n- [Engineering — POWERFUL](https://alirezarezvani.github.io/claude-skills/skills/engineering/): Agent design, RAG, MCP, CI/CD, observability, SLOs, skill authoring.\n- [Product](https://alirezarezvani.github.io/claude-skills/skills/product-team/): RICE, OKRs, user stories, UX research, SaaS scaffolding.\n- [Marketing](https://alirezarezvani.github.io/claude-skills/skills/marketing-skill/): Content, SEO, AEO, ASO, demand gen, campaign analytics.\n- [Project Management](https://alirezarezvani.github.io/claude-skills/skills/project-management/): Jira/Confluence, Atlassian MCP, scrum.\n- [C-Level Advisory](https://alirezarezvani.github.io/claude-skills/skills/c-level-advisor/): Full C-suite advisors + founder-mode orchestration.\n- [Regulatory & Quality](https://alirezarezvani.github.io/claude-skills/skills/ra-qm-team/): ISO 13485, MDR, FDA, GDPR, ISO 27001.\n- [Compliance OS](https://alirezarezvani.github.io/claude-skills/skills/compliance-os/): Audit-prep orchestrator for SOC 2, ISO, GDPR, EU AI Act.\n- [Business & Growth](https://alirezarezvani.github.io/claude-skills/skills/business-growth/): Customer success, sales engineering, revenue operations.\n- [Business Operations](https://alirezarezvani.github.io/claude-skills/skills/business-operations/): Process mapping, vendor management, capacity planning.\n- [Commercial](https://alirezarezvani.github.io/claude-skills/skills/commercial/): Pricing, deal desk, partnerships, RFP response.\n- [Finance](https://alirezarezvani.github.io/claude-skills/skills/finance/): Financial analysis, DCF valuation, SaaS metrics.\n- [Research](https://alirezarezvani.github.io/claude-skills/skills/research/): Literature review, grants, patents, entity dossiers.\n- [Research Operations](https://alirezarezvani.github.io/claude-skills/skills/research-ops/): Clinical study design, R&D finance, market/product research.\n- [Productivity](https://alirezarezvani.github.io/claude-skills/skills/productivity/): Capture, email triage, reflection, handoff.\n- [Markdown to HTML](https://alirezarezvani.github.io/claude-skills/skills/markdown-html/): Markdown-to-interactive-HTML converter suite.\n\n## Optional\n\n- [Guides](https://alirezarezvani.github.io/claude-skills/guides/best-claude-code-plugins/): Best plugins, per-tool skill guides (Codex, Gemini CLI, Cursor, OpenClaw).\n- [Orchestration](https://alirezarezvani.github.io/claude-skills/orchestration/): How skills chain together.\n- [Custom GPTs](https://alirezarezvani.github.io/claude-skills/custom-gpts/): Using the library with custom GPTs.\n- [Personas](https://alirezarezvani.github.io/claude-skills/personas/): Startup CTO, Growth Marketer, Solo Founder bundles.\n","isInternal":false,"tokens":1334,"sizeBytes":4939},{"name":"CLAUDE.md","path":"agent-launcher/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/CLAUDE.md","title":"agent-launcher - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# CLAUDE.md — agent-launcher domain\n\nGuidance for working inside `agent-launcher/`. See the root `CLAUDE.md` for\nrepo-wide rules.\n\n## What this domain is\n\nA plugin that scaffolds and launches **Claude Managed Agents (CMA)** in the user's\nown Anthropic account, organized around a **per-session goal** that compiles into a\n**loop or workflow**. Inspired by `anthropics/launch-your-agent` (Apache-2.0);\nindependent re-implementation, not a fork.\n\n## Non-negotiable rules (enforced by SPEC.md + validators)\n\n1. **Deterministic scaffolders only.** Every script under `skills/*/scripts/` is\n   stdlib-only and makes **no** network/API calls. Live launches are emitted as\n   BYOK curl. Do not add `requests`, `anthropic`, or any network client.\n2. **Never surface the API key.** Launch scripts read `$ANTHROPIC_API_KEY`; no\n   tool echoes/logs/writes a key. `payload_validator.py` and reviewers check this.\n3. **CMA limits are law.** Keep `references/cma-primitives.md` as the source of\n   truth for ceilings; validators must match it.\n4. **Bounded loops only.** `loop_compiler.py` never emits a grade→iterate loop\n   without a `max_iterations` cap (1..20).\n5. **The hook is opt-in and crash-proof.** Gated by `AGENT_LAUNCHER_SESSION=1`;\n   exits 0 on any error. Never make it fire unconditionally.\n6. **The folder is the user's.** All artifacts go under `./my-agent/`; scripts\n   accept `--out-dir` and default there. Never write into the plugin folder.\n\n## Structure\n\n- `skills/agent-launcher-orchestrator/` — `context: fork` goal router\n  (`goal_router.py`, `goal_state.py`, `loop_compiler.py`).\n- `skills/{interview,stage-launch,grade-iterate,run-without-you,wrap-up}/` — one\n  phase each, 3 tools each.\n- `agents/` — `cs-agent-launcher-orchestrator` + 3 phase specialists.\n- `commands/` — 8 `/cs-*` commands.\n- `hooks/` — opt-in `session_start.py` / `session_end.py` + `hooks.json`.\n- `references/` — 5 shared docs. `assets/` — schema + templates + example.\n\n## Tool conventions\n\n- Every tool: `argparse` with real `--help`, a `--sample` that runs a deterministic\n  demo and exits 0, and JSON output via `--json` where a machine reads it.\n- Default output dir `./my-agent/`; never assume network access.\n- Import shared logic via relative `sys.path` insert (see how the orchestrator\n  tools import `goal_state`).\n\n## Forcing-question discipline\n\nEvery SKILL.md ships a \"Forcing-question library\" (Matt Pocock grill-with-docs):\nwalk one question at a time, recommend an answer, cite the reference. The\n`/cs-grill-agent-launcher` command surfaces them.\n\n## When editing\n\n- Changing a CMA limit → update `references/cma-primitives.md` **and** every\n  validator in lockstep.\n- Adding a loop shape → update `loop_compiler.py` **and**\n  `references/loops-and-workflows.md`.\n- Keep `SPEC.md` authoritative; if you ship something different, record it in the\n  delivery report.\n","isInternal":false,"tokens":770,"sizeBytes":2890},{"name":"CLAUDE.md","path":"agents/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agents/CLAUDE.md","title":"agents - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Agent Development Guide\n\nThis guide provides comprehensive instructions for creating **cs-* prefixed agents** that seamlessly integrate with the 346 production skills in this repository (count derived via `scripts/derive_counters.py`).\n\n## Agent Architecture\n\n### What are cs-* Agents?\n\n**cs-* agents** are specialized Claude Code agents that orchestrate the repository's 346 skills. Each agent:\n- References skills via relative paths (`../marketing-skill/`)\n- Executes Python automation tools from skill packages\n- Follows established workflows and templates\n- Maintains skill portability and independence\n\n**Key Principle**: Agents ORCHESTRATE skills, they don't replace them. Skills remain self-contained and portable.\n\n### ClawHub Publishing Constraints\n\nWhen skills are published to **ClawHub** (clawhub.com):\n- **cs- prefix for slug conflicts only** — applies only on the ClawHub registry when another publisher already owns the slug. Repo folder names and local skill names are never renamed.\n- **No paid/commercial service dependencies** — skills must not require paid third-party API keys or commercial services unless provided by the project itself.\n- **plugin.json** — ONLY fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills: \"./\"`.\n- **Rate limit:** 5 new skills/hour on ClawHub. Use drip publishing for bulk operations.\n\n### Production Agents\n\n**33 agents live in this folder** (93 agent files repo-wide, including plugin-bundled agents). A representative selection:\n\n| Agent | Domain | Description |\n|-------|--------|-------------|\n| [cs-content-creator](marketing/cs-content-creator.md) | Marketing | AI-powered content creation with brand voice consistency and SEO optimization |\n| [cs-demand-gen-specialist](marketing/cs-demand-gen-specialist.md) | Marketing | Demand generation and customer acquisition specialist |\n| [cs-ceo-advisor](c-level/cs-ceo-advisor.md) | C-Level | Strategic leadership advisor for CEOs |\n| [cs-cto-advisor](c-level/cs-cto-advisor.md) | C-Level | Technical leadership advisor for CTOs |\n| [cs-product-manager](product/cs-product-manager.md) | Product | RICE prioritization and customer discovery |\n| [cs-product-strategist](product/cs-product-strategist.md) | Product | Product strategy, OKR cascades, market positioning |\n| [cs-agile-product-owner](product/cs-agile-product-owner.md) | Product | Agile product ownership and backlog management |\n| [cs-ux-researcher](product/cs-ux-researcher.md) | Product | UX research, usability testing, design insights |\n| [cs-product-analyst](product/cs-product-analyst.md) | Product | Product analytics, KPI design, experiment design |\n| [cs-engineering-lead](engineering-team/cs-engineering-lead.md) | Engineering | Engineering team coordination and incident management |\n| [cs-workspace-admin](engineering-team/cs-workspace-admin.md) | Engineering | Google Workspace administration via gws CLI |\n| [cs-senior-engineer](engineering/cs-senior-engineer.md) | Engineering | Architecture decisions, code review, CI/CD setup |\n| [cs-fullstack-engineer](engineering/cs-fullstack-engineer.md) | Engineering | Fullstack orchestrator (v2.8.1): walks 7 Matt Pocock forcing questions, picks profile via deterministic engine, forks (`context: fork`) into api-design-reviewer / database-designer / slo-architect / ci-cd-pipeline-builder. Invokable via `/cs-fullstack-review` or `Agent({subagent_type:\"cs-fullstack-engineer\"})`. |\n| [cs-frontend-engineer](engineering/cs-frontend-engineer.md) | Engineering | Frontend orchestrator (v2.8.1): walks 7 forcing questions (device, LCP target, rendering, bundle, SEO, design system, WCAG), picks framework profile, forks into a11y-audit / performance-profiler / epic-design / apple-hig-expert. Invokable via `/cs-frontend-review`. |\n| [cs-backend-engineer](engineering/cs-backend-engineer.md) | Engineering | Backend orchestrator (v2.8.1): walks 7 forcing questions (read/write + QPS, tenancy, sync vs async, sensitivity, pattern, RPO/RTO, SLO), picks language + pattern profile, forks into api-design-reviewer / database-designer / migration-architect / slo-architect / observability-designer. Invokable via `/cs-backend-review`. |\n| [cs-growth-strategist](business-growth/cs-growth-strategist.md) | Business | Growth strategy and revenue optimization |\n| [cs-financial-analyst](finance/cs-financial-analyst.md) | Finance | Financial analysis, DCF valuation, SaaS metrics |\n| [cs-project-manager](project-management/cs-project-manager.md) | PM | Project management with Atlassian integration |\n| [cs-quality-regulatory](ra-qm-team/cs-quality-regulatory.md) | RA/QM | Regulatory affairs and quality management |\n\n**Template Available**: [templates/agent-template.md](../templates/agent-template.md) (318 lines) - Use this to create new agents\n\n### Agent vs Skill\n\n| Aspect | Agent (cs-*) | Skill |\n|--------|-------------|-------|\n| **Purpose** | Orchestrate and execute workflows | Provide tools, knowledge, templates |\n| **Location** | `agents/domain/` | `domain-skill/skill-name/` |\n| **Structure** | Single .md file with YAML frontmatter | SKILL.md + scripts/ + references/ + assets/ |\n| **Integration** | References skills via `../../` | Self-contained, no dependencies |\n| **Naming** | cs-content-creator, cs-ceo-advisor | content-creator, ceo-advisor |\n\n## Agent File Structure\n\n### Required YAML Frontmatter\n\nEvery agent file must start with valid YAML frontmatter:\n\n```yaml\n---\nname: cs-agent-name\ndescription: One-line description of what this agent does\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n```\n\n**Field Definitions:**\n- **name**: Agent identifier with `cs-` prefix (e.g., `cs-content-creator`)\n- **description**: Single sentence describing agent's purpose\n- **No `skills:` field.** Claude Code preloads every skill listed there into the subagent's context on each spawn (resolved by `plugin:skill` name, not by path). This repo's agents are lightweight routers, so name the skill folder in the agent body instead and let the agent load it on demand (decision recorded on PR #939).\n- **domain**: Domain category (marketing, product, engineering, c-level, pm, ra-qm)\n- **model**: Claude model to use (sonnet, opus, haiku)\n- **tools**: Array of Claude Code tools agent can use\n\n### Required Markdown Sections\n\nAfter YAML frontmatter, include these sections:\n\n1. **Purpose** (2-3 paragraphs)\n2. **Skill Integration** (with subsections)\n   - Skill Location\n   - Python Tools\n   - Knowledge Bases\n   - Templates\n3. **Workflows** (minimum 3 workflows)\n4. **Integration Examples** (concrete code/command examples)\n5. **Success Metrics** (how to measure effectiveness)\n6. **Related Agents** (cross-references)\n7. **References** (links to documentation)\n\n## Relative Path Resolution\n\n### Path Pattern\n\nAll skill references use the `../../` pattern:\n\n```markdown\n**Skill Location:** `../marketing-skill/skills/content-creator/`\n\n### Python Tools\n\n1. **Brand Voice Analyzer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py content.txt`\n\n2. **SEO Optimizer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/seo_optimizer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"keyword\"`\n```\n\n### Why `../../`?\n\nFrom agent location: `agents/marketing/cs-content-creator.md`\nTo skill location: `marketing-skill/content-creator/`\n\nNavigation: `agents/marketing/` → `../../` (up to root) → `marketing-skill/content-creator/`\n\n**Always test paths resolve correctly!**\n\n## Python Tool Integration\n\n### Execution Pattern\n\nAgents execute Python tools from skill packages:\n\n```bash\n# From agent context\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt\n\n# With JSON output\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt json\n\n# With arguments\npython ../product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n```\n\n### Tool Requirements\n\nAll Python tools must:\n- Use standard library only (or minimal dependencies documented in SKILL.md)\n- Support both JSON and human-readable output\n- Provide `--help` flag with usage information\n- Return appropriate exit codes (0 = success, 1 = error)\n- Handle missing arguments gracefully\n\n### Error Handling\n\nWhen Python tools fail:\n1. Check file path resolution\n2. Verify input file exists\n3. Check Python version compatibility (3.8+)\n4. Review tool's `--help` output\n5. Inspect error messages in stderr\n\n## Workflow Documentation\n\n### Workflow Structure\n\nEach workflow must include:\n\n```markdown\n### Workflow 1: [Clear Descriptive Name]\n\n**Goal:** One-sentence description\n\n**Steps:**\n1. **[Action]** - Description with specific commands/tools\n2. **[Action]** - Description with specific commands/tools\n3. **[Action]** - Description with specific commands/tools\n\n**Expected Output:** What success looks like\n\n**Time Estimate:** How long this workflow takes\n\n**Example:**\n\\`\\`\\`bash\n# Concrete example command\npython ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"primary keyword\"\n\\`\\`\\`\n```\n\n### Minimum Requirements\n\nEach agent must document **at least 3 workflows** covering:\n1. Primary use case (most common scenario)\n2. Advanced use case (complex scenario)\n3. Integration use case (combining multiple tools)\n\n## Agent Template\n\nUse this template when creating new agents:\n\n```markdown\n---\nname: cs-agent-name\ndescription: One-line description\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n\n# Agent Name\n\n## Purpose\n\n[2-3 paragraphs describing what this agent does, why it exists, and who it serves]\n\n## Skill Integration\n\n**Skill Location:** \\`../../domain-skill/skill-name/\\`\n\n### Python Tools\n\n1. **Tool Name**\n   - **Purpose:** What it does\n   - **Path:** \\`../../domain-skill/skill-name/scripts/tool.py\\`\n   - **Usage:** \\`python ../../domain-skill/skill-name/scripts/tool.py [args]\\`\n\n### Knowledge Bases\n\n1. **Reference Name**\n   - **Location:** \\`../../domain-skill/skill-name/references/file.md\\`\n   - **Content:** What's inside\n\n### Templates\n\n1. **Template Name**\n   - **Location:** \\`../../domain-skill/skill-name/assets/template.md\\`\n   - **Use Case:** When to use\n\n## Workflows\n\n### Workflow 1: [Name]\n\n**Goal:** Description\n\n**Steps:**\n1. Step 1\n2. Step 2\n3. Step 3\n\n**Expected Output:** Success criteria\n\n**Example:**\n\\`\\`\\`bash\npython ../../domain-skill/skill-name/scripts/tool.py input.txt\n\\`\\`\\`\n\n### Workflow 2: [Name]\n[Same structure]\n\n### Workflow 3: [Name]\n[Same structure]\n\n## Integration Examples\n\n[Concrete examples with actual commands and expected outputs]\n\n## Success Metrics\n\n- Metric 1: How to measure\n- Metric 2: How to measure\n- Metric 3: How to measure\n\n## Related Agents\n\n- [cs-related-agent](../<domain>/cs-related-agent.md) - How they relate\n\n## References\n\n- [Skill Documentation](../../domain-skill/skill-name/SKILL.md)\n- [Domain Roadmap](../../<domain-skill>/roadmap.md)\n```\n\n## Quality Standards\n\n### Agent Quality Checklist\n\nBefore committing an agent:\n\n- [ ] YAML frontmatter valid (no parsing errors)\n- [ ] All required fields present (name, description, skills, domain, model, tools)\n- [ ] cs-* prefix used for agent naming\n- [ ] Relative paths resolve correctly (../../ pattern)\n- [ ] Skill location documented and accessible\n- [ ] Python tools referenced with correct paths\n- [ ] At least 3 workflows documented\n- [ ] Integration examples provided and tested\n- [ ] Success metrics defined\n- [ ] Related agents cross-referenced\n\n### Testing Agent Integration\n\nTest these aspects:\n\n**1. Path Resolution**\n```bash\n# From agent directory\ncd agents/marketing/\nls ../marketing-skill/skills/content-creator/  # Should list contents\n```\n\n**2. Python Tool Execution**\n```bash\n# Create test input\necho \"Test content\" > test-input.txt\n\n# Execute tool\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py test-input.txt\n\n# Verify output\n```\n\n**3. Knowledge Base Access**\n```bash\n# Verify reference files exist\ncat ../marketing-skill/skills/content-creator/references/brand_guidelines.md\n```\n\n## Domain-Specific Guidelines\n\n### Marketing Agents (agents/marketing/)\n- Focus on content creation, SEO, demand generation\n- Reference: `../marketing-skill/`\n- Tools: brand_voice_analyzer.py, seo_optimizer.py\n\n### Product Agents (agents/product/)\n- Focus on prioritization, user research, agile workflows\n- Reference: `../product-team/`\n- Tools: rice_prioritizer.py, user_story_generator.py, okr_cascade_generator.py\n\n### C-Level Agents (agents/c-level/)\n- Focus on strategic decision-making\n- Reference: `../c-level-advisor/`\n- Tools: Strategic analysis and planning tools\n\n### Engineering Agents (agents/engineering/)\n- Focus on scaffolding, code quality, fullstack development\n- Reference: `engineering-team/`\n- Tools: project_scaffolder.py, code_quality_analyzer.py\n\n## Common Pitfalls\n\n**Avoid these mistakes:**\n\n❌ Hardcoding absolute paths\n❌ Skipping YAML frontmatter validation\n❌ Forgetting to test relative paths\n❌ Documenting workflows without examples\n❌ Creating agent dependencies (keep them independent)\n❌ Duplicating skill content in agent files\n❌ Using LLM calls instead of referencing Python tools\n\n## Next Steps\n\nAfter creating an agent:\n\n1. Test all relative paths resolve\n2. Execute all Python tools from agent context\n3. Verify all workflows with concrete examples\n4. Update agent catalog in main README.md\n5. Create GitHub issue for agent testing\n6. Commit with conventional commit message: `feat(agents): implement cs-agent-name`\n\n---\n\n**Last Updated:** June 10, 2026\n**Current:** 33 agents in this folder across 10 domain subfolders (93 agent files repo-wide)\n**Related:** See [main CLAUDE.md](../CLAUDE.md) for repository overview\n","isInternal":false,"tokens":3279,"sizeBytes":13994},{"name":"CLAUDE.md","path":"business-growth/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-growth/CLAUDE.md","title":"business-growth - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Business & Growth Skills - Claude Code Guidance\n\nThis guide covers the 5 production-ready business and growth skills and their Python automation tools.\n\n## Business & Growth Skills Overview\n\n**Available Skills:**\n1. **customer-success-manager/** - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)\n2. **sales-engineer/** - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)\n3. **revenue-operations/** - Pipeline analysis, forecast accuracy, GTM efficiency metrics (3 Python tools)\n\n**Total Tools:** 9 Python automation tools, 9 knowledge bases, 19+ templates\n\n## Python Automation Tools\n\n### Customer Success Manager Tools\n\n#### 1. Health Score Calculator (`customer-success-manager/scripts/health_score_calculator.py`)\n\n**Purpose:** Multi-dimensional customer health scoring with trend analysis\n\n**Features:**\n- Weighted scoring across 4 dimensions (usage, engagement, support, relationship)\n- Red/Yellow/Green classification with configurable thresholds\n- Trend analysis comparing current vs previous period\n- Segment-aware benchmarking (Enterprise/Mid-Market/SMB)\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json --format json\n```\n\n#### 2. Churn Risk Analyzer (`customer-success-manager/scripts/churn_risk_analyzer.py`)\n\n**Purpose:** Identify at-risk accounts with intervention recommendations\n\n**Features:**\n- Risk scoring based on behavioral signals\n- Warning signal detection and categorization\n- Tier-appropriate intervention playbooks\n- Urgency-based prioritization\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json --format json\n```\n\n#### 3. Expansion Opportunity Scorer (`customer-success-manager/scripts/expansion_opportunity_scorer.py`)\n\n**Purpose:** Identify upsell and cross-sell opportunities\n\n**Features:**\n- Adoption depth analysis across product modules\n- Whitespace mapping for unused features\n- Revenue opportunity estimation\n- Priority ranking by effort and impact\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json --format json\n```\n\n### Sales Engineer Tools\n\n#### 4. RFP Response Analyzer (`sales-engineer/scripts/rfp_response_analyzer.py`)\n\n**Purpose:** Score RFP/RFI coverage and identify gaps\n\n**Features:**\n- Requirement coverage scoring (Full/Partial/Planned/Gap)\n- Effort estimation per requirement\n- Gap identification with mitigation strategies\n- Overall bid/no-bid recommendation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json --format json\n```\n\n#### 5. Competitive Matrix Builder (`sales-engineer/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Generate feature comparison matrices and competitive positioning\n\n**Features:**\n- Feature-by-feature comparison matrix\n- Competitive scoring with weighted categories\n- Differentiator identification\n- Battlecard-ready output\n\n**Usage:**\n```bash\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json --format json\n```\n\n#### 6. POC Planner (`sales-engineer/scripts/poc_planner.py`)\n\n**Purpose:** Plan proof-of-concept engagements\n\n**Features:**\n- Timeline estimation based on scope\n- Resource allocation planning\n- Success criteria definition\n- Evaluation scorecard generation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/poc_planner.py poc_data.json\npython sales-engineer/scripts/poc_planner.py poc_data.json --format json\n```\n\n### Revenue Operations Tools\n\n#### 7. Pipeline Analyzer (`revenue-operations/scripts/pipeline_analyzer.py`)\n\n**Purpose:** Analyze sales pipeline health and velocity\n\n**Features:**\n- Coverage ratio calculation (pipeline/quota)\n- Stage conversion rate analysis\n- Sales velocity metrics (4-lever model)\n- Deal aging analysis\n\n**Usage:**\n```bash\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json --format json\n```\n\n#### 8. Forecast Accuracy Tracker (`revenue-operations/scripts/forecast_accuracy_tracker.py`)\n\n**Purpose:** Measure and improve forecast accuracy\n\n**Features:**\n- MAPE (Mean Absolute Percentage Error) calculation\n- Forecast bias detection (over/under-forecasting)\n- Period-over-period trend analysis\n- Category-level accuracy breakdown\n\n**Usage:**\n```bash\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json --format json\n```\n\n#### 9. GTM Efficiency Calculator (`revenue-operations/scripts/gtm_efficiency_calculator.py`)\n\n**Purpose:** Calculate go-to-market efficiency metrics\n\n**Features:**\n- Magic number calculation\n- LTV:CAC ratio analysis\n- CAC payback period\n- Burn multiple assessment\n- Industry benchmarking\n\n**Usage:**\n```bash\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json --format json\n```\n\n## Quality Standards\n\n**All business & growth Python tools must:**\n- Use standard library only (no external dependencies)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **Marketing:** Content creation, demand generation -> `../marketing-skill/`\n- **Product Team:** User research, feature prioritization -> `../product-team/`\n- **C-Level:** Strategic planning -> `../c-level-advisor/`\n- **Engineering:** Technical implementation -> `../engineering-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 5/5 business & growth skills production-ready\n**Total Tools:** 9 Python automation tools\n","isInternal":false,"tokens":1330,"sizeBytes":6279},{"name":"CLAUDE.md","path":"business-operations/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/CLAUDE.md","title":"business-operations - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Business Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `business-operations/`.\n\n## Purpose\n\nThe Business Operations domain ships skills that help **internal operators** (BizOps lead, COO direct reports, vendor management office, IT ops) run the company day-to-day. This is **not strategy** (that's `c-level-advisor/`) and **not external sales** (that's `business-growth/`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Job-to-be-done | `context: fork`? |\n|---|---|---|\n| `business-operations-skills` | Domain orchestrator — routes inquiries to the 6 sub-skills | YES |\n| `process-mapper` | BPMN-style process docs + bottleneck + cycle-time (Lean / TOC canon) | YES |\n| `vendor-management` | Vendor scoring + SLA + third-party risk (NIST SP 800-161 / ISO 27036) | YES |\n| `capacity-planner` | Erlang-C queueing math for ops teams (NOT engineering capacity) | NO |\n| `internal-comms` | ADKAR + Kotter 8-step change comms (NOT marketing) | NO |\n| `knowledge-ops` | SOPs + runbooks with 5W2H validation + KB hygiene (NOT personal PKM) | YES |\n| `procurement-optimizer` | UNSPSC-aligned spend categorization + supplier consolidation | NO |\n\n## Build pattern\n\nPath-B 11-file contract per skill (Matt Pocock-derived discipline preserved):\n\n```\nskill/\n├── SKILL.md                  # YAML frontmatter + workflow + forcing-question library\n├── scripts/                  # 3 stdlib-only Python CLI tools\n├── references/               # 3 ref docs, ≥ 7 cited sources each\n└── assets/                   # ≥ 1 user-customizable template\n```\n\n## Hard rules\n\n1. **Stdlib-only Python** — no `requests`, `pandas`, `numpy`. Just `argparse`, `json`, `sys`, `pathlib`, `statistics`, `dataclasses`, `enum`, `datetime`, `math`, `re`, `collections`.\n2. **Deterministic logic** — no LLM calls in scripts. Same input → same output. Erlang-C math implemented in log-space to avoid factorial overflow.\n3. **Industry tuning** — every scoring tool exposes `--profile {saas,services,manufacturing,healthcare,…}` for threshold calibration.\n4. **Matt Pocock grill discipline** — orchestrator routes via one-question-per-turn with a recommended answer + canon citation. Never bundles. Never auto-routes silently after a question. Every SKILL.md ships a \"Forcing-question library\" section with 5-7 cited canon-anchored questions.\n5. **Output is recommendation, not approval** — `vendor-management` never says \"replace this vendor\"; `procurement-optimizer` never auto-consolidates suppliers; the human always decides.\n\n## Agent + command pattern\n\n- `cs-bizops-orchestrator` — the persona agent. Voice: \"Where does the work spend most of its time waiting?\" (Theory of Constraints anchor).\n- `/cs-bizops <inquiry>` — top-level router.\n- `/cs-grill-bizops <plan>` — Matt-style docs-anchored grilling **before** routing.\n- `/cs-process-map`, `/cs-vendor-review`, `/cs-capacity-plan`, `/cs-internal-comms`, `/cs-knowledge-ops`, `/cs-procurement` — direct per-skill invocation.\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/*` (external sales motion) — BizOps is **internal**\n- ❌ Skills that overlap `c-level-advisor/coo-advisor` — that's strategic; BizOps is tactical\n- ❌ \"Process improvement consultant\" generic skills — every skill must answer a SPECIFIC question (e.g., \"where's the bottleneck?\", \"is this vendor delivering?\", \"are we sized to peak demand?\", not \"how can we improve operations?\")\n- ❌ Tools without `--profile` tuning — every score must be industry-tunable\n- ❌ Bundled questions in the orchestrator — Matt's rule: one at a time, with a recommended answer\n- ❌ Engineering-specific framing in capacity-planner — that's vpe-advisor's lane\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-me`, `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/coo-advisor`\n","isInternal":false,"tokens":992,"sizeBytes":3990},{"name":"CLAUDE.md","path":"c-level-advisor/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/CLAUDE.md","title":"c-level-advisor - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# C-Level Advisory Skills — Claude Code Guidance\n\nA complete virtual board of directors: 28 skills covering 10 executive roles, orchestration, cross-cutting capabilities, and culture & collaboration frameworks — plus the new **c-level-agents** plugin layer that surfaces 8 cs-* persona agents and 17 `/cs-*` slash commands on top of the skills.\n\n## Architecture\n\n```\n/cs-onboard setup (Founder Interview) → company-context.md\n                │\n        Chief of Staff (Router)\n                │\n    ┌───────────┼───────────┐\n    10 Roles    6 Cross-Cut  6 Culture\n    │           │            │\n    └───────────┼────────────┘\n                │\n        Executive Mentor (Critic)\n                │\n        Decision Logger (Two-Layer Memory)\n```\n\n## Skills Overview\n\n### C-Suite Roles (15)\n\n| Role | Folder | Reasoning Technique | Scripts |\n|------|--------|-------------------|---------|\n| **CEO** | `ceo-advisor/` | Tree of Thought | strategy_analyzer, financial_scenario_analyzer |\n| **CTO** | `cto-advisor/` | ReAct | tech_debt_analyzer, team_scaling_calculator |\n| **COO** | `coo-advisor/` | Step by Step | ops_efficiency_analyzer, okr_tracker |\n| **CPO** | `cpo-advisor/` | First Principles | pmf_scorer, portfolio_analyzer |\n| **CMO** | `cmo-advisor/` | Recursion of Thought | marketing_budget_modeler, growth_model_simulator |\n| **CFO** | `cfo-advisor/` | Chain of Thought | burn_rate_calculator, unit_economics_analyzer, fundraising_model |\n| **CRO** | `cro-advisor/` | Chain of Thought | revenue_forecast_model, churn_analyzer |\n| **CISO** | `ciso-advisor/` | Risk-Based | risk_quantifier, compliance_tracker |\n| **CHRO** | `chro-advisor/` | Empathy + Data | hiring_plan_modeler, comp_benchmarker |\n| **General Counsel** | `general-counsel-advisor/` | Risk-Based | contract_risk_scanner, term_sheet_analyzer |\n| **Chief Data Officer** | `chief-data-officer-advisor/` | Decision-Driven | ai_training_data_audit, data_product_strategy_picker, data_asset_valuator |\n| **Chief AI Officer** | `chief-ai-officer-advisor/` | Eval-Demanding | model_buildvsbuy_calculator, ai_risk_classifier, ai_cost_economics |\n| **Chief Customer Officer** | `chief-customer-officer-advisor/` | Retention-Obsessed | retention_decomposition_analyzer, customer_segmentation_designer, cs_coverage_calculator |\n| **VP of Engineering** ⭐ NEW v2.5.5 | `vpe-advisor/` | Throughput-First | delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer |\n| **Executive Mentor** | `executive-mentor/` | Adversarial | decision_matrix_scorer, stakeholder_mapper |\n\n### Orchestration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **C-Suite Onboard** | `cs-onboard/` | Founder interview → company-context.md |\n| **Chief of Staff** | `chief-of-staff/` | Routes questions, triggers board meetings |\n| **Board Meeting** | `board-meeting/` | 6-phase multi-agent deliberation |\n| **Decision Logger** | `decision-logger/` | Two-layer memory (raw + approved) |\n| **Agent Protocol** | `agent-protocol/` | Inter-agent invocation, loop prevention, quality loop |\n| **Context Engine** | `context-engine/` | Company context loading + anonymization |\n\n### Cross-Cutting Capabilities (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Board Deck Builder** | `board-deck-builder/` | Assembles board/investor updates |\n| **Scenario War Room** | `scenario-war-room/` | Multi-variable what-if modeling |\n| **Competitive Intel** | `competitive-intel/` | Systematic competitor tracking |\n| **Org Health Diagnostic** | `org-health-diagnostic/` | Cross-functional health scoring |\n| **M&A Playbook** | `ma-playbook/` | Acquiring or being acquired |\n| **International Expansion** | `intl-expansion/` | Market entry strategy |\n\n### Culture & Collaboration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Culture Architect** | `culture-architect/` | Build and operationalize culture |\n| **Company OS** | `company-os/` | EOS/Scaling Up operating system |\n| **Founder Coach** | `founder-coach/` | Founder development and growth |\n| **Strategic Alignment** | `strategic-alignment/` | Strategy cascade, silo detection |\n| **Change Management** | `change-management/` | ADKAR-based change rollout |\n| **Internal Narrative** | `internal-narrative/` | One story across all audiences |\n\n## c-level-agents Plugin (v1.0.0 — new in v2.5.0)\n\nA separate plugin at the repo's top-level `c-level-agents/` directory (moved out of `c-level-advisor/` in #949 so the two marketplace sources no longer overlap) that wraps the 10 C-roles with persona agents and slash commands. Founder-mode entry layer.\n\n### 13 cs-* Agents (in `../c-level-agents/agents/`)\n\n| Agent | Voice | Wraps Skill |\n|---|---|---|\n| cs-cfo-advisor | Numerate skeptic | cfo-advisor |\n| cs-cmo-advisor | Narrative-first | cmo-advisor |\n| cs-cro-advisor | Pipeline-paranoid | cro-advisor |\n| cs-cpo-advisor | JTBD-driven | cpo-advisor |\n| cs-coo-advisor | Execution OS | coo-advisor |\n| cs-chro-advisor | People-systems | chro-advisor |\n| cs-ciso-advisor | Risk-paranoid | ciso-advisor |\n| cs-chief-of-staff | Router & synthesist | chief-of-staff |\n| cs-general-counsel-advisor | Risk-paranoid (legal) | general-counsel-advisor |\n| cs-cdo-advisor | Decision-driven (data) | chief-data-officer-advisor |\n| cs-caio-advisor | Eval-demanding (AI) | chief-ai-officer-advisor |\n| cs-cco-advisor | Retention-obsessed (customer) | chief-customer-officer-advisor |\n| cs-vpe-advisor ⭐ NEW v2.5.5 | Throughput-first (engineering ops) | vpe-advisor |\n\nExisting `cs-ceo-advisor` and `cs-cto-advisor` live in `/agents/c-level/` and integrate with the same protocol.\n\n### 17 /cs-* Slash Commands (in `../c-level-agents/skills/`)\n\n**Forcing-question office hours (8):** `/c-level-agents:office-hours`, `/c-level-agents:cfo-review`, `/c-level-agents:cmo-review`, `/c-level-agents:cpo-review`, `/c-level-agents:cro-review`, `/c-level-agents:cto-review`, `/c-level-agents:ciso-review`, `/c-level-agents:gc-review`\n\n**Strategic sprint pipeline (5):** `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`\n\n**Meta + safety (4):** `/c-level-agents:founder-mode` (auto-router), `/cs-onboard` (founder interview), `/c-level-agents:cross-eval` (multi-model consensus), `/c-level-agents:freeze` (cooldown lock)\n\nSee [c-level-agents/README.md](../c-level-agents/README.md) for the full plugin guide and [c-level-agents/references/persona-voices.md](../c-level-agents/references/persona-voices.md) for voice specs.\n\n## Executive Mentor Slash Commands\n\nThe only skill with a `plugin.json` (namespace: `em`) because it has slash commands. Other skills are invoked by name through the Chief of Staff router or directly by the user. This is intentional — only add `plugin.json` when a skill has dedicated slash commands that need a namespace.\n\n| Command | Purpose |\n|---------|---------|\n| `/em:challenge` | Pre-mortem analysis of any plan |\n| `/em:board-prep` | Board meeting preparation |\n| `/em:hard-call` | Framework for hard decisions |\n| `/em:stress-test` | Stress-test any assumption |\n| `/em:postmortem` | Honest retrospective |\n\n## Key Design Decisions\n\n- **Two-layer memory:** Raw transcripts (reference) + approved decisions only (feeds future meetings). Prevents hallucinated consensus.\n- **Phase 2 isolation:** During board meetings, agents think independently before cross-examination.\n- **Internal Quality Loop:** Self-verify → peer-verify → critic pre-screen → present. No unverified output reaches the founder.\n- **Proactive triggers:** Every role has context-driven early warnings that surface issues without being asked.\n- **User Communication Standard:** Bottom Line → What → Why → How to Act → Your Decision. Results only, no process narration.\n\n## Python Tools (25 total)\n\nAll scripts are stdlib-only, CLI-first, with JSON output and embedded sample data.\n\n```bash\n# Examples\npython cfo-advisor/scripts/burn_rate_calculator.py\npython cro-advisor/scripts/churn_analyzer.py\npython cpo-advisor/scripts/pmf_scorer.py\npython org-health-diagnostic/scripts/health_scorer.py\npython strategic-alignment/scripts/alignment_checker.py\npython decision-logger/scripts/decision_tracker.py\n```\n\n## Integration with Other Domains\n\n| C-Level Role | Layers Above |\n|-------------|-------------|\n| CMO | marketing-skill/ (content, demand gen, ASO execution) |\n| CFO | finance/financial-analyst (spreadsheets, DCF) |\n| CRO | business-growth/ (revenue ops, sales engineering) |\n| CISO | ra-qm-team/ (ISO 27001 checklists, ISMS audits) |\n| CPO | product-team/ (PM toolkit, user stories, sprint planning) |\n\n---\n\n**Last Updated:** 2026-05-13\n**Skills Deployed:** 33 skills (15 roles incl. General Counsel, CDO, CAIO, CCO, and VPE + 5 mentor commands + 6 orchestration + 6 cross-cutting + 6 culture) + 21 /cs-* sub-skills in c-level-agents plugin\n**Agents:** 15 cs-* (cs-ceo, cs-cto in /agents/c-level/; 13 in ../c-level-agents/agents/ including new cs-vpe-advisor)\n**Python Tools:** 39 (stdlib-only) — +3 with vpe-advisor (delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer)\n**Reference Docs:** 73 (71 in skills + 2 in c-level-agents/references)\n","isInternal":false,"tokens":2455,"sizeBytes":9364},{"name":"CLAUDE.md","path":"CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/CLAUDE.md","title":"Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Project Purpose\n\nThis is a **comprehensive skills library** for Claude AI and Claude Code - reusable, production-ready skill packages that bundle domain expertise, best practices, analysis tools, and strategic frameworks. The repository provides modular skills that teams can download and use directly in their workflows.\n\n**Current Scope:** 398 production-ready skills across 20 domains with 766 Python automation tools, 877 reference guides, 123 agents (cs-* + 7 personas), and 157 slash commands, distributed as 104 marketplace plugins. Headline counters are derived from the tree by `scripts/derive_counters.py` (run with `--check` to verify the docs still match). **v2.11.2 (current)** vendors **engineering/skillopt-sleep/** — started as a verbatim, byte-for-byte copy of `microsoft/SkillOpt`'s `skillopt_sleep` engine (stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), then received 23 targeted patches after ten rounds of adversarial review (see `engineering/skillopt-sleep/README.md`'s numbered \"Deviations from upstream\" list, the authoritative source — re-apply all 23 on re-vendor). Gives a local agent a nightly \"sleep cycle\": read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget. The heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) was deliberately **not** vendored — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit. Attribution preserved in `.claude-plugin/authoring-notes.json` + `LICENSE` + `README.md` (MIT, © Microsoft Corporation / Yifan Yang), following the same verbatim-vendor pattern as `loop-library/`. **Unreleased (post-v2.11.2, PR #961 merged)** adds the **agent-launcher/** top-level domain — a plugin re-implementation of Anthropic's `launch-your-agent` reference skill (Apache-2.0; independent, not a fork) for building **Claude Managed Agents (CMA)** in the user's own account. Every session starts with a goal (`./my-agent/goal.json`, surfaced by an opt-in `AGENT_LAUNCHER_SESSION=1` SessionStart hook + `/cs-goal`); `loop_compiler.py` compiles that goal into a **bounded grade→iterate loop** (CMA `user.define_outcome` self-grading, `max_iterations` 1..20), a **recurring POSIX-cron scheduled-deployment loop**, or a **single-pass interview→stage→launch workflow**. 6 skills (orchestrator `context: fork` + interview + stage-launch + grade-iterate + run-without-you + wrap-up), 18 stdlib-only deterministic scaffolder tools (NO network/API calls — live launches emitted as BYOK curl that never prints the key), 4 agents, 8 `/cs-*` commands, opt-in hooks, 5 shared references, 4 assets; validators enforce CMA limits (≤20 skills/session, ≤8 memory stores, depth-1 multiagent, `max_iterations` ≤20, ≤1000 deployments/org). Distinct from `engineering/agent-harness` (generic bounded loop over any domain) and `engineering/write-a-skill` (authors Claude Code skills, not CMAs). **Unreleased (post-v2.11.2)** ships the **productivity coverage expansion** — public audit record `audit/productivity-2026-07/` (all 7 legacy skills scored, 24/24 scripts smoke-tested, coverage map vs the personal-productivity canon) + 3 gap-filling plugins, each with a cs-* agent, /cs-* commands, 3 stdlib scripts and 3 cited references: **weekly-review** (GTD loop; review-gate refuses COMPLETE while a mandatory GET CURRENT step is missing), **deep-work** (time-block planner refusing >4h deep demand, shallow-work budget auditor, focus-session logger), **meetings** (MEET/ASYNC/NOT-READY cost gate, outcome-required agenda builder, action-item extractor with ORPHAN/NO-DUE flags). **Unreleased (post-v2.11.1)** added **productivity/fable-goal** — converts a rambling description of a desired outcome into one polished, copy-paste `/goal` prompt for a fresh autonomous session (ported from `duncan-buildroom/freeskills`). **v2.11.1 (complete)** upgrades **product-team/** and **project-management/** into agent-harness domains: both prose routers rebuilt as `context: fork` orchestrators with deterministic goal routers (exit-code route/ask/refuse), a Jira MCP snapshot bridge (Kanban-Guide-2025 flow metrics + seeded Monte Carlo forecasts, verified end-to-end into velocity_analyzer), a delegation-governance loop gate (human owner / reviewer / machine-checkable acceptance / close refusal), a Torres continuous-discovery cadence tracker + Opportunity Solution Tree linter, cs-pm-orchestrator + cs-product-orchestrator agents, and /cs-pm|grill-pm|pm-loop + /cs-product|grill-product|product-loop commands — plus the public audit record `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria). **v2.9.0 (complete)** added the **research-ops/** top-level domain — enterprise Research Operations (orchestrator + clinical-research + research-finance + market-research + product-research), the managed counterpart to the academic research/ domain, with `context: fork` orchestration and a Matt Pocock \"Forcing-question library\" in every SKILL.md plus `/cs-grill-research-ops`. **v2.8.0 (complete)** added 2 new top-level domains — **business-operations/** (7 internal-ops skills: orchestrator + process-mapper + vendor-management + capacity-planner + internal-comms + knowledge-ops + procurement-optimizer) and **commercial/** (8 per-deal-economics skills: orchestrator + pricing-strategist + deal-desk + partnerships-architect + channel-economics + commercial-policy + rfp-responder + commercial-forecaster) — with orchestrator skills using `context: fork` for chaining, Matt Pocock docs-anchored \"Forcing-question library\" in every SKILL.md, plus `/cs-grill-bizops` and `/cs-grill-commercial`. **v2.8.2** adds a productivity-shaped `handoff` skill (sibling to engineering/handoff) inspired by Matt Pocock — first-run setup with configurable save location, redaction linter, SessionStart + SessionEnd hooks, fidelity self-check, `--refresh` flag. **v2.8.1** upgraded the engineering role-skills (senior-fullstack / senior-frontend / senior-backend) with karpathy-coder + Matt Pocock decision engines + per-role forcing questions. v2.7.3 ports `alirezarezvani/aeo-box` — AEO (Answer Engine Optimization) skill into marketing-skill/ + security-guidance PreToolUse hook into engineering/. v2.7.0 added 13 Path-B skills across 3 top-level domains (productivity, marketing, research). v2.6.0 added 4 Matt Pocock-derived productivity skills.\n\n**Key Distinction**: This is NOT a traditional application. It's a library of skill packages meant to be extracted and deployed by users into their own Claude workflows.\n\n## Maintainer-Local Folders (gitignored)\n\nThe following exist on the maintainer's disk but are excluded from the public GitHub tree so cloners only see production skill packages:\n\n- `documentation/` — sprint plans, strategy, implementation roadmaps\n- `eval-workspace/` — Tessl evaluation outputs\n- `megaprompts/` — pre-skill draft specs (Path-B source material)\n- `tests/` — pytest suite (run locally; not in CI)\n- `.autoresearch/` — autoresearch agent workspace\n- `AUDIT_REPORT.md` — internal audit snapshots\n\n**Distinct from the above:** the top-level `audit/` directory (e.g.\n`audit/newgen-2026-06/`) is an **intentional, public** audit record — rubric +\nper-domain reports with per-skill verification criteria that follow-up PRs use\nas acceptance gates. It is excluded from headline counters by\n`scripts/derive_counters.py`, but it is committed and visible to cloners.\n`AUDIT_REPORT.md` (gitignored, above) is the older internal-snapshot format.\n\nIn-repo references to paths under these folders (e.g. `documentation/implementation/...`) resolve locally for the maintainer but appear as dead links on GitHub. This is intentional.\n\n## Navigation Map\n\nThis repository uses **modular documentation**. For domain-specific guidance, see:\n\n| Domain | CLAUDE.md Location | Focus |\n|--------|-------------------|-------|\n| **Agent Development** | [agents/CLAUDE.md](agents/CLAUDE.md) | cs-* agent creation, YAML frontmatter, relative paths |\n| **Marketing Skills** | [marketing-skill/CLAUDE.md](marketing-skill/CLAUDE.md) | Content creation, SEO, ASO, demand gen, campaign analytics |\n| **Product Team** | [product-team/CLAUDE.md](product-team/CLAUDE.md) | RICE, OKRs, user stories, UX research, SaaS scaffolding |\n| **Engineering (Core)** | [engineering-team/CLAUDE.md](engineering-team/CLAUDE.md) | Fullstack, AI/ML, DevOps, security, data, QA tools |\n| **Engineering (POWERFUL)** | [engineering/](engineering/) | Agent design, RAG, MCP, CI/CD, database, observability |\n| **C-Level Advisory** | [c-level-advisor/CLAUDE.md](c-level-advisor/CLAUDE.md) | CEO/CTO strategic decision-making |\n| **Project Management** | [project-management/CLAUDE.md](project-management/CLAUDE.md) | Atlassian MCP, Jira/Confluence integration |\n| **RA/QM Compliance** | [ra-qm-team/CLAUDE.md](ra-qm-team/CLAUDE.md) | ISO 13485, MDR, FDA, GDPR, ISO 27001 compliance |\n| **Business & Growth** | [business-growth/CLAUDE.md](business-growth/CLAUDE.md) | Customer success, sales engineering, revenue operations |\n| **Finance** | [finance/CLAUDE.md](finance/CLAUDE.md) | Financial analysis, DCF valuation, budgeting, forecasting, SaaS metrics |\n| **Research Operations** | [research-ops/CLAUDE.md](research-ops/CLAUDE.md) | Clinical study design, R&D finance, market research, product research (enterprise counterpart to academic research/) |\n| **Markdown → HTML** | [markdown-html/CLAUDE.md](markdown-html/CLAUDE.md) | Markdown-to-interactive-HTML converter (orchestrator + design-system foundation; md-document/review/slides v2.10.1). Inspired by Shihipar's \"Claude Code HTML output\" essay |\n| **Agent Launcher** | [agent-launcher/CLAUDE.md](agent-launcher/CLAUDE.md) | Claude Managed Agent (CMA) launcher — session-goal orchestrator + interview / stage-launch / grade-iterate / run-without-you / wrap-up; deterministic BYOK-curl scaffolders; bounded grade→iterate + cron deployment loops. Re-implements anthropics/launch-your-agent (Apache-2.0) |\n| **Standards Library** | [standards/CLAUDE.md](standards/CLAUDE.md) | Communication, quality, git, security standards |\n| **Templates** | [templates/CLAUDE.md](templates/CLAUDE.md) | Template system usage |\n\n## Architecture Overview\n\n### Repository Structure\n\n```\nclaude-code-skills/\n├── .claude-plugin/            # Plugin registry (marketplace.json)\n├── agents/                    # 32 standalone agents (cs-* + 7 personas); 51+ cs-* agents repo-wide\n├── commands/                  # slash commands (changelog, tdd, saas-health, prd, code-to-prd, plugin-audit, sprint-plan, slo-design, etc.); 87+ repo-wide\n├── engineering-team/          # 51 core engineering skills + Playwright Pro + Self-Improving Agent + Security Suite\n├── engineering/               # 81 POWERFUL-tier advanced skills (incl. AgentHub, autoresearch-agent, self-eval, llm-wiki, tc-tracker, ship-gate, slo-architect, write-a-skill, caveman, grill-me, handoff, agent-harness)\n├── product-team/              # 17 product skills (incl. apple-hig-expert) + Python tools\n├── marketing-skill/           # 46 marketing skills (8 pods) + Python tools\n├── c-level-advisor/           # 66 C-level advisory skills (full C-suite + founder-mode agents + orchestration)\n├── project-management/        # 9 PM skills + bundled Atlassian Remote MCP (.mcp.json)\n├── ra-qm-team/                # 18 RA/QM compliance skills\n├── compliance-os/             # 9 compliance-OS skills\n├── business-growth/           # 5 business & growth skills + Python tools\n├── business-operations/       # 7 internal-ops skills (orchestrator + 6 sub-skills)\n├── commercial/                # 8 per-deal-economics skills (orchestrator + 7 sub-skills)\n├── finance/                   # 4 finance skills + Python tools\n├── research/                  # 8 academic research skills (orchestrator + 7 specialists)\n├── research-ops/              # 5 research-ops skills (orchestrator + clinical-research + research-finance + market-research + product-research)\n├── markdown-html/             # 2 markdown-to-HTML skills v2.10.0 foundation (orchestrator + design-system); md-document/review/slides land in v2.10.1\n├── agent-launcher/            # 6 CMA-launcher skills (session-goal orchestrator + 5 phase skills; 18 BYOK-curl scaffolder tools, opt-in SessionStart goal hook)\n├── eval-workspace/            # Skill evaluation results (Tessl)\n├── standards/                 # 5 standards library files\n├── templates/                 # Reusable templates\n├── docs/                      # MkDocs Material documentation site\n├── scripts/                   # Build scripts (docs generation)\n└── documentation/             # Implementation plans, sprints, delivery\n```\n\n### Skill Package Pattern\n\nEach skill follows this structure:\n```\nskill-name/\n├── SKILL.md              # Master documentation\n├── scripts/              # Python CLI tools (no ML/LLM calls)\n├── references/           # Expert knowledge bases\n└── assets/               # User templates\n```\n\n**Design Philosophy**: Skills are self-contained packages. Each includes executable tools (Python scripts), knowledge bases (markdown references), and user-facing templates. Teams can extract a skill folder and use it immediately.\n\n**Key Pattern**: Knowledge flows from `references/` → into `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\n## Git Workflow\n\n**Branch Strategy:** feature → dev → main (PR only)\n\n> **⛔ HARD RULE — PR TARGET IS ALWAYS `dev`, NEVER `main`.**\n> Every PR (human or AI-created) must use `--base dev`. Nothing merges into `main`\n> directly — `main` only receives periodic `dev → main` promotion PRs opened by the\n> maintainer. If you find a PR targeting `main`, retarget it to `dev` before review.\n> AI agents (Claude Code included): set the base branch explicitly when creating PRs;\n> never rely on the repository default branch.\n\n**Branch Protection Active:** Main branch requires PR approval. Direct pushes blocked.\n\n### Quick Start\n\n```bash\n# 1. Always start from dev\ngit checkout dev\ngit pull origin dev\n\n# 2. Create feature branch\ngit checkout -b feature/agents-{name}\n\n# 3. Work and commit (conventional commits)\nfeat(agents): implement cs-{agent-name}\nfix(tool): correct calculation logic\ndocs(workflow): update branch strategy\n\n# 4. Push and create PR to dev\ngit push origin feature/agents-{name}\ngh pr create --base dev --head feature/agents-{name}\n\n# 5. After approval, PR merges to dev\n# 6. Periodically, dev merges to main via PR\n```\n\n**Branch Protection Rules:**\n- ✅ Main: Requires PR approval, no direct push\n- ✅ Dev: Unprotected, but PRs recommended\n- ✅ All: Conventional commits enforced\n\nSee [documentation/WORKFLOW.md](documentation/WORKFLOW.md) for complete workflow guide.\nSee [standards/git/git-workflow-standards.md](standards/git/git-workflow-standards.md) for commit standards.\n\n## Development Environment\n\n**No build system or test frameworks** - intentional design choice for portability.\n\n**Python Scripts:**\n- Use standard library only (minimal dependencies)\n- CLI-first design for easy automation\n- Support both JSON and human-readable output\n- No ML/LLM calls (keeps skills portable and fast)\n\n**If adding dependencies:**\n- Keep scripts runnable with minimal setup (`pip install package` at most)\n- Document all dependencies in SKILL.md\n- Prefer standard library implementations\n\n## Current Version\n\n**Version:** v2.14.1 (audit fix release: all 104 plugins bumped so `claude plugin update` reaches existing installs, new version-bump gate G11, category-scoped Codex installer, `${CLAUDE_PLUGIN_ROOT}` script paths, productivity handoff renamed session-handoff. See CHANGELOG.md [2.14.1].)\n\n**Previously: v2.14.0** (audit skills release: agent-regression-evals, coding-agent-rollout and month-end-close plugins, open-source-first youtube-full, claude-coach plugin renamed to power-user-coach with a one-time reinstall. See CHANGELOG.md [2.14.0].)\n\n**Previously: v2.13.0** (October triage and quality-audit release: runnable command names, self-contained c-level-agents/compliance-os, hivemind as an opt-in plugin, six new skills from the community backlog. See CHANGELOG.md [2.13.0].)\n\n**Previously: v2.12.0** (consolidated release — 20 domains, 380 skills; full reported-issue triage sweep; first tag since v2.9.0. See CHANGELOG.md [2.12.0].)\n\n---\n\n**Previously: v2.11.2** (skillopt-sleep — vendored nightly self-improvement plugin from microsoft/SkillOpt)\n\n**v2.11.2 highlights — engineering/skillopt-sleep/:**\n\nVendors `engineering/skillopt-sleep/` — a byte-for-byte start from [microsoft/SkillOpt](https://github.com/microsoft/SkillOpt)'s `skillopt_sleep` engine (32 files, stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), following the same verbatim-vendor pattern as `loop-library/`. Gives a local agent a nightly gated self-improvement cycle: read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget.\n\n- **Deliberately not vendored:** the heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit.\n- **23 deviations from upstream (6 cosmetic, 17 safety/hardening)**, found across ten rounds of adversarial code review rather than assumed safe from the surface docs. The **numbered list in `engineering/skillopt-sleep/README.md`'s \"Deviations from upstream\" section is the single source of truth** — the plugin's `authoring-notes.json` `attribution.derivation_note` and this bullet are both summaries of it, kept in sync by hand; if any of the three ever disagree on the count again, README.md wins. Highlights: `redact_secrets()` now covers every artifact that goes live or persists — `proposed_SKILL.md`/`proposed_CLAUDE.md`, the cross-night task archive (`state.json`), `report.md`/`report.json` (previously only `diagnostics.json` was scrubbed, despite `report.md` being the file the SKILL.md's own workflow tells a human to read *first*), and — the gap that survived seven review rounds because every earlier fix was file-level — the CLI's own `cmd_run`/`cmd_harvest` console/`--json`/`--output` output, which read the same unredacted in-memory `Report`/`TaskRecord` objects and (via `scheduler.py`'s cron redirect) could leak straight into `cron.log`; the generated crontab line is fully `shlex.quote()`-d including the `extra` flags param, and `cron.log` itself is now `chmod 600` (previously uncovered by the state/staging chmod pass); `scheduler.py`'s per-project cron-line marker match is now anchored on end-of-line rather than a bare substring test, closing a real bug where scheduling/unscheduling one project could silently drop a sibling project's job whose path happened to be a prefix of it; the previously-dead `max_tokens_per_night` config key now sizes `dream_rollouts` down via the engine's own `plan_depth()` heuristic; a hardcoded internal Azure OpenAI backend (5 internal-looking endpoint hostnames + a Managed Identity client ID) was removed rather than carried forward; tool-shim names reachable via `--tasks-file` are now validated against a safe-identifier allowlist before use as a filename or shell text; `commands/skillopt-sleep.md` now tells the agent to confirm with the user before `schedule` (which installs a real crontab entry immediately, unlike every other action); every directory/file `state.py`/`staging.py` create is `chmod 0700`/`0600` rather than left at the world-readable process umask default.\n- One documented, opt-in exception to CLAUDE.md's \"no LLM calls in scripts\" anti-pattern (see that section) — `backend.py`'s `claude`/`codex` backends shell out to those CLIs only when a non-`mock` backend is explicitly selected.\n- Registered as its own installable marketplace plugin; **counters:** skills 358 → 359; tools 603 → 635; refs 732 (unchanged); commands 110 → 111; plugins 84 → 85 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**v2.14.0 — three audit-proposed skills (agent-regression-evals, coding-agent-rollout, month-end-close):**\n\nBuilt from the October quality audit's new-skill proposals, ranked by impact on teams. Each is a\nstandalone plugin mirrored into its domain bundle (`engineering/skills/`, `finance/skills/`), with\na cs-* agent, two `/cs-*` commands, stdlib scripts and three cited references; all three SKILL.md\nfiles pass the write-a-skill checklist. Evaluated with skill-creator (with-skill vs no-skill, one\nrealistic prompt each): 21/21 vs 17/21 assertions. The baseline's misses are why the skills exist:\nit called `bypassPermissions` in a project file \"YOLO mode for every engineer\" and `mcp__*` in\nallow \"all tools\", both of which Claude Code ignores, and it used a \"typical\" flux threshold\nwithout asking for the entity's policy.\n\n- **The evals changed the scripts, not just the scores.** Four fixes came from reading the runs:\n  the MCP inventory now scans `args` and `url` for credentials (a `postgresql://user:pass@`\n  string in `args` slipped past it); the reconciliation matcher names a carried-in\n  opening-balance difference before guessing transposition; the flux analyzer takes `--reviewer`\n  and blocks lines the reviewer owns; the flake detector warns when every failure lands in late\n  trials, the signature of state shared between trials.\n- **Rules these encode:** never compare single trials and never quarantine a critical case\n  (agent-regression-evals); policy that must hold for everyone goes in managed settings, not the\n  repo file (team-rollout); a reconciliation is a proof, a signature is not evidence of review\n  (PCAOB SAPA 11), and materiality thresholds are the entity's policy (month-end-close).\n- **Counters:** skills 392 → 398; tools 746 → 766; refs 859 → 877; agents 120 → 123;\n  commands 151 → 157; plugins 101 → 104 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/deep-learning-book (companion, not compilation):**\n\nNew `engineering/deep-learning-book/` plugin: a study companion for *Deep Learning* by\nGoodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org.\nRequested as \"convert this book into a skill\"; built as a **companion** instead, and the\nreasoning is the reusable part.\n\n- **Why not `book-to-skill`.** That skill's rights gate refuses a `shareable` package without\n  `public-domain` / `open-license` / `internal-docs` / `author-permission` — none applies to an\n  MIT Press title whose own site states the HTML-only format exists as a friction against\n  copying under the authors' contract — and its `rights_and_provenance.md` lists publishing a\n  compiled skill of a copyrighted book to a public marketplace under **Do not**. Its hard rule 1\n  also forbids scraping a book from the web, so the pipeline could not have run against a URL.\n  **The rule this sets:** when a user asks to convert a copyrighted work into a *shareable*\n  skill, build a companion that indexes and updates the source, not a compilation that\n  reproduces it; compile only when the gate clears, and keep the output local when it does not.\n  Recorded in `skills/deep-learning-book/references/rights_and_use.md`.\n- **What it is.** The compiled-skill *shape* (master SKILL.md at ~2.0k tokens with a chapter\n  index and topic index, `chapters/ch01..ch20`, glossary, patterns, cheatsheet) filled with\n  original synthesis — no passages, figures, or per-paragraph paraphrase — each chapter file\n  linking to the official free chapter. Passes `book_to_skill`'s own `book_skill_validator.py`\n  clean and every file is inside `token_budget_estimator.py`'s caps.\n- **The differentiator is the delta layer.** A static compilation freezes a source at its\n  publication date; this one dates it. Every chapter carries \"What changed after 2016\", and\n  `references/book_to_2026_delta.md` gives five corrections with primary citations and per-claim\n  confidence levels: double descent qualifying Ch 5's U-curve, AdamW splitting weight decay from\n  L2 (Ch 7 treats them as interchangeable), transformers displacing Ch 10's recurrence (keep the\n  gradient analysis, drop the architecture advice), diffusion growing out of Ch 14's denoising\n  autoencoders and Ch 18's score matching, and self-supervised learning vindicating Ch 15 while\n  replacing every method it names. Two claims are marked contested rather than propagated (batch\n  norm's \"internal covariate shift\" mechanism; the strong lottery-ticket form) and two named as\n  folklore. The stated rule: **the conflict is almost always in the recommendation, not the\n  analysis.**\n- **4 stdlib tools, each with a real refusal.** `reading_path_planner.py` (goal → prerequisite\n  closure over the book's actual dependency graph, ordered, priced in weeks; exit 3 for a goal\n  the book does not cover, naming what does; exit 4 with forcing questions when unroutable),\n  `training_diagnostics.py` (Ch 11's rules in priority order, so a NaN is never reported as\n  overfitting; exit 4 rather than diagnosing with no instruments), `capacity_planner.py`\n  (regularization ladder in cost order, with \"shrink the model\" pushed **last** in the\n  overparameterized regime per double descent; exit 4 on a val-below-train split),\n  `model_arithmetic.py` (params/FLOPs/activation memory per example for conv, linear, MHA and\n  LSTM/GRU stacks; exit 5 naming the layer whose shapes do not connect).\n- 4 references citing 7-8 sources each, 3 assets, `cs-deep-learning-tutor` agent, `/cs-deep-learning`\n  + `/cs-dl-reading-path` + `/cs-dl-diagnose`. **Counters:** skills 386 → 387; tools 723 → 727;\n  refs 838 → 842; agents 116 → 117; commands 146 → 149; plugins 97 → 98 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — marketing/linkedin (organic LinkedIn presence, platform rules in code):**\n\nNew `marketing/linkedin/` plugin answering [discussion #934](https://github.com/alirezarezvani/claude-skills/discussions/934), which asked for a strategic assistant for growing a LinkedIn presence organically rather than a post generator. Six skills (orchestrator + profile + strategy + content + engagement + analytics), 17 stdlib-only tools, 15 references, 2 agents, 8 `/cs-*` commands.\n\n- **The design constraint is the differentiator.** No LinkedIn credentials, no API calls, no scraping, nothing auto-sent — automated posting/connecting/commenting are prohibited by LinkedIn's User Agreement §8.2, and a restricted account ends a compounding asset. `linkedin_policy_gate.py` runs before any drafting and refuses seven request classes (automation, scraping, engagement pods, bulk messaging, fake identity, fabricated proof, named third-party automation platforms), each carrying the policy anchor **and a compliant substitute** — the gate never just says no. Orchestrator is `context: fork` with a deterministic five-lane router (route 0 / ask 2 / no-signal 3) and cross-lane prerequisites.\n- **Refusals are real, not warnings.** Cadence under 90 min/week returns a comment-only plan rather than a schedule that dies in week five; a newsletter whose six-month cost exceeds the budget is refused before the promise is made; an experiment needing more posts than a quarter allows is reported infeasible rather than quietly re-sized; the pattern miner refuses to test anything below 10 posts and reports `NOTHING_SURVIVED` as a finding.\n- **Evidence discipline — two popular claims corrected rather than propagated** (the `andreessen` precedent). (1) \"A personalised note triples connection acceptance (~45% vs ~15%)\" is not supported by the largest samples, which show acceptance close to identical either way (~26.4%); what a note actually moves is the **post-accept reply rate** (~5.4% → ~9.4%) — which is why `outreach_message_builder.py` refuses an ask in a first-touch note. (2) The ~19% in-body external-link reach reduction has **never been confirmed by LinkedIn as a penalty** and has a plausible dwell-time explanation, so it is a warning, not a block. Every reference carries per-claim confidence levels (🟢 LinkedIn-official / 🟡 third-party study / 🔴 folklore, named as folklore).\n- **Accessibility is a blocking lint finding, not a footnote.** Unicode pseudo-bold (the output of \"bold text generators\") fails the linter: screen readers announce those characters as mathematical symbols and LinkedIn search does not index them as words. Engagement bait is also blocking, per the Professional Community Policies. `pattern_miner.py` adds multiple-comparisons accounting and mirrored-candidate de-duplication that no comparable tool implements.\n- All six SKILL.md files are a full **6/6 PASS** on the write-a-skill checklist (binding for post-v2.6.0 skills). Every tool supports `--help`/`--sample`/`--output json` with typed exit codes. **Counters:** skills 380 → 386; tools 706 → 723; refs 823 → 838; agents 114 → 116; commands 138 → 146; plugins 96 → 97 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/spinning-up-deep-rl (the first book compiled by book-to-skill):**\n\nThe first knowledge-base plugin produced end-to-end by `engineering/book-to-skill`, from OpenAI's\n[Spinning Up in Deep RL](https://spinningup.openai.com/) (MIT, © 2018 OpenAI; primarily developed by\nJoshua Achiam). Source obtained by cloning `openai/spinningup` and compiling its `docs/` reStructuredText\ntree — 38 files, ~37k words, ~49K tokens — through the full pipeline: `extract_document.py --mode technical`\n→ analysis → 20 chapter files → glossary / patterns / cheatsheet → master `SKILL.md` → `book_skill_validator.py`\n→ `skill_plugin_emitter.py`. Validator passes clean **in `--strict` mode**; every file is inside budget\n(resident core 2,101 / 4,000 tokens; 20 chapters averaging ~1,256 tokens each, loaded on demand).\n\n- **Rights basis is `open-license`, not fair use.** The emitter's Step-11 gate refuses a shareable package\n  without one; MIT permits derivative distribution. Upstream's notice is reproduced in full in the plugin's\n  `LICENSE` alongside this package's own, and the README names the source, the author and the commit-era —\n  a sidecar JSON is not a license notice.\n- **Chapter structure follows the source's own `toctree`**, not a heading scan: user documentation (ch01-06),\n  Introduction to RL Parts 1-3 (ch07-09), resources — the researcher essay, key papers, exercises, benchmarks\n  (ch10-13), one chapter per algorithm in lineage order (ch14-19: VPG → TRPO → PPO, DDPG → TD3 → SAC), and the\n  logger/MPI/ExperimentGrid utilities (ch20).\n- **The cheatsheet carries what a glossary cannot**: the debug-turnaround threshold (under 5 minutes), the seed\n  minimums (3, ideally 10+), the benchmark network defaults that differ by algorithm family ((64,32)/tanh\n  on-policy vs (256,256)/relu off-policy), and Spinning Up's own **parity disclosure** — DDPG/TD3/SAC are\n  research-grade, VPG/TRPO/PPO are not, and the docs say to use OpenAI Baselines for those instead.\n- **One emitter defect found and fixed in the same change.** `skill_plugin_emitter.py` was writing its `source`\n  provenance block into `plugin.json`, which this repo's own `scripts/check_plugin_json.py` hard-fails\n  (issue #954 — Claude Code rejects the whole manifest on any unrecognized key). Its inline comment claimed\n  `source`/`attribution` were \"approved extension fields,\" which had been true and no longer was. The manifest\n  builder now emits spec fields only and a new `_authoring_notes()` writes `.claude-plugin/authoring-notes.json`.\n  Every future `book-to-skill` package gets a manifest that passes CI; the one emitted here was the first to\n  catch it.\n- **write-a-skill checklist: 4/6, and the two remaining are structural, not defects.** A compiled\n  knowledge base is not a hand-authored instruction skill. (2) \"SKILL.md under 100 lines\" conflicts\n  with the format's mandatory 20-row Chapter Index plus Topic Index; the binding budget here is\n  `book_skill_validator.py`'s 4,000-token cap, and the file sits at 2,101 — trimming to 100 lines\n  would delete exactly the navigation that `budget.over_cap` exists to protect. (3) \"no\n  time-sensitive info\" fires on \"January 2020\", which is a **provenance pin on a frozen source**\n  (Spinning Up's last update), not a staleness claim — removing it would make the skill less honest\n  about what it covers. (5) was a real gap and is fixed: the resident core now carries a worked\n  invocation block.\n- **No new Python tools** — a compiled knowledge base ships notes, not scripts, so the tools and references\n  counters are unchanged. **Counters:** skills 387 → 388; agents 117 → 118; commands 149 → 150; plugins\n  98 → 99, on top of `deep-learning-book` which merged into `dev` first (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/skill-doctor (grade the agent setup from real sessions):**\n\nRebuild of [warpdotdev/common-skills](https://github.com/warpdotdev/common-skills)' `skill-doctor` (MIT, © Denver Technologies, Inc., pinned at `f3b58c81`) as a full plugin. Harvests the last N days of local Claude Code / Codex sessions scoped to one repo, has the agent judge each condensed transcript against two verbatim-preserved rubrics (efficiency, code quality — labels only, closed tables), measures which installed skills actually fired, and proposes only the skill edits the evidence justifies — one local, self-contained HTML report; nothing is ever uploaded.\n\n- **22 numbered deviations from upstream** — `engineering/skill-doctor/README.md`'s list is authoritative; `authoring-notes.json` summarizes it. Headline additions: **`score_aggregator.py`, a deterministic gate with no upstream counterpart** — upstream let the scoring LLM average its own scores and assemble `report.json`; here labels map to scores via embedded tables mirroring the rubrics, scores for unsampled sessions are rejected as fabrications, reasons are length-checked, and a suggestion that cites no scored session id (or carries no diff) fails at exit 4. **Collector hardening:** always-on 12-pattern secret redaction before any transcript touches disk (no off switch; per-label counts land in the inventory and report), `chmod 0700/0600` artifacts, plugin-layout skill discovery (`*/skills/*/SKILL.md`), slash-command usage detection mined from `<command-name>` markers before the injection filter drops them. **Renderer replaced:** zero JavaScript (upstream embeds a 1,531-line prebuilt diff bundle + canvas share-image) — pure-CSS diff coloring, native `<details>` collapse, `prefers-color-scheme`, print-to-PDF; Warp branding and the `warp.dev/factories` CTA removed. **Dropped:** the Warp `warp.sqlite` source and its 392-line hand-rolled protobuf decoder (unauditable vendored binary-format code; Warp users should run upstream).\n- Preserved verbatim: both scoring rubrics (`scorers/`) and the skill-improvement filing bar (\"would a competent agent with the current instructions still fail this way?\"), now §1–§2 of `references/skill_edit_governance.md`. Zero suggestions clearing the bar is a valid, reportable success; proposed edits stay staged under the run's scratch dir until an explicit per-skill yes, and proposals for this repo's skills must pass write-a-skill's 6-item checklist.\n- 3 stdlib tools (all `--help`/`--sample`/`--output json`, typed exit codes; the pipeline smoke-tests end-to-end from `--sample` fixtures including a planted fake secret), 3 references citing 7 sources each, 3 handoff-shape assets, `cs-skill-doctor` agent, `/cs-skill-doctor` command. SKILL.md is a full 6/6 PASS on the write-a-skill checklist. Distinct from `skillopt-sleep` (automated nightly loop; this is one interactive graded pass), `write-a-skill` (authors from expertise; this improves from evidence), and self-eval (grades the current session; this grades a window). **Counters** (this branch merged `dev` after `agent-memory` landed, so these deltas sit on top of it): skills 378 → 379; tools 703 → 706; refs 820 → 823; agents 110 → 111; commands 130 → 131; plugins 95 → 96 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/book-to-skill (document → knowledge-base skill → plugin):**\n\nDerived from [virgiliojr94/book-to-skill](https://github.com/virgiliojr94/book-to-skill) (MIT). Compiles a book, documentation folder, or spec collection (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into an agent skill: a resident master `SKILL.md` (core frameworks + chapter index + topic index, capped at 4k tokens) plus on-demand `chapters/chNN-*.md`, `glossary.md`, `patterns.md`, and a decision `cheatsheet.md`. The agent reads the core, then one chapter — never the whole source again.\n\n- **Vendored close to verbatim:** the extraction library (`scripts/book_to_skill/` — config, exceptions, sanitize, dependencies, utils + 7 per-format parsers) keeps upstream's format chains, chapter detection across Latin/Roman/Chinese/Thai/Korean heading styles, invisible-Unicode (Trojan Source) sanitization and DOCX entity-expansion guard.\n- **26 numbered deviations from upstream** — the list in `engineering/book-to-skill/README.md` is authoritative; the plugin's `authoring-notes.json` `attribution.derivation_note` summarizes it. Highlights: (5) `--install-missing` now defaults to `report` — it prints the pip command and uses the stdlib fallback instead of upstream's TTY prompt that runs `pip install` into the caller's environment; (6) a **rights gate** — `skill_plugin_emitter.py --distribution shareable` refuses without `--rights` from `public-domain|open-license|internal-docs|author-permission`, with `fair-use` deliberately excluded (a defence, not a licence); (10) the two upstream validators merged into one four-family gate, adding **budget** and **index** families — dead chapter links, unindexed chapter files and dangling topic refs are the failure that silently breaks navigation while the skill still looks complete, and upstream had no check for it; (11) folded YAML scalars now parse, so a wrapped description no longer under-reports its length past the 1024-char cap; (12) `discovery_tax.py` → `token_budget_estimator.py` with the optional `tiktoken` path dropped, a post-flight budget audit added, and an explicit **worth-converting verdict** that says \"just read it\" when the source is under ~3× the compiled skill.\n- **Repo-native addition with no upstream counterpart — Step 11 / `/cs-book-to-plugin`:** upstream stops at a bare folder in `~/.claude/skills/`, which this library cannot route to. `skill_plugin_emitter.py` wraps a compiled skill as a full plugin package (manifest + `cs-<slug>` agent + `/cs-<slug>` command + README) and prints the marketplace entry; it never edits `marketplace.json` itself, and refuses to wrap a skill carrying validation errors.\n- **Cross-linked into `engineering/write-a-skill`** (\"author first, compile second\" — that skill authors from expertise in your head, this one compiles from a document on disk).\n- 4 stdlib-only tools (all `--help` / `--sample` / `--output json`), 5 references citing 7–8 sources each, 3 assets, `cs-book-to-skill` agent, 2 commands. **Counters:** skills 362 → 363; tools 644 → 663; refs 741 → 746; agents 102 → 103; commands 116 → 118; plugins 88 → 89 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/memory-engineering (engineer the forgetting, not the remembering):**\n\nNew `engineering/memory-engineering/` plugin. Fills a real gap: the repo had no\nskill for designing, pricing, or auditing an **agent memory system** (nearest\nneighbours `llm-wiki`, `skillopt-sleep`, `agent-harness` all bound something\nelse — a vault, a loop, a task plan). Framing synthesized from *\"How to be a\nMemory Engineer, from the perspective of Stanford, Microsoft, Anthropic and\nNvidia\"* by [@N01ennn](https://x.com/N01ennn/status/2083971749079581120), with\nevery quantitative claim re-cited to the primary source.\n\n- **4 stdlib scripts, one per lens.** `memory_cost_profiler.py` (construction vs\n  query split, **cost per correct answer**, amortization, co-location warning →\n  WRITE-PATH-DOMINANT / UNDER-AMORTIZED / NEEDS-SCHEDULING-FIX);\n  `memory_architecture_picker.py` (scores the paper's four paradigm families,\n  disqualifies on hard constraints, **names the cost the choice makes you pay**,\n  and exits 2 refusing to pick when the top two are within 0.06 — printing the\n  tie-breaking question instead); `memory_density_auditor.py` (classifies every\n  record **FACT / SKILL / LOG / PROSE**, near-duplicates via word-shingle\n  Jaccard, staleness + volatile-wording flags, knowledge density per 1k tokens;\n  runs on a real `--dir` **or** `--jsonl`); `forgetting_policy_linter.py` — **the\n  gate**: 8 checks with **F1** (explicit forgetting rule) and **F4**\n  (contradictions surfaced, never auto-merged) blocking at exit 4.\n- **Evidence discipline — two of the source article's paraphrases are corrected\n  in the references rather than propagated.** (1) The 47× energy figure is the\n  *spread across ten evaluated systems* (BM25 at 4,145 J/correct answer vs\n  A-Mem/MIRIX at 115–197 kJ, a \"28–47× premium\"), **not** \"two systems with\n  identical accuracy.\" (2) The 97% first-pass-error reduction is **Rakuten's\n  named vendor-published customer testimonial** (Yusuke Kaji, at 27% lower cost\n  / 34% lower latency), not a controlled study or a general property of the\n  approach. Every reference carries per-claim confidence levels, per the\n  `andreessen` precedent.\n- **Two classifier defects found and fixed during the build**, both of which\n  would have produced garbage on any real repo: markdown headings *inside*\n  fenced code blocks were splitting records (fixed by masking fences before\n  heading detection — dropped 258 phantom records to 107 on a real directory),\n  and short fragments trivially matched at 1.00 Jaccard (fixed with a\n  20-word floor for duplicate candidacy, eliminating 41 false-positive\n  \"duplicates\"). A third fix added the **PROSE** class: an earlier version\n  labeled every signal-less block LOG, firing LOG_HEAVY at 74% on a prose\n  documentation folder.\n- 4 references citing 7 sources each (arXiv:2606.06448 Stanford characterization;\n  MSR PlugMem; arXiv:2604.09852 MEMENTO + OpenMementos; Anthropic managed-agents\n  memory), 3 assets (seven-question forcing worksheet, combined example spec\n  consumed by all three spec-taking scripts, fillable F1–F8 policy template),\n  `cs-memory-engineer` agent, `/cs-memory-engineering` + `/cs-forgetting-audit`.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist (binding for\n  post-v2.6.0 skills). **Counters** (this branch merged `dev` after\n  `book-to-skill` landed, so these deltas sit on top of it): skills 363 → 364;\n  tools 663 → 667; refs 746 → 750; agents 103 → 104; commands 118 → 120;\n  plugins 89 → 90 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/agent-memory (promotion is earned, not asserted):**\n\nNew `engineering/agent-memory/` plugin. Concept derived from\n[TencentCloud/TencentDB-Agent-Memory](https://github.com/TencentCloud/TencentDB-Agent-Memory)\n(MIT) — **no upstream code included**. A four-tier ladder over Claude Code's own\nhooks: **L0** raw transcripts (never injected) → **L1** candidate atoms\n(gitignored, recalled on lexical relevance per prompt) → **L2** project context\n(committed after adopt, loaded every session start) → **L3** stable persona\n(always loaded). Tiers are distinguished by *injection policy*, not storage\nformat.\n\n- **Three upstream choices deliberately rejected**, each for a repo rule rather\n  than taste: the managed **database** (self-contained-package rule → one\n  append-oriented JSONL per project, capped at 500 atoms); a **proxy layer**\n  between agent and model (Claude Code already exposes the three interception\n  points — adding a proxy to obtain hooks the platform provides buys nothing and\n  adds a failure mode on the critical path); **LLM-based extraction** (the\n  no-LLM-in-scripts anti-pattern, and a model call cannot run in an async\n  teardown hook on a latency budget, nor reproduce its output from the\n  transcript, which would break \"cite, don't invent\").\n- **The gates are the design.** L1→L2 needs ≥3 distinct sessions spanning ≥2\n  distinct calendar days (`stated` = 2 sessions, day rule *still applies*;\n  `verified` = 1 observation and is the only day-exempt path); L2→L3 needs ≥2\n  distinct projects + 30 days. Thresholds are tuned toward refusing because the\n  error costs are asymmetric: under-promotion is self-healing (the user restates\n  it, which is itself an observation), over-promotion silently steers every\n  future session.\n- **Two gates refuse rather than guess.** `redacted: true` blocks promotion on\n  *any* volume of evidence — a **durability-independent barrier**, since a\n  secret restated over five sessions passes every recurrence gate; the flag\n  firing means the text was altered, and a lexical filter finding one secret is\n  not proof it found all of them, while L2/L3 are committed to git. An open\n  contradiction freezes both claims, found by **reverse join** (the newer atom\n  carries no flag) rather than a mirrored field.\n- **Three hooks, all fail-open.** `SessionStart` injects L2+L3 and marks\n  L2↔L3 collisions the project-scoped detector structurally cannot see;\n  `UserPromptSubmit` recalls on a **100 ms internal budget** against a monotonic\n  clock (the 1 s hook `timeout` is a wedged-process backstop, not the budget);\n  `SessionEnd` is async and captures → redacts → merges → detects → stages.\n  Measured: spawn+recall p50 ≈ 29 ms / p95 ≈ 31 ms, scoring itself 2–3 ms over\n  500 atoms — **interpreter cold start is the entire cost**, which is why the\n  in-script loop is not worth optimizing further.\n- **Nothing reaches a `CLAUDE.md` without a human.** Promotions land in\n  `.memory/staged/`; `/cs-memory adopt` walks them one at a time and backs both\n  files up first. `cs-memory-curator` refuses to adopt a redacted claim, an\n  unresolvable citation, or to resolve a contradiction itself.\n- 5 stdlib scripts + 3 hooks (`memory_core.py` is a deviation from `DESIGN.md`\n  §10's four-script tree — the **`README.md` deviations list is authoritative**,\n  and §10.1's stale `+6` tool estimate is corrected to `+8` there and in\n  `DESIGN.md`), 3 references citing 6–7 sources each with per-claim confidence\n  levels, a 69-check example validator, and `DESIGN.md` — ~1,400 lines, 44\n  review rounds, open decisions ranked by what they gate, including the one that\n  permits deleting the folder if rule-based recall proves too low.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist. **Counters:**\n  skills 377 → 378; tools 695 → 703 (+8: 5 scripts + 3 hooks); refs 817 → 820;\n  agents 109 → 110; commands 129 → 130; plugins 94 → 95 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.1) — productivity/fable-goal (ramble → autonomous /goal prompt):**\n\nImproved port of `duncan-buildroom/freeskills` `fable-goal` (informal \"free to use and modify\" grant — quoted, not relicensed; see the `attribution` block). Converts a rambling description of a desired outcome into one polished, copy-paste /goal prompt for a fresh autonomous session — the prompt is the deliverable, never the build. Adds over upstream: wrong-tool check, observable-done principle, six-slot extraction (deliverable/quantity/stakes/tools/quality/destination), per-medium verification defaults, six-point pre-delivery self-check, anti-pattern list + failure-mode catalog reference, second worked example in a non-web medium. Ships `goal_prompt_self_check.py` (stdlib runner for the mechanically checkable self-check subset — word count 150–350, goal line, autonomy directive, verification/freedom/destination language; exit 0/1, `--sample`, `--output json`), `/cs-fable-goal` command. Intentionally no `agents/`/`assets/` (single reasoning pass; see plugin README design notes). SKILL.md is a full PASS on the write-a-skill 6-item checklist. Counters: skills 357 → 358 (this PR also trues up pre-existing engineering-row drift 355 → 357); tools 602 → 603; refs 731 → 732; commands 109 → 110; plugins 83 → 84.\n\n---\n\n**Version:** v2.11.1 (pm/product agent-harness domains — deep audit + orchestrated loops for product-team & project-management)\n\n**v2.11.1 highlights — both PM/product routers become agent harnesses:**\n\nExtends the v2.11.0 agent-harness layer to the two people-process domains. Public audit record at `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria).\n\n- **project-management → delivery loop:** `pm-skills` rebuilt as a `context: fork` orchestrator with 3 stdlib tools — `pm_goal_router.py`\n\n<!-- [TRUNCATED AT 50KB] -->","isInternal":false,"tokens":12596,"sizeBytes":50649},{"name":"CLAUDE.md","path":"commercial/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/CLAUDE.md","title":"commercial - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Commercial — Domain Guide\n\nThis file provides domain-specific guidance for skills in `commercial/`.\n\n## Purpose\n\nThe Commercial domain ships skills that help **deal-desk operators, pricing teams, partner managers, RFP responders, and commercial forecasters** make per-deal and packaging decisions. This is **not strategy** (`c-level-advisor/cro-advisor`), **not sales execution** (`business-growth/sales-engineer`), and **not financial close** (`finance/financial-analysis`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `commercial-skills` | Domain orchestrator — routes to 7 sub-skills | YES |\n| `pricing-strategist` | Pricing model picker + Van Westendorp WTP + packaging | NO |\n| `deal-desk` | Per-deal scorer + discount approval routing + redline | NO |\n| `partnerships-architect` | 5-tier classifier + joint GTM + revshare modeler | NO |\n| `channel-economics` | Cost-to-serve + ROI + channel mix optimizer | NO |\n| `commercial-policy` | Data-backed discount matrix + exception flow + policy linter | NO |\n| `rfp-responder` | Shipley-method structured RFP/RFI/RFQ response | YES |\n| `commercial-forecaster` | 4Q-weighted bookings + cohort NRR/GRR + funnel-confidence | NO |\n\n## Hard rules (domain-specific)\n\n1. **Pricing outputs: model + range, never a specific number.** The human picks the number.\n2. **Deal outputs: score + named human approver. Never auto-approve.** Even at 0% discount.\n3. **Forecast outputs: surface the conversion assumption explicitly.** Pipeline math without disclosed assumptions is theatre.\n4. **RFP responses: never invent claims for GAP requirements.** Surface the gap; leadership decides bid/no-bid.\n5. **Partnership tiers: insist on independent-demand evidence for STRATEGIC.** Forrester: channel-led deals from your own pipeline cost more than direct.\n6. **Channel ROI requires retention differential.** CAC alone is meaningless without channel-level retention.\n7. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n8. **Industry tuning** via `--profile {saas,api,enterprise-software,marketplace,services,hardware}` on every scoring tool.\n9. **Matt Pocock grill discipline** — `/cs-grill-commercial` interrogates plan against SaaS pricing canon before any sub-skill runs.\n\n## Build pattern\n\nPath-B 11-file contract per skill. SKILL.md includes a \"Forcing-question library\" section that grills the user with cited canon (Skok, Tunguz, Bessemer, Ramanujam, ProfitWell, Winning by Design, Shipley, APMP).\n\n## Agent + command pattern\n\n- `cs-commercial-orchestrator` — margin-protective Commercial lead. Voice: \"What's the margin at full discount, AND what does next quarter's pipeline look like at the same terms?\"\n- `/cs-commercial <inquiry>` — top-level router\n- `/cs-grill-commercial <plan>` — Matt-style grilling first\n- `/cs-pricing-strategy`, `/cs-deal-review`, `/cs-partner-tier`, `/cs-channel-econ`, `/cs-commercial-policy`, `/cs-rfp-respond`, `/cs-commercial-forecast` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/contract-and-proposal-writer` (prose authoring) — Commercial is **decision logic + structured response**\n- ❌ Skills that overlap `c-level-advisor/cro-advisor` — that's strategic CRO judgment\n- ❌ Skills that recommend a specific price — recommend model + range\n- ❌ Skills that auto-approve deals — score + route to named human\n- ❌ Forecasting tools that hide conversion assumptions\n- ❌ RFP responder that invents claims — surface GAPs, leadership decides\n- ❌ Partnership classifier that grants STRATEGIC tier without independent-demand evidence\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/cro-advisor`\n- Sales execution complement: `business-growth/sales-engineer`\n","isInternal":false,"tokens":952,"sizeBytes":3931},{"name":"CLAUDE.md","path":"engineering-team/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/CLAUDE.md","title":"engineering-team - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Engineering Team Skills - Claude Code Guidance\n\nThis guide covers the 32 production-ready engineering skills and their Python automation tools.\n\n## Engineering Skills Overview\n\n**Core Engineering (16 skills):**\n- senior-architect, senior-frontend, senior-backend, senior-fullstack\n- senior-qa, senior-devops, senior-secops\n- code-reviewer, senior-security\n- aws-solution-architect, ms365-tenant-manager, google-workspace-cli, tdd-guide, tech-stack-evaluator, epic-design\n- **a11y-audit** — WCAG 2.2 accessibility audit and fix (a11y_scanner.py, contrast_checker.py)\n- **azure-cloud-architect** — Azure infrastructure design, ARM/Bicep templates, landing zones\n- **gcp-cloud-architect** — GCP infrastructure design, Terraform modules, cloud-native patterns\n- **security-pen-testing** — Penetration testing methodology, vulnerability assessment, exploit analysis\n- **snowflake-development** — Snowflake data warehouse development, SQL optimization, data pipeline patterns\n\n**Security (5 skills):**\n- **adversarial-reviewer** — Adversarial code review with 3 hostile personas (Saboteur, New Hire, Security Auditor)\n- **threat-detection** — Hypothesis-driven threat hunting, IOC sweep generation, z-score anomaly detection\n- **incident-response** — SEV1-SEV4 triage, 14-type incident taxonomy, NIST SP 800-61 forensics\n- **cloud-security** — IAM privilege escalation paths, S3 public access checks, security group detection\n- **red-team** — MITRE ATT&CK kill-chain planning, effort scoring, choke point identification\n- **ai-security** — ATLAS-mapped prompt injection detection, model inversion & data poisoning risk scoring\n\n**AI/ML/Data (5 skills):**\n- senior-data-scientist, senior-data-engineer, senior-ml-engineer\n- senior-prompt-engineer, senior-computer-vision\n\n**Total Tools:** 39+ Python automation tools\n\n## Core Engineering Tools\n\n### 1. Project Scaffolder (`senior-fullstack/scripts/project_scaffolder.py`)\n\n**Purpose:** Production-ready project scaffolding for modern stacks\n\n**Supported Stacks:**\n- Next.js + GraphQL + PostgreSQL\n- React + REST + MongoDB\n- Vue + GraphQL + MySQL\n- Express + TypeScript + PostgreSQL\n\n**Features:**\n- Docker Compose configuration\n- CI/CD pipeline (GitHub Actions)\n- Testing infrastructure (Jest, Cypress)\n- TypeScript + ESLint + Prettier\n- Database migrations\n\n**Usage:**\n```bash\n# Create new project\npython senior-fullstack/scripts/project_scaffolder.py my-project --type nextjs-graphql\n\n# Start services\ncd my-project && docker-compose up -d\n```\n\n### 2. Code Quality Analyzer (`senior-fullstack/scripts/code_quality_analyzer.py`)\n\n**Purpose:** Comprehensive code quality analysis and metrics\n\n**Features:**\n- Security vulnerability scanning\n- Performance issue detection\n- Test coverage assessment\n- Documentation quality\n- Dependency analysis\n- Actionable recommendations\n\n**Usage:**\n```bash\n# Analyze project\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project\n\n# JSON output\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project --json\n```\n\n**Output:**\n```\nCode Quality Report:\n- Overall Score: 85/100\n- Security: 90/100 (2 medium issues)\n- Performance: 80/100 (3 optimization opportunities)\n- Test Coverage: 75% (target: 80%)\n- Documentation: 88/100\n\nRecommendations:\n1. Update lodash to 4.17.21 (CVE-2020-8203)\n2. Optimize database queries in UserService\n3. Add integration tests for payment flow\n```\n\n### 3. Fullstack Scaffolder (`senior-fullstack/scripts/fullstack_scaffolder.py`)\n\n**Purpose:** Rapid fullstack application generation\n\n**Usage:**\n```bash\npython senior-fullstack/scripts/fullstack_scaffolder.py my-app --stack nextjs-graphql\n```\n\n## AI/ML/Data Tools\n\n### Data Science Tools\n\n**Experiment Designer** (`senior-data-scientist/scripts/experiment_designer.py`)\n- A/B test design\n- Statistical power analysis\n- Sample size calculation\n\n**Feature Engineering Pipeline** (`senior-data-scientist/scripts/feature_engineering_pipeline.py`)\n- Automated feature generation\n- Correlation analysis\n- Feature selection\n\n**Statistical Analyzer** (`senior-data-scientist/scripts/statistical_analyzer.py`)\n- Hypothesis testing\n- Causal inference\n- Regression analysis\n\n### Data Engineering Tools\n\n**Pipeline Orchestrator** (`senior-data-engineer/scripts/pipeline_orchestrator.py`)\n- Airflow DAG generation\n- Spark job templates\n- Data quality checks\n\n**Data Quality Validator** (`senior-data-engineer/scripts/data_quality_validator.py`)\n- Schema validation\n- Null check enforcement\n- Anomaly detection\n\n**ETL Generator** (`senior-data-engineer/scripts/etl_generator.py`)\n- Extract-Transform-Load workflows\n- CDC (Change Data Capture) patterns\n- Incremental loading\n\n### ML Engineering Tools\n\n**Model Deployment Pipeline** (`senior-ml-engineer/scripts/model_deployment_pipeline.py`)\n- Containerized model serving\n- REST API generation\n- Load balancing config\n\n**MLOps Setup Tool** (`senior-ml-engineer/scripts/mlops_setup_tool.py`)\n- MLflow configuration\n- Model versioning\n- Drift monitoring\n\n**LLM Integration Builder** (`senior-ml-engineer/scripts/llm_integration_builder.py`)\n- OpenAI API integration\n- Prompt templates\n- Response parsing\n\n### Prompt Engineering Tools\n\n**Prompt Optimizer** (`senior-prompt-engineer/scripts/prompt_optimizer.py`)\n- Prompt A/B testing\n- Token optimization\n- Few-shot example generation\n\n**RAG System Builder** (`senior-prompt-engineer/scripts/rag_system_builder.py`)\n- Vector database setup\n- Embedding generation\n- Retrieval strategies\n\n**Agent Orchestrator** (`senior-prompt-engineer/scripts/agent_orchestrator.py`)\n- Multi-agent workflows\n- Tool calling patterns\n- State management\n\n### Computer Vision Tools\n\n**Vision Model Trainer** (`senior-computer-vision/scripts/vision_model_trainer.py`)\n- Object detection (YOLO, Faster R-CNN)\n- Semantic segmentation\n- Transfer learning\n\n**Inference Optimizer** (`senior-computer-vision/scripts/inference_optimizer.py`)\n- Model quantization\n- TensorRT optimization\n- ONNX export\n\n**Video Processor** (`senior-computer-vision/scripts/video_processor.py`)\n- Frame extraction\n- Object tracking\n- Scene detection\n\n## Tech Stack Patterns\n\n### Frontend (React/Next.js)\n- TypeScript strict mode\n- Component-driven architecture\n- Atomic design patterns\n- State management (Zustand/Jotai)\n- Testing (Jest + React Testing Library)\n\n### Backend (Node.js/Express)\n- Clean architecture\n- Dependency injection\n- Repository pattern\n- Domain-driven design\n- Testing (Jest + Supertest)\n\n### Fullstack Integration\n- GraphQL for API layer\n- REST for external services\n- WebSocket for real-time\n- Redis for caching\n- PostgreSQL for persistence\n\n## Development Workflows\n\n### Workflow 1: New Project Setup\n\n```bash\n# 1. Scaffold project\npython senior-fullstack/scripts/project_scaffolder.py my-app --type nextjs-graphql\n\n# 2. Start services\ncd my-app && docker-compose up -d\n\n# 3. Run migrations\nnpm run migrate\n\n# 4. Start development\nnpm run dev\n```\n\n### Workflow 2: Code Quality Check\n\n```bash\n# 1. Analyze codebase\npython senior-fullstack/scripts/code_quality_analyzer.py ./\n\n# 2. Fix security issues\nnpm audit fix\n\n# 3. Run tests\nnpm test\n\n# 4. Build production\nnpm run build\n```\n\n### Workflow 3: ML Model Deployment\n\n```bash\n# 1. Setup MLOps infrastructure\npython senior-ml-engineer/scripts/mlops_setup_tool.py\n\n# 2. Deploy model\npython senior-ml-engineer/scripts/model_deployment_pipeline.py model.pkl\n\n# 3. Monitor performance\n# Check MLflow dashboard\n```\n\n## Quality Standards\n\n**All engineering tools must:**\n- Support modern tech stacks (Next.js, React, Vue, Express)\n- Generate production-ready code\n- Include testing infrastructure\n- Provide Docker configurations\n- Support CI/CD integration\n\n## Integration Patterns\n\n### GitHub Actions CI/CD\n\nAll scaffolders generate GitHub Actions workflows:\n```yaml\n.github/workflows/\n├── test.yml          # Run tests on PR\n├── build.yml         # Build and lint\n└── deploy.yml        # Deploy to production\n```\n\n### Docker Compose\n\nMulti-service development environment:\n```yaml\nservices:\n  - app (Next.js)\n  - api (GraphQL)\n  - db (PostgreSQL)\n  - redis (Cache)\n```\n\n## Additional Resources\n\n- **Quick Start:** `START_HERE.md`\n- **Team Structure:** `TEAM_STRUCTURE_GUIDE.md`\n- **Engineering Roadmap:** `engineering_skills_roadmap.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 32 engineering skills production-ready\n**Total Tools:** 39+ Python automation tools across core + AI/ML/Data + epic-design + a11y\n\n---\n\n## epic-design\n\nBuild cinematic 2.5D interactive websites with scroll storytelling, parallax depth, and premium animations. Includes asset inspection pipeline, 45+ techniques across 8 categories, and accessibility built-in.\n\n**Key features:**\n- 6-layer depth system with automatic parallax\n- 13 text animation techniques, 9 scroll patterns\n- Asset inspection with background judgment rules\n- Python tool for automated image analysis\n- WCAG 2.1 AA compliant (reduced-motion)\n\n**Use for:** Product launches, portfolio sites, SaaS marketing pages, event sites, Apple-style animations\n\n**Live demo:** [epic-design-showcase.vercel.app](https://epic-design-showcase.vercel.app/)\n","isInternal":false,"tokens":2182,"sizeBytes":9195},{"name":"CLAUDE.md","path":"finance/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/CLAUDE.md","title":"finance - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Finance Skills - Claude Code Guidance\n\nThis guide covers 5 production-ready finance skills and their Python automation tools.\n\n## Finance Skills Overview\n\n**Available Skills:**\n1. **financial-analyst/** - Financial statement analysis, ratio analysis, DCF valuation, budgeting, forecasting (4 Python tools)\n2. **saas-metrics-coach/** - SaaS financial health: ARR, MRR, churn, CAC, LTV, NRR, Quick Ratio, 12-month projections (3 Python tools)\n3. **business-investment-advisor/** - Investment thesis evaluation, ROI modeling, capital allocation guidance\n4. **passive-deal-screener/** - Screens private deals from the passive LP perspective: equity syndications, preferred equity, hard money / bridge funds, and private credit, pasted from any source. Stress-tests returns against public benchmarks plus an illiquidity premium, converts the fee stack to gross-to-net drag, and surfaces red flags, missing disclosures, and GP questions with bad-answer signals (2 Python tools: `fee_drag_calculator.py`, `benchmark_comparator.py`)\n5. **month-end-close/** - Runs the accounting close: close calendar on its critical path with owner and reviewer checks, reconciliation proof with aging and transposition hints, and a flux gate that refuses boilerplate explanations (3 Python tools: `close_calendar_planner.py`, `reconciliation_matcher.py`, `flux_analyzer.py`; standalone plugin with `/cs-month-end-close` and `/cs-flux-review`)\n\n**Total Tools:** 12 Python automation tools; 5 knowledge bases and 6 templates across skills 1-3, plus 5 reference files in passive-deal-screener\n\n**Commands:** 2 (`/financial-health`, `/saas-health`)\n\n## Python Automation Tools\n\n### 1. Ratio Calculator (`financial-analyst/scripts/ratio_calculator.py`)\n\n**Purpose:** Calculate and interpret financial ratios from statement data\n\n**Features:**\n- Profitability ratios (ROE, ROA, Gross/Operating/Net Margin)\n- Liquidity ratios (Current, Quick, Cash)\n- Leverage ratios (Debt-to-Equity, Interest Coverage, DSCR)\n- Efficiency ratios (Asset/Inventory/Receivables Turnover, DSO)\n- Valuation ratios (P/E, P/B, P/S, EV/EBITDA, PEG)\n- Built-in interpretation and benchmarking\n\n**Usage:**\n```bash\npython financial-analyst/scripts/ratio_calculator.py financial_data.json\npython financial-analyst/scripts/ratio_calculator.py financial_data.json --format json\n```\n\n### 2. DCF Valuation (`financial-analyst/scripts/dcf_valuation.py`)\n\n**Purpose:** Discounted Cash Flow enterprise and equity valuation\n\n**Features:**\n- Revenue and cash flow projections\n- WACC calculation (CAPM-based)\n- Terminal value (perpetuity growth and exit multiple methods)\n- Enterprise and equity value derivation\n- Two-way sensitivity analysis\n- No external dependencies (uses math/statistics)\n\n**Usage:**\n```bash\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json --format json\n```\n\n### 3. Budget Variance Analyzer (`financial-analyst/scripts/budget_variance_analyzer.py`)\n\n**Purpose:** Analyze actual vs budget vs prior year performance\n\n**Features:**\n- Variance calculation (actual vs budget, actual vs prior year)\n- Materiality threshold filtering\n- Favorable/unfavorable classification\n- Department and category breakdown\n\n**Usage:**\n```bash\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json --format json\n```\n\n### 4. Forecast Builder (`financial-analyst/scripts/forecast_builder.py`)\n\n**Purpose:** Driver-based revenue forecasting and cash flow projection\n\n**Features:**\n- Driver-based revenue forecast model\n- 13-week cash flow projection\n- Scenario modeling (base/bull/bear)\n- Trend analysis from historical data\n\n**Usage:**\n```bash\npython financial-analyst/scripts/forecast_builder.py forecast_data.json\npython financial-analyst/scripts/forecast_builder.py forecast_data.json --format json\n```\n\n## Quality Standards\n\n**All finance Python tools must:**\n- Use standard library only (math, statistics, json, argparse)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **C-Level:** Strategic financial decision-making -> `../c-level-advisor/`\n- **Business & Growth:** Revenue operations, sales metrics -> `../business-growth/`\n- **Product Team:** Budget allocation, RICE scoring -> `../product-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 4 finance skills documented here (domain totals: `scripts/derive_counters.py`)\n**Total Tools:** 12 Python automation tools\n**Commands:** /financial-health, /saas-health\n","isInternal":false,"tokens":1091,"sizeBytes":4764},{"name":"CLAUDE.md","path":"markdown-html/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/CLAUDE.md","title":"markdown-html - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Markdown → HTML — Domain Guide\n\nThis file provides domain-specific guidance for skills in `markdown-html/`.\n\n## Purpose\n\nThe markdown-html domain converts long markdown files (the actual artifacts produced inside a Claude project — specs, reports, RFCs, PR writeups, slide outlines) into world-class, single-file, lightly-interactive HTML. Inspired by Thariq Shihipar's argument (Medium, 2026): markdown collapses past ~100 lines because it lacks visual machinery for density and lateral navigation; HTML restores both.\n\nIt is **not** an interactive prompt-tuning playground (`/playground` plugin owns that lane), **not** a landing-page generator (`marketing/landing/`), **not** a session-handoff brief generator (`engineering/handoff/` + `productivity/handoff/`), and **not** a static-site generator (single-file artifacts, not site indices).\n\n## Skills (v2.10.3 — domain complete)\n\n| Skill | Purpose | `context: fork`? | Status |\n|---|---|---|---|\n| `markdown-html-orchestrator` | Domain orchestrator — classifies doctype, gates on threshold + onboarding, routes to converter | YES | ✓ live |\n| `design-system` | One-time onboarding wizard + WCAG-AA-validated brand palette (12 CSS custom properties) + shared config | NO | ✓ live |\n| `md-document` | Long-form converter: sticky TOC, collapsibles, search, code-copy, scrollspy | NO | ✓ live |\n| `md-review` | Code-review converter: 2-col diff + severity-tagged margin annotations + jump-nav | NO | ✓ live |\n| `md-slides` | Slide-deck converter: arrow-key nav + presenter mode + print-to-PDF | NO | ✓ live |\n\nAll three converters are shipped. Routing always targets the converter skill's scripts — never hand-render HTML inline.\n\n## Hard rules (domain-specific)\n\n1. **Refuses input < 100 lines.** Markdown still wins below the threshold (Shihipar). Every converter (and the orchestrator) prints the line count and a \"keep as markdown\" recommendation.\n2. **Refuses without design-system onboarding.** The orchestrator's `route_explainer.py` checks `config_loader.setup_completed()`. If false, refuse and surface onboarding (`python3 markdown-html/skills/design-system/scripts/onboard.py`).\n3. **WCAG AA enforced.** `brand_palette_validator.py` rejects color combinations whose body-text contrast falls below 4.5:1 on bg. Link contrast is iteratively walked to 4.5:1 by adjusting luminance.\n4. **Single-file HTML output.** All CSS and JS inline. The only permitted external CDN entries are Google Fonts CSS and Prism.js. No bundler, no build step, no JS framework runtimes (vanilla JS + IntersectionObserver only).\n5. **Never silently chain converters.** \"Convert this markdown AND make slides from it AND a code review\" is three operations. Pick one, finish, ask before chaining.\n6. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n7. **Customization in use, not decoration.** Every converter MUST render differently when the user changes `design_style`, `brand.primary`, `code_theme`, or `toc.behavior`. If a token doesn't change behavior, it doesn't belong in the schema.\n8. **Onboarding-first.** The orchestrator surfaces onboarding the moment it detects a missing `setup_completed_at`. Don't render with placeholder defaults silently.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scripts + 3 references (each citing 5-7 sources) + (optional) 1 asset template. The orchestrator skill ships `context: fork` in its frontmatter. The `design-system` skill is the shared brand owner — every converter imports its `config_loader.py` via `sys.path.insert(0, .../design-system/scripts)`.\n\nEach SKILL.md ships a \"Forcing-question library\" section (cited-canon grilling, one question at a time) — same discipline as `research-ops`, `commercial`, and `business-operations`.\n\n## Agent + command pattern\n\n- `cs-markdown-html-orchestrator` — density-first markdown-to-HTML converter. Voice: \"What decision does this HTML drive — is the reader skimming, deciding, or presenting?\"\n- `/cs-markdown-html <path>.md` — top-level router (classifier + route + recommend)\n- `/cs-grill-markdown-html <path>.md` — Matt-Pocock-style 5-question grill before conversion\n- `/cs-design-system` — surface the onboarding wizard\n\nPer-sub-skill commands (all live):\n- `/cs-md-document`, `/cs-md-review`, `/cs-md-slides`\n\n## Anti-patterns (domain-level)\n\n- ❌ Converting markdown < 100 lines — markdown still wins. Refuse + cite Shihipar.\n- ❌ Skipping onboarding because \"the user wants it done now.\" Surface onboarding — it's 60 seconds.\n- ❌ Multi-file output (separate CSS / JS / image folders). Single file or nothing.\n- ❌ External JS framework runtimes (React, Vue, Svelte, Alpine). Vanilla JS + IntersectionObserver only.\n- ❌ Silently overwriting existing output files. `output_path_resolver.py` suffixes `-2`, `-3`, … by default.\n- ❌ Setting `MARKDOWN_HTML_NO_CONFIG=1` silently for an interactive user.\n- ❌ Decorative tokens — every token must change at least one converter's output.\n- ❌ Inventing brand colors when the user hasn't onboarded.\n- ❌ A skill that overlaps Anthropic's official Playground plugin (sliders/knobs/prompt-copy-back).\n- ❌ A skill that overlaps `marketing/landing/` (landing-page generation from scratch).\n\n## Customization pipeline\n\n1. User runs `python3 markdown-html/skills/design-system/scripts/onboard.py`.\n2. Wizard validates brand colors via `brand_palette_validator.py`, derives 12-token palette.\n3. Result written to `~/.config/markdown-html/design-system.json` (or `./.markdown-html/design-system.json` with `--scope project`).\n4. Every converter sub-skill imports `config_loader.py` and calls `load_config()` to read project > global > defaults.\n5. Each converter's renderer emits a single `<style>` block with `:root { --md-bg: ...; }` for all 12 tokens, then references those variables throughout the CSS.\n6. Result: change a single field via `--set brand.primary=#FF6B35` → next conversion re-renders with the new brand.\n\n## References\n\n- Spec: Thariq Shihipar — *Claude Code HTML output: Why Markdown Lost and How to Switch* (Medium, 2026)\n- Forking pattern source: `research-ops/skills/research-ops-skills/SKILL.md` (`context: fork`, two-signal routing)\n- Onboarding pattern source: `research-ops/skills/clinical-research/scripts/onboard.py` + `config_loader.py`\n- Brand palette math source: `marketing/landing/skills/landing/scripts/brand_palette_validator.py`\n- Matt Pocock grill-with-docs: `engineering/grill-with-docs`\n- Single-file HTML discipline source: `marketing/landing/skills/landing/SKILL.md`\n","isInternal":false,"tokens":1578,"sizeBytes":6580},{"name":"CLAUDE.md","path":"marketing-skill/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/CLAUDE.md","title":"marketing-skill - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Marketing Skills — Agent Instructions\n\n## For All Agents (Claude Code, Codex CLI, OpenClaw)\n\nThis directory contains 44 marketing skills organized into 8 specialist pods (Content, SEO + AEO, CRO, Channels, Growth, Intelligence, Sales enablement, Marketing ops).\n\n### How to Use\n\n1. **Start with routing:** Read `marketing-ops/SKILL.md` — it has a routing matrix that maps user requests to the right skill.\n2. **Check context:** If `.claude/product-marketing-context.md` exists, read it first. It has brand voice, personas, and competitive landscape.\n3. **Load ONE skill:** Read only the specialist SKILL.md you need. Never bulk-load.\n\n### Skill Map\n\n- `marketing-context/` — Run first to capture brand context\n- `marketing-ops/` — Router (read this to know where to go)\n- `content-production/` — Write content (blog posts, articles, guides)\n- `content-strategy/` — Plan what content to create\n- `aeo/` — Answer Engine Optimization (E-E-A-T scoring, schema injection, citation tracking across LLMs)\n- `seo-audit/` — Traditional SEO audit\n- `page-cro/` — Conversion rate optimization\n- `pricing-strategy/` — Pricing and packaging\n- `content-humanizer/` — Fix AI-sounding content\n- `x-twitter-growth/` — X/Twitter audience growth, tweet composing, competitor analysis\n\n### Python Tools\n\n59 scripts, all stdlib-only. Run directly:\n```bash\npython3 <skill>/scripts/<tool>.py [args]\n```\nNo pip install needed. Scripts include embedded samples for demo mode (run with no args).\n\n### Anti-Patterns\n\n❌ Don't read all 44 SKILL.md files\n❌ Don't skip `.claude/product-marketing-context.md` if it exists\n❌ Don't use content-creator (deprecated → use content-production)\n❌ Don't install pip packages for Python tools\n","isInternal":false,"tokens":431,"sizeBytes":1738},{"name":"CLAUDE.md","path":"product-team/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/CLAUDE.md","title":"product-team - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Product Team Skills - Claude Code Guidance\n\nThis guide covers the 17 production-ready product management skills (13 bundled incl. the orchestrator + 4 standalone plugins) and their Python automation tools.\n\n## Orchestrator & Discovery Loop (product-skills)\n\n`skills/product-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a product goal deterministically across all 16 lanes (exit 0 route / 2 ask / 3 no signal)\npython3 skills/product-skills/scripts/product_goal_router.py --text \"help me prioritize features\"\n\n# Score the continuous-discovery cadence (Torres weekly habit; refuses on < 2 interviews)\npython3 skills/product-skills/scripts/discovery_cadence_tracker.py --input discovery_log.json\n\n# Lint the Opportunity Solution Tree (exit 2 blocks the tree from driving a roadmap)\npython3 skills/product-skills/scripts/ost_linter.py --input ost.json\n```\n\nCommands: `/cs-product` (router) · `/cs-grill-product` (canon-cited grilling) ·\n`/cs-product-loop` (the discovery loop). Agent: `cs-product-orchestrator`. Build-scale\ngoals compile through `engineering/agent-harness` with the `product-team.json` manifest.\nHard rules: no roadmap cites a tree that fails the linter; single-participant claims are\nanecdotes; AI features ship with eval specs (see\n`skills/product-skills/references/ai_product_evals.md`).\n\n## Product Skills Overview\n\n**Available Skills:**\n0. **product-skills/** - Domain orchestrator (`context: fork`) + continuous-discovery loop (3 tools: goal router, cadence tracker, OST linter)\n1. **product-manager-toolkit/** - RICE prioritization, customer interview analysis (2 tools)\n2. **agile-product-owner/** - User story generation, sprint planning (1 tool)\n3. **product-strategist/** - OKR cascade, strategic planning (1 tool)\n4. **ux-researcher-designer/** - Persona generation, user research (1 tool)\n5. **ui-design-system/** - Design token generation, component systems (1 tool)\n6. **competitive-teardown/** - Competitive matrix building, gap analysis (1 tool)\n7. **landing-page-generator/** - Landing page scaffolding (1 tool)\n8. **saas-scaffolder/** - SaaS project bootstrapping (1 tool)\n9. **product-analytics/** - KPI design, retention/cohort/funnel analysis (1 tool)\n10. **experiment-designer/** - Experiment design and sample size planning (1 tool)\n11. **product-discovery/** - Discovery frameworks and assumption mapping (1 tool)\n12. **roadmap-communicator/** - Roadmap communication and changelog generation (1 tool)\n13. **code-to-prd/** - Reverse-engineer any codebase into PRD (2 tools: codebase_analyzer, prd_scaffolder)\n14. **research-summarizer/** - Research synthesis and summarization (1 tool)\n15. **apple-hig-expert/** - Apple Human Interface Guidelines compliance and design (1 tool: hig_checker)\n16. **spec-to-repo/** - Convert a spec document into a scaffolded repository\n\n**Total Tools:** 22 Python automation tools\n\n**Agents:** 6 (cs-product-orchestrator, cs-product-manager, cs-agile-product-owner, cs-product-strategist, cs-ux-researcher, cs-product-analyst)\n\n**Slash Commands:** 11 (/cs-product, /cs-grill-product, /cs-product-loop, /rice, /okr, /persona, /user-story, /competitive-matrix, /prd, /sprint-plan, /code-to-prd)\n\n## Python Automation Tools\n\n### 1. RICE Prioritizer (`product-manager-toolkit/scripts/rice_prioritizer.py`)\n\n**Purpose:** RICE framework implementation for feature prioritization\n\n**Formula:** (Reach × Impact × Confidence) / Effort\n\n**Features:**\n- Portfolio analysis (quick wins vs big bets)\n- Quarterly roadmap generation\n- Capacity planning (story points or dev days)\n- CSV input/output for Jira/Linear integration\n- JSON export for dashboards\n\n**Usage:**\n```bash\n# Basic prioritization\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv\n\n# With capacity planning\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n\n# JSON output\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json\n```\n\n**CSV Format:**\n```csv\nfeature,reach,impact,confidence,effort\nUser Dashboard,500,3,0.8,5\nAPI Rate Limiting,1000,2,0.9,3\nDark Mode,300,1,1.0,2\n```\n\n### 2. Customer Interview Analyzer (`product-manager-toolkit/scripts/customer_interview_analyzer.py`)\n\n**Purpose:** NLP-based interview transcript analysis\n\n**Features:**\n- Pain point extraction with severity scoring\n- Feature request identification\n- Sentiment analysis\n- Theme extraction\n- Jobs-to-be-done pattern recognition\n\n**Usage:**\n```bash\n# Analyze transcript\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt\n\n# JSON output\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt json\n```\n\n### 3. User Story Generator (`agile-product-owner/scripts/user_story_generator.py`)\n\n**Purpose:** INVEST-compliant user story generation\n\n**Features:**\n- Sprint planning with capacity allocation\n- Epic breakdown into deliverable stories\n- Acceptance criteria generation\n- Story point estimation\n- Priority scoring\n\n**Usage:**\n```bash\n# Interactive mode\npython agile-product-owner/scripts/user_story_generator.py\n\n# Sprint planning (30 story points)\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### 4. OKR Cascade Generator (`product-strategist/scripts/okr_cascade_generator.py`)\n\n**Purpose:** Automated OKR hierarchy (company → product → team)\n\n**Features:**\n- Alignment scoring (vertical and horizontal)\n- Strategy templates (growth, retention, revenue, innovation)\n- Key result tracking\n- Progress visualization\n\n**Usage:**\n```bash\n# Growth strategy OKRs\npython product-strategist/scripts/okr_cascade_generator.py growth\n\n# Retention strategy\npython product-strategist/scripts/okr_cascade_generator.py retention\n```\n\n### 5. Persona Generator (`ux-researcher-designer/scripts/persona_generator.py`)\n\n**Purpose:** Data-driven persona creation from user research\n\n**Usage:**\n```bash\npython ux-researcher-designer/scripts/persona_generator.py\npython ux-researcher-designer/scripts/persona_generator.py --output json\n```\n\n### 6. Design Token Generator (`ui-design-system/scripts/design_token_generator.py`)\n\n**Purpose:** Complete design token system from brand color\n\n**Usage:**\n```bash\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern scss\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern json\n```\n\n### 7. Competitive Matrix Builder (`competitive-teardown/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Weighted competitive scoring with gap analysis\n\n**Usage:**\n```bash\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### 8. Landing Page Scaffolder (`landing-page-generator/scripts/landing_page_scaffolder.py`)\n\n**Purpose:** Generate production-ready landing pages as Next.js/React TSX components with Tailwind CSS (default) or plain HTML.\n\n**Features:**\n- TSX output (default): Next.js 14+ App Router components with Tailwind classes\n- 4 design styles: `dark-saas`, `clean-minimal`, `bold-startup`, `enterprise`\n- 7 section generators: nav, hero, features, testimonials, pricing, CTA, footer\n- Copy frameworks: PAS, AIDA, BAB\n\n**Usage:**\n```bash\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format html\n```\n\n### 9. Project Bootstrapper (`saas-scaffolder/scripts/project_bootstrapper.py`)\n\n**Purpose:** SaaS project scaffolding with auth, billing, and API setup\n\n**Usage:**\n```bash\npython saas-scaffolder/scripts/project_bootstrapper.py project_config.json\n```\n\n### 10. Metrics Calculator (`product-analytics/scripts/metrics_calculator.py`)\n\n**Purpose:** Product analytics — retention, cohort, and funnel analysis\n\n**Features:**\n- Retention curve analysis from event data\n- Funnel conversion tracking with stage-by-stage drop-off\n- Cohort grouping and comparison\n\n**Usage:**\n```bash\n# Retention analysis\npython product-analytics/scripts/metrics_calculator.py retention events.csv\n\n# Funnel analysis\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\n\n# KPI summary\npython product-analytics/scripts/metrics_calculator.py kpi metrics.csv --json\n```\n\n### 11. Sample Size Calculator (`experiment-designer/scripts/sample_size_calculator.py`)\n\n**Purpose:** Statistical sample size planning for A/B tests and experiments\n\n**Features:**\n- Minimum detectable effect (MDE) calculation\n- Absolute and relative effect size modes\n- Power analysis with configurable alpha/beta\n\n**Usage:**\n```bash\n# Absolute MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n\n# Relative MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.15 --mde-type relative\n\n# Custom power/significance\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --alpha 0.01 --power 0.9\n```\n\n### 12. Assumption Mapper (`product-discovery/scripts/assumption_mapper.py`)\n\n**Purpose:** Map and prioritize product assumptions for discovery validation\n\n**Features:**\n- Risk × uncertainty scoring for prioritization\n- CSV input with structured assumption fields\n- Categorization by assumption type (desirability, viability, feasibility, usability)\n\n**Usage:**\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\npython product-discovery/scripts/assumption_mapper.py assumptions.csv --json\n```\n\n### 13. Changelog Generator (`roadmap-communicator/scripts/changelog_generator.py`)\n\n**Purpose:** Generate structured changelogs from git commit history\n\n**Note:** Requires `git` on PATH — must be run inside a git repository.\n\n**Usage:**\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to v2.0.0 --json\n```\n\n## Product Workflows\n\n### Workflow 1: Feature Prioritization to Sprint Execution\n\n```bash\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### Workflow 2: Strategy to Team-Level OKRs\n\n```bash\npython product-strategist/scripts/okr_cascade_generator.py growth --json > okrs.json\n```\n\n### Workflow 3: Research to Persona Artifacts\n\n```bash\npython ux-researcher-designer/scripts/persona_generator.py json > personas.json\n```\n\n### Workflow 4: Brand-Aligned Landing Page\n\n```bash\npython ../marketing-skill/content-production/scripts/brand_voice_analyzer.py website_copy.txt --format json > voice.json\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### Workflow 5: Product Analytics and Experimentation\n\n```bash\npython product-analytics/scripts/metrics_calculator.py retention events.csv\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n```\n\n### Workflow 6: Discovery and Opportunity Validation\n\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\n```\n\n### Workflow 7: Roadmap and Release Communication\n\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\n```\n\n## Quality Standards\n\n**All product Python tools must:**\n- CLI-first design for automation\n- Support both interactive and batch modes\n- JSON output for tool integration\n- Standard library only (minimal dependencies)\n- Actionable recommendations\n\n## Additional Resources\n\n- **Main Documentation:** `../CLAUDE.md`\n- **Marketing Brand Voice:** `../marketing-skill/content-production/scripts/brand_voice_analyzer.py`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 17/17 product skills production-ready (product-skills is now a fork-orchestrator + discovery loop)\n**Total Tools:** 22 Python automation tools\n**Agents:** 6 | **Commands:** 11\n","isInternal":false,"tokens":2877,"sizeBytes":12305},{"name":"CLAUDE.md","path":"project-management/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/CLAUDE.md","title":"project-management - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Project Management Skills - Claude Code Guidance\n\nThis guide covers the 9 production-ready project management skills, 15 Python automation tools, and bundled Atlassian Remote MCP integration (`.mcp.json` ships with the plugin — OAuth handled by Claude Code, no env vars required).\n\n## PM Skills Overview\n\n**Available Skills:**\n1. **pm-skills/** - Domain orchestrator (`context: fork`) + agentic delivery loop (3 scripts: goal router, Jira snapshot bridge, delivery loop gate)\n2. **senior-pm/** - Portfolio health, risk analysis, resource planning (3 scripts)\n3. **scrum-master/** - Sprint health, velocity forecasting, retrospectives (3 scripts)\n4. **jira-expert/** - JQL building, workflow validation (2 scripts)\n5. **confluence-expert/** - Space structure, content auditing (2 scripts)\n6. **atlassian-admin/** - Permission auditing (1 script)\n7. **atlassian-templates/** - Template scaffolding (1 script)\n8. **meeting-analyzer/** - Meeting transcript behavioral analysis (prompt-driven; scripts are follow-up work)\n9. **team-communications/** - 3P updates, newsletters, FAQs (reference-driven)\n\n**Total Tools:** 15 Python automation tools\n**Agents:** 2 — cs-pm-orchestrator (routing + delivery loop) and cs-project-manager (legacy per-skill orchestration)\n**Slash Commands:** 6 (/cs-pm, /cs-grill-pm, /cs-pm-loop, /sprint-health, /project-health, /retro)\n**Key Feature:** Atlassian MCP Server integration for direct Jira/Confluence operations\n\n## Orchestrator & Delivery Loop (pm-skills)\n\n`skills/pm-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a PM goal deterministically (exit 0 route / 2 ask / 3 no signal)\npython3 skills/pm-skills/scripts/pm_goal_router.py --text \"our sprints feel off\"\n\n# Bridge a saved searchJiraIssuesUsingJql result into analyzable inputs\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to flow --forecast 20\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to sprint > sprint_data.json\npython3 skills/scrum-master/scripts/velocity_analyzer.py sprint_data.json\n\n# Gate agent-executed delivery loops (G1 human owner … G6 exhausted budget = escalation)\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode plan   # exit 2 = blocked\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode close  # exit 4 = refused\n```\n\nMulti-task goals compile through the repo-wide harness\n(`engineering/agent-harness` with the `project-management.json` manifest). Hard rules:\nagents contribute, humans own; forecasts are Monte Carlo ranges, never dates; exhausted\nbudgets escalate — never reported as success. The five reusable PM loops (sprint-flow,\nhealth, retro-action, RAID-hygiene, comms) are documented in\n`skills/pm-skills/references/pm_loop_playbook.md`.\n\n## Atlassian MCP Integration\n\n**Purpose:** Direct integration with Jira and Confluence via Model Context Protocol (MCP)\n\n**Canonical tool list:** [references/atlassian-mcp-tools.md](references/atlassian-mcp-tools.md) — the single source of truth for real tool names. Never invent tool names; if a capability isn't in that list (project creation, sprint management, field configuration, automation rules, space creation, …), it is NOT available via MCP — use the Atlassian web UI or REST API.\n\n**Capabilities (real tools, camelCase):**\n- Jira issues: `createJiraIssue`, `getJiraIssue`, `editJiraIssue`, `searchJiraIssuesUsingJql`, `transitionJiraIssue`, `addCommentToJiraIssue`, `createIssueLink`\n- Confluence pages: `createConfluencePage`, `getConfluencePage`, `updateConfluencePage`, `searchConfluenceUsingCql`, `getConfluencePageDescendants`\n- Discovery: `getAccessibleAtlassianResources` (get `cloudId` first), `getVisibleJiraProjects`, `getConfluenceSpaces`\n\n**Setup:** Bundled `.mcp.json` registers the `atlassian` SSE server; tools surface as `mcp__atlassian__<toolName>`.\n\n**Usage Pattern:**\n```\n# Jira: create an issue (call getAccessibleAtlassianResources first to obtain cloudId)\nmcp__atlassian__createJiraIssue (cloudId, projectKey=\"PROJ\", issueTypeName=\"Story\", summary=\"New feature\")\n\n# Confluence: create a page (body must be storage-format XHTML or ADF, not wiki markup)\nmcp__atlassian__createConfluencePage (cloudId, space, title=\"Sprint Retrospective\", body=<storage-format XHTML>)\n```\n\n**Not available via MCP** (use web UI/REST API): project creation, sprints, boards, filters, space creation, page deletion, labels, field/workflow/permission configuration, user provisioning, automation rules.\n\n## Skill-Specific Guidance\n\n### Senior PM (`senior-pm/`)\n\n**Focus:** Project planning, stakeholder management, risk mitigation\n\n**Key Workflows:**\n- Project charter creation\n- Stakeholder analysis and communication plans\n- Risk register maintenance\n- Status reporting and escalation\n\n### Scrum Master (`scrum-master/`)\n\n**Focus:** Agile ceremonies, team coaching, impediment removal\n\n**Key Workflows:**\n- Sprint planning facilitation\n- Daily standup coordination\n- Sprint retrospectives\n- Backlog refinement\n\n### Jira Expert (`jira-expert/`)\n\n**Focus:** Jira configuration, custom workflows, automation rules\n\n**Scripts:**\n- `scripts/jql_query_builder.py` — Pattern-matching JQL builder from natural language\n- `scripts/workflow_validator.py` — Validates workflow definitions for anti-patterns\n\n**Key Workflows:**\n- Workflow customization\n- Automation rule creation\n- Board configuration\n- JQL query optimization\n\n### Confluence Expert (`confluence-expert/`)\n\n**Focus:** Documentation strategy, templates, knowledge management\n\n**Scripts:**\n- `scripts/space_structure_generator.py` — Generates space hierarchy from team description\n- `scripts/content_audit_analyzer.py` — Analyzes page inventory for stale/orphaned content\n\n**Key Workflows:**\n- Space architecture design\n- Template library creation\n- Documentation standards\n- Search optimization\n\n### Atlassian Admin (`atlassian-admin/`)\n\n**Focus:** Suite administration, user management, integrations\n\n**Scripts:**\n- `scripts/permission_audit_tool.py` — Analyzes permission schemes for security gaps\n\n**Key Workflows:**\n- User provisioning and permissions\n- SSO/SAML configuration\n- App marketplace management\n- Performance monitoring\n\n### Atlassian Templates (`atlassian-templates/`)\n\n**Focus:** Ready-to-use templates for common PM tasks\n\n**Scripts:**\n- `scripts/template_scaffolder.py` — Generates Confluence storage-format XHTML templates\n\n**Available Templates:**\n- Sprint planning template\n- Retrospective formats (Start-Stop-Continue, 4Ls, Mad-Sad-Glad)\n- Project charter\n- Risk register\n- Decision log\n\n## Integration Patterns\n\n### Pattern 1: Sprint Planning\n\n```bash\n# 1. Create the sprint in the Jira board UI (sprint creation is NOT available via MCP —\n#    use Jira Software UI or REST /rest/agile/1.0/sprint)\n\n# 2. Generate user stories (product-team integration)\npython ../product-team/agile-product-owner/scripts/user_story_generator.py sprint 30\n\n# 3. Import stories to Jira via MCP: one mcp__atlassian__createJiraIssue call per story\n#    (cloudId, projectKey, issueTypeName=\"Story\", summary, description)\n```\n\n### Pattern 2: Documentation Workflow\n\n```bash\n# 1. Scaffold storage-format XHTML, then create the Confluence page via MCP\npython skills/atlassian-templates/scripts/template_scaffolder.py meeting-notes\n#    → pass the emitted markup as the body of mcp__atlassian__createConfluencePage\n\n# 2. Link the page to a Jira issue: paste the page URL into the issue via\n#    mcp__atlassian__editJiraIssue or as a comment via mcp__atlassian__addCommentToJiraIssue\n#    (read existing links with mcp__atlassian__getJiraIssueRemoteIssueLinks)\n```\n\n## Python Automation Tools\n\n### New Scripts (Phase 2)\n\n```bash\n# JQL from natural language\npython jira-expert/scripts/jql_query_builder.py \"high priority bugs assigned to me\"\n\n# Validate Jira workflow\npython jira-expert/scripts/workflow_validator.py workflow.json\n\n# Generate Confluence space structure\npython confluence-expert/scripts/space_structure_generator.py team_info.json\n\n# Audit Confluence content health\npython confluence-expert/scripts/content_audit_analyzer.py pages.json\n\n# Audit Atlassian permissions\npython atlassian-admin/scripts/permission_audit_tool.py permissions.json\n\n# Scaffold Confluence templates\npython atlassian-templates/scripts/template_scaffolder.py meeting-notes\n```\n\n## Additional Resources\n\n- **Installation Guide:** `INSTALLATION_GUIDE.txt`\n- **Implementation Summary:** `IMPLEMENTATION_SUMMARY.md`\n- **Real-World Scenario:** `REAL_WORLD_SCENARIO.md`\n- **PM Overview:** `README.md`\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 9/9 PM skills production-ready (pm-skills is now a fork-orchestrator + delivery loop)\n**Total Tools:** 15 Python automation tools\n**Agents:** cs-pm-orchestrator, cs-project-manager | **Commands:** 6\n**Integration:** Atlassian Remote MCP Server (bundled via `.mcp.json`) for Jira/Confluence automation\n","isInternal":false,"tokens":2148,"sizeBytes":9019},{"name":"CLAUDE.md","path":"ra-qm-team/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/CLAUDE.md","title":"ra-qm-team - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Regulatory Affairs & Quality Management Skills - Claude Code Guidance\n\nThis guide covers the 14 production-ready RA/QM compliance skills for HealthTech/MedTech companies.\n\n## RA/QM Skills Overview\n\n**Strategic Leadership (2 skills):**\n- regulatory-affairs-head - RA strategy, regulatory intelligence, authority relations\n- quality-manager-qmr - QMS oversight, management review, quality culture\n\n**Quality Systems (3 skills):**\n- quality-manager-qms-iso13485 - ISO 13485 compliance, process management\n- capa-officer - CAPA system management, root cause analysis\n- quality-documentation-manager - DHF, DMR, DHR management\n\n**Risk & Security (2 skills):**\n- risk-management-specialist - ISO 14971 compliance, risk analysis\n- information-security-manager-iso27001 - ISO 27001, data protection, ISMS\n\n**Regulatory Specialists (2 skills):**\n- mdr-745-specialist - EU MDR 2017/745 compliance, technical documentation\n- fda-consultant-specialist - FDA 510(k), PMA, QSR compliance\n\n**Audit & Compliance (4 skills):**\n- qms-audit-expert - Internal audits, ISO 13485 certification\n- isms-audit-expert - ISO 27001 audits, security assessments\n- gdpr-dsgvo-expert - GDPR/DSGVO compliance, data privacy\n- soc2-compliance - SOC 2 Type I/II compliance, trust service criteria, audit readiness\n\n**Total:** 14 specialized compliance skills for medical device industry\n\n## Compliance Frameworks\n\n### ISO 13485 (Medical Device Quality Management)\n\n**Managed by:** quality-manager-qms-iso13485, qms-audit-expert\n\n**Key Areas:**\n- Management responsibility\n- Resource management\n- Product realization\n- Measurement, analysis, improvement\n\n**Tools:**\n- QMS process mapping\n- Document control systems\n- Change management workflows\n\n### ISO 14971 (Medical Device Risk Management)\n\n**Managed by:** risk-management-specialist\n\n**Key Areas:**\n- Risk analysis and evaluation\n- Risk control measures\n- Residual risk evaluation\n- Risk management review\n\n**Tools:**\n- Risk assessment templates\n- FMEA/FMECA analysis\n- Risk-benefit analysis\n\n### MDR 2017/745 (EU Medical Device Regulation)\n\n**Managed by:** mdr-745-specialist\n\n**Key Areas:**\n- Technical documentation (Annex II, III)\n- Clinical evaluation (Annex XIV)\n- Post-market surveillance\n- UDI (Unique Device Identification)\n\n### FDA Regulations (US Medical Device Compliance)\n\n**Managed by:** fda-consultant-specialist\n\n**Key Areas:**\n- 510(k) premarket notification\n- PMA (Premarket Approval)\n- QSR (Quality System Regulation)\n- Post-market reporting\n\n### ISO 27001 (Information Security Management)\n\n**Managed by:** information-security-manager-iso27001, isms-audit-expert\n\n**Key Areas:**\n- ISMS establishment and maintenance\n- Risk assessment and treatment\n- Security controls (Annex A)\n- Continuous improvement\n\n### GDPR/DSGVO (Data Protection)\n\n**Managed by:** gdpr-dsgvo-expert\n\n**Key Areas:**\n- Data protection impact assessment (DPIA)\n- Privacy by design\n- Data subject rights\n- Breach notification\n\n## Regulatory Workflows\n\n### Workflow 1: New Medical Device Development\n\n```\n1. Risk Management (ISO 14971) → risk-management-specialist\n2. QMS Process Setup (ISO 13485) → quality-manager-qms-iso13485\n3. Technical Documentation (MDR) → mdr-745-specialist\n4. FDA Submission → fda-consultant-specialist\n5. Clinical Evaluation → regulatory-affairs-head\n```\n\n### Workflow 2: QMS Audit Preparation\n\n```\n1. Internal Audit → qms-audit-expert\n2. CAPA Implementation → capa-officer\n3. Document Review → quality-documentation-manager\n4. Management Review → quality-manager-qmr\n5. Certification Audit → qms-audit-expert\n```\n\n### Workflow 3: Data Protection Compliance\n\n```\n1. GDPR Assessment → gdpr-dsgvo-expert\n2. ISMS Implementation → information-security-manager-iso27001\n3. Security Audit → isms-audit-expert\n4. Continuous Monitoring → information-security-manager-iso27001\n```\n\n## Integration Patterns\n\n**RA/QM ↔ Engineering:** Regulatory requirements inform technical design decisions\n\n**RA/QM ↔ Product:** Compliance requirements shape product features and roadmap\n\n**RA/QM ↔ Security:** ISO 27001 aligns with security engineering practices\n\n## Additional Resources\n\n- **RA/QM Overview:** `README.md`\n- **Complete Skills Collection:** `final-complete-skills-collection.md`\n- **Start Here:** `START_HERE.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 14/14 RA/QM skills production-ready\n**Focus:** Medical device compliance (ISO 13485, MDR, FDA, ISO 27001, GDPR)\n","isInternal":false,"tokens":1098,"sizeBytes":4497},{"name":"CLAUDE.md","path":"research-ops/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/CLAUDE.md","title":"research-ops - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Research Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `research-ops/`.\n\n## Purpose\n\nThe Research Operations domain ships skills that help **R&D leads, clinical study teams, R&D finance/controllers, market-research analysts, and product-research / ResearchOps teams** plan, fund, scope, and synthesize research across enterprise workstreams. This is the **enterprise / cross-functional counterpart** to the academic `research/` domain (litreview, grants, patent, syllabus, pulse, dossier, notebooklm).\n\nIt is **not regulatory submission** (`ra-qm-team`), **not corporate financial close/valuation** (`finance/financial-analysis`), **not funding discovery** (`research/grants`), **not persona/journey/live-experiment design** (`product-team`), and **not campaign analytics** (`marketing-skill`).\n\n## Skills (v2.9.0)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `research-ops-skills` | Domain orchestrator — routes to 4 sub-skills | YES |\n| `clinical-research` | Study design: protocol synopsis + endpoint selection + sample-size/power + phase-gating | NO |\n| `research-finance` | R&D program budgeting + burn/runway + F&A rate modeling + capitalize-vs-expense routing | NO |\n| `market-research` | TAM/SAM/SOM (both methods) + survey/sampling design + segmentation + CI synthesis | NO |\n| `product-research` | Study design + saturation/sample method + insight repository synthesis | NO |\n\n## Hard rules (domain-specific)\n\n1. **clinical-research: outputs are study-design RECOMMENDATIONS signed by a named clinician/biostatistician/regulatory owner.** Power/sample-size is an ESTIMATE with stated assumptions — never presented as clinical fact. Every tool prints an \"ESTIMATE — confirm with a biostatistician\" banner.\n2. **research-finance: every budget output surfaces its assumptions block.** Capitalize-vs-expense routes to a NAMED finance owner and never auto-decides accounting treatment.\n3. **market-research: TAM/SAM/SOM always shows method (top-down AND bottoms-up) + assumptions.** Never a single unsourced number.\n4. **product-research: never fabricates user insight.** Sample-size/saturation guidance is method-based and surfaces confidence; single-source claims are flagged as anecdotes, not insights.\n5. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n6. **Industry tuning** via `--profile` on every scoring tool.\n7. **Matt Pocock grill discipline** — `/cs-grill-research-ops` interrogates the plan against the research canon (ICH E9, IAS 38, Cochran, Nielsen, Kotler) before any sub-skill runs.\n8. **Onboarding-first + customization-in-use.** Each sub-skill ships `scripts/onboard.py` (its own question set) + `scripts/config_loader.py`. Answers persist to `~/.config/research-ops/<skill>.json` (global) or `./.research-ops/<skill>.json` (project) and are consumed by every tool (CLI flags override; `RESEARCH_OPS_NO_CONFIG=1` bypasses). Customization must change behavior, not sit as decoration.\n9. **Autoresearch is opt-in + isolated.** Each sub-skill ships `scripts/ar_evaluator.py` — a per-skill, locked ground-truth bridge to `engineering/autoresearch-agent`. A loop is invoked ONLY on explicit user request and only edits the skill's input file, never the evaluator. No cross-skill coupling.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scoring scripts + 3 references (each citing 5-7 sources) + 1 asset template, **plus** 3 integration scripts — `onboard.py` (questionnaire), `config_loader.py` (customization loader, project→global→defaults precedence), and `ar_evaluator.py` (isolated autoresearch bridge). SKILL.md includes a \"Forcing-question library\" section (cited-canon grilling, one question at a time) and the \"Onboarding & customization\" + \"Optimize with autoresearch (opt-in)\" sections.\n\n## Agent + command pattern\n\n- `cs-research-ops-orchestrator` — evidence-first R&D operations lead. Voice: \"What decision does this research drive, and what's your confidence — show me the method and the assumptions before the number.\"\n- `/cs-research-ops <inquiry>` — top-level router\n- `/cs-grill-research-ops <plan>` — Matt-style grilling first\n- `/cs-clinical-research`, `/cs-research-finance`, `/cs-market-research`, `/cs-product-research` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `ra-qm-team` (regulatory/QM submission) — clinical-research designs the **study**, not the submission\n- ❌ Skills that overlap `finance/financial-analysis` (close/valuation) — research-finance manages **R&D program spend**\n- ❌ Skills that overlap `research/grants` (funding discovery) — research-finance manages **money already won**\n- ❌ Skills that overlap `product-team` (persona/journey/live experiments) — product-research is **method + repository discipline**\n- ❌ Skills that overlap `marketing-skill` (campaign analytics) — market-research is **upstream methodology**\n- ❌ A market size stated as a single unsourced number\n- ❌ A clinical power/endpoint output presented as fact rather than an estimate with a named owner\n- ❌ A product insight asserted from a single participant\n\n## References\n\n- Master plan: `documentation/implementation/research-ops-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Academic counterpart: `research/` (litreview, grants, patent)\n- Regulatory complement: `ra-qm-team`\n- Corporate-finance complement: `finance/financial-analysis`\n- Product complement: `product-team`\n","isInternal":false,"tokens":1320,"sizeBytes":5529},{"name":"CLAUDE.md","path":"standards/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/standards/CLAUDE.md","title":"standards - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Standards Library - Claude Code Guidance\n\nThis guide explains how to use the standards library for consistent quality across all skills and agents.\n\n## Standards Overview\n\n**Location:** `standards/`\n\n**Available Standards:**\n1. **communication/** - Communication principles and response protocols\n2. **quality/** - Code quality, testing, and validation standards\n3. **git/** - Git workflow, conventional commits, branching strategy\n4. **documentation/** - Markdown quality, structure consistency, living docs\n5. **security/** - Secret detection, dependency security, input validation\n\n## When to Reference Standards\n\n### Communication Standards\n\n**Reference when:**\n- Writing agent documentation\n- Creating SKILL.md files\n- Drafting user-facing content\n- Providing technical guidance\n\n**Key Principles:**\n- Absolute honesty - Direct assessments without cushioning\n- Zero fluff - Eliminate vague statements\n- Pragmatic focus - Actionable suggestions only\n- File economy - Edit existing files vs creating new ones\n\n**Location:** `communication/communication-standards.md`\n\n### Quality Standards\n\n**Reference when:**\n- Creating Python automation tools\n- Writing agent workflows\n- Implementing skill features\n- Testing integration points\n\n**Key Areas:**\n- Python tool quality (PEP 8, type hints, docstrings)\n- Agent workflow clarity (minimum 3 workflows documented)\n- Testing requirements (functional, integration, documentation)\n- Completion criteria (zero defect handoff, validation requirements)\n\n**Location:** `quality/quality-standards.md`\n\n### Git Workflow Standards\n\n**Reference when:**\n- Committing code changes\n- Creating feature branches\n- Tagging releases\n- Writing commit messages\n\n**Commit Format:**\n```bash\n<type>[optional scope]: <description>\n\n[optional body]\n\n[optional footer(s)]\n```\n\n**Types:** feat, fix, docs, style, refactor, perf, test, chore, ci\n\n**Examples:**\n```bash\nfeat(agents): implement cs-content-creator agent\nfix(seo-optimizer): correct keyword density calculation\ndocs(README): add agent catalog section\n```\n\n**Location:** `git/git-workflow-standards.md`\n\n### Documentation Standards\n\n**Reference when:**\n- Writing SKILL.md files\n- Creating agent documentation\n- Updating README files\n- Writing reference guides\n\n**Best Practices:**\n- Max 200 lines per CLAUDE.md file\n- Markdown formatting standards (headings, lists, code blocks)\n- Living documentation (README, CLAUDE, AGENTS updated regularly)\n- Link validation (no 404s, no broken references)\n\n**Location:** `documentation/documentation-standards.md`\n\n### Security Standards\n\n**Reference when:**\n- Writing Python scripts\n- Handling user input\n- Managing dependencies\n- Committing code\n\n**Critical Checks:**\n- No hardcoded API keys, passwords, or tokens\n- Environment variables for sensitive data\n- Input validation for all user input\n- Dependency security audits\n\n**Location:** `security/security-standards.md`\n\n## Standards Application Workflow\n\n### For New Skills\n\n```bash\n# 1. Reference communication standards\ncat standards/communication/communication-standards.md\n\n# 2. Review quality standards for Python tools\ncat standards/quality/quality-standards.md\n\n# 3. Follow documentation standards for SKILL.md\ncat standards/documentation/documentation-standards.md\n\n# 4. Apply security standards to scripts\ncat standards/security/security-standards.md\n\n# 5. Use git standards for commits\ncat standards/git/git-workflow-standards.md\n```\n\n### For New Agents\n\n```bash\n# 1. Communication: Write clear, actionable agent docs\n# 2. Quality: Minimum 3 workflows, tested relative paths\n# 3. Documentation: Follow agent template structure\n# 4. Git: Conventional commit with feat(agents) scope\n```\n\n## Standards Hierarchy\n\n**Priority Order:**\n1. **Security** - Non-negotiable, always enforced\n2. **Quality** - Zero defect handoff required\n3. **Git** - Conventional commits for all changes\n4. **Documentation** - Living docs stay current\n5. **Communication** - Clear, pragmatic, actionable\n\n## Standards Compliance Checklist\n\n### Before Committing Code\n\n- [ ] Communication: Documentation is clear and actionable\n- [ ] Quality: All tests passing, code reviewed\n- [ ] Git: Conventional commit message format\n- [ ] Documentation: Living docs updated if needed\n- [ ] Security: No secrets, input validated, dependencies secure\n\n### Before Creating PR\n\n- [ ] All standards compliance checks passed\n- [ ] Related documentation updated\n- [ ] Examples tested and working\n- [ ] No broken links or references\n\n## Related Documentation\n\n- **Main CLAUDE.md:** `../CLAUDE.md`\n- **Agent Development:** `../agents/CLAUDE.md`\n- **Domain Skills:** See navigation map in main CLAUDE.md\n\n---\n\n**Last Updated:** November 5, 2025\n**Standards Count:** 5 comprehensive standards\n**Enforcement:** Required for all skills and agents\n","isInternal":false,"tokens":1063,"sizeBytes":4782},{"name":"CLAUDE.md","path":"templates/CLAUDE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/templates/CLAUDE.md","title":"templates - Claude Agent Guidelines & System Prompt","category":"claude-rule","format":"markdown","content":"# Templates - Claude Code Guidance\n\nThis guide explains the template system for agents, commands, and standardized workflows.\n\n## Template Purpose\n\n**Location:** `templates/`\n\n**Purpose:** Reusable templates for consistent agent development, slash command creation, and workflow automation across all domains.\n\n## Available Templates\n\n### Agent Templates\n\n**Location:** `templates/agent-template.md`\n\n**Usage:** Starting point for creating new cs-* agents\n\n**Contains:**\n- YAML frontmatter structure\n- Required markdown sections\n- Workflow documentation format\n- Integration examples pattern\n\n**When to Use:** Creating any new agent in `agents/` directory\n\n### Command Templates and Workflow Templates\n\nNot yet created. There is no command template or workflow template file in `templates/` today — when creating slash commands, copy an existing command in `commands/` (e.g. `commands/cs-backend-review.md` for the argument-hint + gate pattern) instead of looking for a template here.\n\n## Template Usage Pattern\n\n```bash\n# 1. Copy template\ncp templates/agent-template.md agents/domain/cs-new-agent.md\n\n# 2. Customize for your agent\nvim agents/domain/cs-new-agent.md\n\n# 3. Follow template structure exactly\n\n# 4. Test relative paths and integrations\n\n# 5. Commit with conventional commit\ngit commit -m \"feat(agents): implement cs-new-agent from template\"\n```\n\n## Related Documentation\n\n- **Agent Development:** `../agents/CLAUDE.md` - Comprehensive agent creation guide\n- **Standards:** `../standards/CLAUDE.md` - Quality and consistency standards\n- **Main Documentation:** `../CLAUDE.md` - Repository overview\n\n---\n\n**Last Updated:** November 5, 2025\n**Purpose:** Consistent templates for rapid agent and workflow 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-->","isInternal":false,"tokens":6,"sizeBytes":34},{"name":"SKILL.md","path":".gemini/skills/sprint-plan/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/sprint-plan/SKILL.md","title":"sprint-plan","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fsprint-plan%2FSKILL.md -->","isInternal":false,"tokens":6,"sizeBytes":32},{"name":"SKILL.md","path":".gemini/skills/startup-cto/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/startup-cto/SKILL.md","title":"startup-cto","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fstartup-cto%2FSKILL.md -->","isInternal":false,"tokens":10,"sizeBytes":39},{"name":"SKILL.md","path":".gemini/skills/tc/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/tc/SKILL.md","title":"tc","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftc%2FSKILL.md -->","isInternal":false,"tokens":5,"sizeBytes":23},{"name":"SKILL.md","path":".gemini/skills/tdd/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/tdd/SKILL.md","title":"tdd","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftdd%2FSKILL.md -->","isInternal":false,"tokens":5,"sizeBytes":24},{"name":"SKILL.md","path":".gemini/skills/tech-debt/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/tech-debt/SKILL.md","title":"tech-debt","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Ftech-debt%2FSKILL.md -->","isInternal":false,"tokens":7,"sizeBytes":30},{"name":"SKILL.md","path":".gemini/skills/user-story/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/user-story/SKILL.md","title":"user-story","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fuser-story%2FSKILL.md -->","isInternal":false,"tokens":5,"sizeBytes":31},{"name":"SKILL.md","path":".gemini/skills/wiki-ingest/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/wiki-ingest/SKILL.md","title":"wiki-ingest","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-ingest%2FSKILL.md -->","isInternal":false,"tokens":6,"sizeBytes":32},{"name":"SKILL.md","path":".gemini/skills/wiki-init/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/wiki-init/SKILL.md","title":"wiki-init","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-init%2FSKILL.md -->","isInternal":false,"tokens":5,"sizeBytes":30},{"name":"SKILL.md","path":".gemini/skills/wiki-lint/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/wiki-lint/SKILL.md","title":"wiki-lint","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-lint%2FSKILL.md -->","isInternal":false,"tokens":6,"sizeBytes":30},{"name":"SKILL.md","path":".gemini/skills/wiki-log/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/wiki-log/SKILL.md","title":"wiki-log","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-log%2FSKILL.md -->","isInternal":false,"tokens":5,"sizeBytes":29},{"name":"SKILL.md","path":".gemini/skills/wiki-query/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/wiki-query/SKILL.md","title":"wiki-query","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.gemini%2Fskills%2Fwiki-query%2FSKILL.md -->","isInternal":false,"tokens":5,"sizeBytes":31},{"name":"skills-index.json","path":".hermes/skills/claude-skills/skills-index.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.hermes/skills/claude-skills/skills-index.json","title":"Claude-skills Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.hermes%2Fskills%2Fclaude-skills%2Fskills-index.json -->","isInternal":false,"tokens":10766,"sizeBytes":50030},{"name":"skills-index.json","path":".vibe/skills/claude-skills/skills-index.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.vibe/skills/claude-skills/skills-index.json","title":"Claude-skills Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.vibe%2Fskills%2Fclaude-skills%2Fskills-index.json -->","isInternal":false,"tokens":10766,"sizeBytes":50030},{"name":"README.md","path":"agent-launcher/skills/agent-launcher-orchestrator/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/agent-launcher-orchestrator/README.md","title":"Agent-launcher-orchestrator Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fagent-launcher-orchestrator%2FREADME.md -->","isInternal":false,"tokens":329,"sizeBytes":1261},{"name":"SKILL.md","path":"agent-launcher/skills/agent-launcher-orchestrator/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/agent-launcher-orchestrator/SKILL.md","title":"agent-launcher-orchestrator","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fagent-launcher-orchestrator%2FSKILL.md -->","frontmatter":{"name":"agent-launcher-orchestrator","description":"Use when a user wants to build, launch, grade, or schedule a Claude Managed Agent (CMA) in their own Anthropic account — \"build me an agent\", \"launch this as a managed agent\", \"run this on a schedule\", \"grade my agent against a rubric\", \"set up a nightly worker\". Reads the per-session goal (./my-agent/goal.json), routes deterministically to one of five phase sub-skills (interview → stage-launch → grade-iterate → run-without-you → wrap-up) via goal_router.py, and compiles the goal+phase into an execution shape (single-pass workflow / bounded grade→iterate loop / recurring cron deployment loop) via loop_compiler.py. Forks context so heavy intake (build sheets, payloads, eval cases) stays out of the parent thread. All launches are emitted as BYOK curl the user runs with their own key; no tool makes API calls. Inspired by anthropics/launch-your-agent (Apache-2.0). Distinct from engineering/agent-harness (generic domain loop) and engineering/write-a-skill (authors Claude Code skills, not CMAs).","context":"fork","license":"MIT","metadata":{"version":"2.11.2","author":"Alireza Rezvani","tags":["claude-managed-agents","cma","agent","launch","orchestrator","session-goal","loop","workflow","cron","outcome","byok"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1433,"sizeBytes":5380},{"name":"README.md","path":"agent-launcher/skills/grade-iterate/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/grade-iterate/README.md","title":"Grade-iterate Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fgrade-iterate%2FREADME.md -->","isInternal":false,"tokens":266,"sizeBytes":997},{"name":"SKILL.md","path":"agent-launcher/skills/grade-iterate/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/grade-iterate/SKILL.md","title":"grade-iterate","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fgrade-iterate%2FSKILL.md -->","frontmatter":{"name":"grade-iterate","description":"Phase 3 of building a Claude Managed Agent — the bounded grade→iterate loop. Define a CMA outcome (a required markdown rubric graded by an isolated grader), read each verdict, decide the next move (sharpen / re-run / promote to schedule), and once a version passes, run held-back eval cases in parallel. Use when the user says \"grade my agent\", \"make it pass the rubric\", \"iterate until it's good\", \"is it good enough\", or when the orchestrator routes phase=grade-iterate. outcome_builder.py builds the user.define_outcome payload (rubric required, max_iterations clamped 1..20 — never unbounded); verdict_reader.py reads the grader result and recommends the next move; eval_scaffold.py generates held-back cases + a parallel run plan (capped at the 25-thread CMA ceiling). Distinct from stage-launch (first launch) and run-without-you (scheduling).","license":"MIT","metadata":{"version":"2.11.2","author":"Alireza Rezvani","tags":["cma","outcome","rubric","grader","grade-iterate","loop","max-iterations","eval","held-back"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1082,"sizeBytes":4179},{"name":"README.md","path":"agent-launcher/skills/interview/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/interview/README.md","title":"Interview Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Finterview%2FREADME.md -->","isInternal":false,"tokens":276,"sizeBytes":1107},{"name":"SKILL.md","path":"agent-launcher/skills/interview/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/interview/SKILL.md","title":"interview","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Finterview%2FSKILL.md -->","frontmatter":{"name":"interview","description":"Phase 1 of building a Claude Managed Agent — interview the founder about the one job the agent should do, then produce a build sheet (CMA primitives table + v1/v2 deferrals + eval plan) WITHOUT needing their API key yet. Use when the user says \"help me scope an agent\", \"I have an idea for an agent\", \"what should this agent be\", or when the orchestrator routes phase=interview. Drives the six intake slots (job, trigger, inputs, actions, definition-of-done, recurrence) via AskUserQuestion, maps them to primitives with interview_planner.py, assembles build-sheet.json with build_sheet_builder.py, and validates limits with primitives_validator.py. Connectors are mockable in v0 (schema-true custom tools); real MCP servers become v1 deferrals. Distinct from stage-launch (which turns the sheet into payloads).","license":"MIT","metadata":{"version":"2.11.2","author":"Alireza Rezvani","tags":["cma","interview","scoping","build-sheet","primitives","deferrals","eval-plan"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1156,"sizeBytes":4456},{"name":"README.md","path":"agent-launcher/skills/run-without-you/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/run-without-you/README.md","title":"Run-without-you Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Frun-without-you%2FREADME.md -->","isInternal":false,"tokens":292,"sizeBytes":1115},{"name":"SKILL.md","path":"agent-launcher/skills/run-without-you/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/run-without-you/SKILL.md","title":"run-without-you","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Frun-without-you%2FSKILL.md -->","frontmatter":{"name":"run-without-you","description":"Phase 4 of building a Claude Managed Agent — make it run without you. Turn a graded agent into a recurring scheduled deployment (POSIX-cron), an event-driven curl trigger, or confirmed on-demand use, then finalize the versioned roadmap. Use when the user says \"run it every morning\", \"put it on a schedule\", \"nightly\", \"weekly\", \"automate this\", \"make it recurring\", or when the orchestrator routes phase=run-without-you. deployment_builder.py builds the POST /v1/deployments payload (initial_events must include user.message; optionally nests a user.define_outcome so each firing self-grades); cron_validator.py validates the 5-field cron + IANA timezone and prints the wall-clock DST note; next_directions_writer.py writes NEXT-DIRECTIONS.md. No tool makes API calls — the deployment is created via BYOK curl. Distinct from grade-iterate (the in-session loop) and wrap-up (closeout).","license":"MIT","metadata":{"version":"2.11.2","author":"Alireza Rezvani","tags":["cma","deployment","cron","schedule","recurring","run-without-you","next-directions","dst"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1128,"sizeBytes":4370},{"name":"README.md","path":"agent-launcher/skills/stage-launch/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/stage-launch/README.md","title":"Stage-launch Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fstage-launch%2FREADME.md -->","isInternal":false,"tokens":279,"sizeBytes":1060},{"name":"SKILL.md","path":"agent-launcher/skills/stage-launch/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/stage-launch/SKILL.md","title":"stage-launch","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fstage-launch%2FSKILL.md -->","frontmatter":{"name":"stage-launch","description":"Phase 2 of building a Claude Managed Agent — turn a validated build sheet into exact API payloads and a resumable BYOK curl launch script, then launch (environment → agent → session → kickoff) using the founder's OWN Anthropic key. Use when the user says \"launch it\", \"deploy the agent\", \"create the agent now\", or when the orchestrator routes phase=stage-launch. payload_generator.py emits the four ordered payloads; launch_script_writer.py writes launch.sh that reads $ANTHROPIC_API_KEY at runtime and never embeds it; payload_validator.py runs a pre-launch check including an API-key-leak scan. No tool in this skill makes network calls — the user runs launch.sh themselves. Distinct from interview (planning) and grade-iterate (the outcome loop).","license":"MIT","metadata":{"version":"2.11.2","author":"Alireza Rezvani","tags":["cma","launch","payloads","curl","byok","api-key-safety","environment","agent","session"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1014,"sizeBytes":3917},{"name":"README.md","path":"agent-launcher/skills/wrap-up/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/wrap-up/README.md","title":"Wrap-up Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fwrap-up%2FREADME.md -->","isInternal":false,"tokens":209,"sizeBytes":844},{"name":"SKILL.md","path":"agent-launcher/skills/wrap-up/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/skills/wrap-up/SKILL.md","title":"wrap-up","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2Fskills%2Fwrap-up%2FSKILL.md -->","frontmatter":{"name":"wrap-up","description":"Close out a launched Claude Managed Agent — recap every primitive the founder now owns, regenerate the single-file overview page, and suggest the next 1-2 upgrades. Use when the user says \"wrap up\", \"close this out\", \"what do I own now\", \"give me the summary\", \"recap the agent\", or when the orchestrator routes phase=wrap-up. primitives_inventory.py tables everything owned (agent, environment, session, memory, outcome, deployment); overview_page.py regenerates a self-contained ./my-agent/agent-overview.html; upgrade_suggester.py ranks the next moves from recorded deferrals plus standing hardening steps. Companion to run-without-you; the last stop before phase=done.","license":"MIT","metadata":{"version":"2.11.2","author":"Alireza Rezvani","tags":["cma","wrap-up","closeout","inventory","overview","upgrades","next-directions"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":772,"sizeBytes":3100},{"name":"SKILL.md","path":"business-growth/skills/business-growth-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-growth/skills/business-growth-skills/SKILL.md","title":"business-growth-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fbusiness-growth-skills%2FSKILL.md -->","frontmatter":{"name":"business-growth-skills","description":"Router/index for the 4 business & growth skills bundled in this plugin: customer-success-manager (health scoring, churn risk, expansion), sales-engineer (RFP analysis, competitive matrices, PoC planning), revenue-operations (pipeline, forecast accuracy, GTM efficiency), and contract-and-proposal-writer. Use when a growth/revenue request doesn't obviously match one skill and you need to pick the right one (e.g., 'which accounts are at risk', 'should we bid on this RFP').","license":"MIT","metadata":{"version":"2.9.0","author":"Alireza Rezvani","tags":["business","customer-success","sales","revenue-operations","growth"],"agents":["claude-code","codex-cli","openclaw"]}},"isInternal":false,"tokens":498,"sizeBytes":2060},{"name":"SKILL.md","path":"business-growth/skills/contract-and-proposal-writer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-growth/skills/contract-and-proposal-writer/SKILL.md","title":"contract-and-proposal-writer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcontract-and-proposal-writer%2FSKILL.md -->","frontmatter":{"name":"contract-and-proposal-writer","description":"Generate professional, jurisdiction-aware business documents: freelance contracts, project proposals, SOWs, NDAs, and MSAs. Structured Markdown output with docx conversion instructions. Covers US (Delaware), EU (GDPR), UK, and DACH (German law) jurisdictions. Not a substitute for legal counsel — use as strong starting points. Use when drafting a freelance contract, preparing a client proposal, writing an SOW for a new engagement, or producing an NDA before sharing sensitive material."},"isInternal":false,"tokens":3334,"sizeBytes":13756},{"name":"executive_business_review_template.md","path":"business-growth/skills/customer-success-manager/assets/executive_business_review_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-growth/skills/customer-success-manager/assets/executive_business_review_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcustomer-success-manager%2Fassets%2Fexecutive_business_review_template.md -->","isInternal":false,"tokens":1894,"sizeBytes":6951},{"name":"expected_output.json","path":"business-growth/skills/customer-success-manager/assets/expected_output.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-growth/skills/customer-success-manager/assets/expected_output.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2Fskills%2Fcustomer-success-manager%2Fassets%2Fexpected_output.json -->","frontmatter":{"report":"customer_health_scores","summary":{"total_customers":4,"average_score":78.8,"green_count":3,"yellow_count":1,"red_count":0},"customers":[{"customer_id":"CUST-001","name":"Acme Corp","segment":"enterprise","arr":120000,"overall_score":86.2,"classification":"green","dimensions":{"usage":{"score":91.6,"weight":"30%","classification":"green"},"engagement":{"score":82,"weight":"25%","classification":"green"},"support":{"score":78.5,"weight":"20%","classification":"green"},"relationship":{"score":90.1,"weight":"25%","classification":"green"}},"trends":{"usage":"improving","engagement":"improving","support":"stable","relationship":"improving","overall":"improving"},"recommendations":[]},{"customer_id":"CUST-002","name":"TechStart 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Distinct from business-growth (external sales motion) and c-level-advisor (strategic, not operational).","context":"fork","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["bizops","operations","process","vendor","capacity","sop","procurement","coo","orchestrator"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2167,"sizeBytes":9112},{"name":"capacity_brief_template.md","path":"business-operations/skills/capacity-planner/assets/capacity_brief_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/capacity-planner/assets/capacity_brief_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2Fassets%2Fcapacity_brief_template.md -->","isInternal":false,"tokens":1410,"sizeBytes":4984},{"name":"capacity_anti_patterns.md","path":"business-operations/skills/capacity-planner/references/capacity_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/capacity-planner/references/capacity_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2Freferences%2Fcapacity_anti_patterns.md -->","isInternal":false,"tokens":2384,"sizeBytes":9049},{"name":"ops_workforce_planning_canon.md","path":"business-operations/skills/capacity-planner/references/ops_workforce_planning_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/capacity-planner/references/ops_workforce_planning_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2Freferences%2Fops_workforce_planning_canon.md -->","isInternal":false,"tokens":1582,"sizeBytes":6317},{"name":"queueing_theory_canon.md","path":"business-operations/skills/capacity-planner/references/queueing_theory_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/capacity-planner/references/queueing_theory_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2Freferences%2Fqueueing_theory_canon.md -->","isInternal":false,"tokens":1566,"sizeBytes":5981},{"name":"SKILL.md","path":"business-operations/skills/capacity-planner/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/capacity-planner/SKILL.md","title":"capacity-planner","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fcapacity-planner%2FSKILL.md -->","frontmatter":{"name":"capacity-planner","description":"Use when an ops leader (Director of CX, Head of Support, VP Ops, Head of BizOps, Head of IT ops, Head of Finance ops) is sizing ops capacity, building a headcount plan, modeling utilization risk, planning Q3 capacity or annual support capacity, or designing CS coverage — and needs Erlang-C queueing math, P90 demand sizing, shrinkage-adjusted FTE, manager-trigger thresholds, and a quarterly hiring sequence with ramp + attrition. Apply when sustained team utilization is above 80% or when the team is growing more than 50% in 12 months. Run before committing the headcount budget. This is NOT engineering capacity (see vpe-advisor for DORA + cycle time) and NOT strategic 3-year workforce planning (see chro-advisor).","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["bizops","capacity","headcount","utilization","queueing-theory","ops-planning","little-law","workforce"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3156,"sizeBytes":12160},{"name":"comms_brief_template.md","path":"business-operations/skills/internal-comms/assets/comms_brief_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/internal-comms/assets/comms_brief_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Finternal-comms%2Fassets%2Fcomms_brief_template.md -->","isInternal":false,"tokens":1837,"sizeBytes":7286},{"name":"announcement_anti_patterns.md","path":"business-operations/skills/internal-comms/references/announcement_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/internal-comms/references/announcement_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Finternal-comms%2Freferences%2Fannouncement_anti_patterns.md -->","isInternal":false,"tokens":1910,"sizeBytes":8307},{"name":"change_management_canon.md","path":"business-operations/skills/internal-comms/references/change_management_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/internal-comms/references/change_management_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Finternal-comms%2Freferences%2Fchange_management_canon.md -->","isInternal":false,"tokens":1803,"sizeBytes":7479},{"name":"internal_comms_canon.md","path":"business-operations/skills/internal-comms/references/internal_comms_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/internal-comms/references/internal_comms_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Finternal-comms%2Freferences%2Finternal_comms_canon.md -->","isInternal":false,"tokens":1765,"sizeBytes":7621},{"name":"SKILL.md","path":"business-operations/skills/internal-comms/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/internal-comms/SKILL.md","title":"internal-comms","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Finternal-comms%2FSKILL.md -->","frontmatter":{"name":"internal-comms","description":"Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management communication — a re-org announcement, a tool rollout, a policy change, a leadership transition, a layoff, an acquisition close, or an internal product launch — and the audience is employees (not customers). Pairs Prosci ADKAR and Kotter's 8-step change model with deterministic stdlib-only Python tools to produce a sequenced touchpoint calendar, a Kotter-compliant primary announcement, an audience-segmented FAQ, and manager cascade talking points; industry-tuned via --profile {tech-startup, scaleup, enterprise, public-company, non-profit}. Triggers on \"all-hands announcement\", \"change comms\", \"rollout comms\", \"re-org announcement\", \"manager talking points\", \"layoff comms\".","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["bizops","internal-comms","change-management","adkar","kotter","all-hands","town-hall","prosci"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3172,"sizeBytes":13851},{"name":"runbook_template.md","path":"business-operations/skills/knowledge-ops/assets/runbook_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/knowledge-ops/assets/runbook_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fknowledge-ops%2Fassets%2Frunbook_template.md -->","isInternal":false,"tokens":1429,"sizeBytes":5778},{"name":"sop_template.md","path":"business-operations/skills/knowledge-ops/assets/sop_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/knowledge-ops/assets/sop_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fknowledge-ops%2Fassets%2Fsop_template.md -->","isInternal":false,"tokens":1169,"sizeBytes":4661},{"name":"5w2h_sop_canon.md","path":"business-operations/skills/knowledge-ops/references/5w2h_sop_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/knowledge-ops/references/5w2h_sop_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fknowledge-ops%2Freferences%2F5w2h_sop_canon.md -->","isInternal":false,"tokens":1425,"sizeBytes":5999},{"name":"kb_hygiene_anti_patterns.md","path":"business-operations/skills/knowledge-ops/references/kb_hygiene_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/knowledge-ops/references/kb_hygiene_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fknowledge-ops%2Freferences%2Fkb_hygiene_anti_patterns.md -->","isInternal":false,"tokens":2272,"sizeBytes":9744},{"name":"runbook_canon.md","path":"business-operations/skills/knowledge-ops/references/runbook_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/knowledge-ops/references/runbook_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fknowledge-ops%2Freferences%2Frunbook_canon.md -->","isInternal":false,"tokens":1570,"sizeBytes":6739},{"name":"SKILL.md","path":"business-operations/skills/knowledge-ops/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/knowledge-ops/SKILL.md","title":"knowledge-ops","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fknowledge-ops%2FSKILL.md -->","frontmatter":{"name":"knowledge-ops","description":"Use when a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Ishikawa's 5W2H method, Gawande's *The Checklist Manifesto*, ISO 9001, ITIL v4, and Google SRE Workbook runbook discipline with deterministic stdlib-only Python tools that score completeness, detect anti-patterns, and emit prioritized cleanup lists (e.g., \"validate this runbook before it goes into rotation\", \"audit our Confluence wiki for stale and orphaned SOPs\").","context":"fork","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["bizops","sop","runbook","knowledge-management","kb","5w2h","wiki","ops-documentation"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3939,"sizeBytes":16449},{"name":"process_template.md","path":"business-operations/skills/process-mapper/assets/process_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/process-mapper/assets/process_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocess-mapper%2Fassets%2Fprocess_template.md -->","isInternal":false,"tokens":1165,"sizeBytes":4333},{"name":"bottleneck_anti_patterns.md","path":"business-operations/skills/process-mapper/references/bottleneck_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/process-mapper/references/bottleneck_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocess-mapper%2Freferences%2Fbottleneck_anti_patterns.md -->","isInternal":false,"tokens":1905,"sizeBytes":7800},{"name":"bpmn_essentials.md","path":"business-operations/skills/process-mapper/references/bpmn_essentials.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/process-mapper/references/bpmn_essentials.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocess-mapper%2Freferences%2Fbpmn_essentials.md -->","isInternal":false,"tokens":1565,"sizeBytes":6491},{"name":"lean_six_sigma_canon.md","path":"business-operations/skills/process-mapper/references/lean_six_sigma_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/process-mapper/references/lean_six_sigma_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocess-mapper%2Freferences%2Flean_six_sigma_canon.md -->","isInternal":false,"tokens":1599,"sizeBytes":6569},{"name":"SKILL.md","path":"business-operations/skills/process-mapper/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/process-mapper/SKILL.md","title":"process-mapper","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocess-mapper%2FSKILL.md -->","frontmatter":{"name":"process-mapper","description":"Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time. Pairs Lean / Six Sigma / Theory-of-Constraints canon with deterministic stdlib-only Python tools to produce a process map, a ranked bottleneck list (with severity + root-cause hypothesis), and a cycle-time analysis (P50, P90, value-add ratio, Little's-Law throughput). Distinct from sales-pipeline, system-reliability (SLO), and strategic-OKR work — this is tactical process documentation for internal operations.","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["bizops","process","bpmn","bottleneck","cycle-time","lean","six-sigma","value-stream"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2168,"sizeBytes":9011},{"name":"spend_intake_template.md","path":"business-operations/skills/procurement-optimizer/assets/spend_intake_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/procurement-optimizer/assets/spend_intake_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocurement-optimizer%2Fassets%2Fspend_intake_template.md -->","isInternal":false,"tokens":1409,"sizeBytes":5353},{"name":"procurement_anti_patterns.md","path":"business-operations/skills/procurement-optimizer/references/procurement_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/procurement-optimizer/references/procurement_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocurement-optimizer%2Freferences%2Fprocurement_anti_patterns.md -->","isInternal":false,"tokens":2436,"sizeBytes":10822},{"name":"saas_management_canon.md","path":"business-operations/skills/procurement-optimizer/references/saas_management_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/procurement-optimizer/references/saas_management_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocurement-optimizer%2Freferences%2Fsaas_management_canon.md -->","isInternal":false,"tokens":1518,"sizeBytes":6754},{"name":"spend_management_canon.md","path":"business-operations/skills/procurement-optimizer/references/spend_management_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/procurement-optimizer/references/spend_management_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocurement-optimizer%2Freferences%2Fspend_management_canon.md -->","isInternal":false,"tokens":1485,"sizeBytes":6776},{"name":"SKILL.md","path":"business-operations/skills/procurement-optimizer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/procurement-optimizer/SKILL.md","title":"procurement-optimizer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fprocurement-optimizer%2FSKILL.md -->","frontmatter":{"name":"procurement-optimizer","description":"Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs a spend audit, spend categorization (UNSPSC-aligned with Pareto breakdown and industry profiles), purchasing-cycle analysis (bottleneck categories per Goldratt's Theory of Constraints), or risk-balanced supplier consolidation that refuses single-source recommendations for tier-1 categories without a documented break-glass plan. Triggers on \"spend audit\", \"SaaS audit\", \"spend categorization\", \"supplier rationalization\", \"supplier consolidation\", \"category strategy\", \"duplicate SaaS\", \"renewal cluster\".","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["bizops","procurement","spend-categorization","supplier-consolidation","unspsc","saas-audit","purchasing-cycle"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3224,"sizeBytes":14255},{"name":"vendor_catalog_template.md","path":"business-operations/skills/vendor-management/assets/vendor_catalog_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/vendor-management/assets/vendor_catalog_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fvendor-management%2Fassets%2Fvendor_catalog_template.md -->","isInternal":false,"tokens":2044,"sizeBytes":6799},{"name":"sla_design_patterns.md","path":"business-operations/skills/vendor-management/references/sla_design_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/vendor-management/references/sla_design_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fvendor-management%2Freferences%2Fsla_design_patterns.md -->","isInternal":false,"tokens":1557,"sizeBytes":6574},{"name":"vendor_management_canon.md","path":"business-operations/skills/vendor-management/references/vendor_management_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/vendor-management/references/vendor_management_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fvendor-management%2Freferences%2Fvendor_management_canon.md -->","isInternal":false,"tokens":1335,"sizeBytes":5537},{"name":"vendor_risk_anti_patterns.md","path":"business-operations/skills/vendor-management/references/vendor_risk_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/vendor-management/references/vendor_risk_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fvendor-management%2Freferences%2Fvendor_risk_anti_patterns.md -->","isInternal":false,"tokens":2024,"sizeBytes":8707},{"name":"SKILL.md","path":"business-operations/skills/vendor-management/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/skills/vendor-management/SKILL.md","title":"vendor-management","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2Fskills%2Fvendor-management%2FSKILL.md -->","frontmatter":{"name":"vendor-management","description":"Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA compliance with credit-claim flags, classifying third-party risk across 4 risk vectors, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. 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Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"chief-customer-officer-leadership","updated":"2026-05-13","python-tools":"retention_decomposition_analyzer.py, customer_segmentation_designer.py, cs_coverage_calculator.py","frameworks":"retention-decomposition, customer-segmentation, cs-coverage-model, cs-team-org"}},"isInternal":false,"tokens":2889,"sizeBytes":11993},{"name":"ai_training_data_rights.md","path":"c-level-advisor/skills/chief-data-officer-advisor/references/ai_training_data_rights.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-data-officer-advisor/references/ai_training_data_rights.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-data-officer-advisor%2Freferences%2Fai_training_data_rights.md -->","isInternal":false,"tokens":1882,"sizeBytes":7563},{"name":"customer_data_as_asset.md","path":"c-level-advisor/skills/chief-data-officer-advisor/references/customer_data_as_asset.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-data-officer-advisor/references/customer_data_as_asset.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-data-officer-advisor%2Freferences%2Fcustomer_data_as_asset.md -->","isInternal":false,"tokens":2447,"sizeBytes":10285},{"name":"data_product_strategy.md","path":"c-level-advisor/skills/chief-data-officer-advisor/references/data_product_strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-data-officer-advisor/references/data_product_strategy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-data-officer-advisor%2Freferences%2Fdata_product_strategy.md -->","isInternal":false,"tokens":2017,"sizeBytes":8612},{"name":"data_team_org_evolution.md","path":"c-level-advisor/skills/chief-data-officer-advisor/references/data_team_org_evolution.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-data-officer-advisor/references/data_team_org_evolution.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-data-officer-advisor%2Freferences%2Fdata_team_org_evolution.md -->","isInternal":false,"tokens":2408,"sizeBytes":10446},{"name":"SKILL.md","path":"c-level-advisor/skills/chief-data-officer-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-data-officer-advisor/SKILL.md","title":"chief-data-officer-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-data-officer-advisor%2FSKILL.md -->","frontmatter":{"name":"chief-data-officer-advisor","description":"Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy), B2B customer-data-as-asset valuation and M&A readiness, data team org evolution. Use when deciding whether to train models on customer data, choosing data architecture, valuing data for fundraising or M&A, sequencing data hires, or when user mentions CDO, chief data officer, data strategy, data mesh, lakehouse, training data, data product, data monetization, or customer data asset. NOT a tactical data engineering skill — strategic decisions only.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"chief-data-officer-leadership","updated":"2026-05-12","python-tools":"ai_training_data_audit.py, data_product_strategy_picker.py, data_asset_valuator.py","frameworks":"training-data-rights-matrix, data-product-strategy, customer-data-as-asset, data-team-org-evolution"}},"isInternal":false,"tokens":2815,"sizeBytes":11695},{"name":"routing-matrix.md","path":"c-level-advisor/skills/chief-of-staff/references/routing-matrix.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-of-staff/references/routing-matrix.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-of-staff%2Freferences%2Frouting-matrix.md -->","isInternal":false,"tokens":3287,"sizeBytes":12070},{"name":"synthesis-framework.md","path":"c-level-advisor/skills/chief-of-staff/references/synthesis-framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-of-staff/references/synthesis-framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-of-staff%2Freferences%2Fsynthesis-framework.md -->","isInternal":false,"tokens":1790,"sizeBytes":7887},{"name":"SKILL.md","path":"c-level-advisor/skills/chief-of-staff/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chief-of-staff/SKILL.md","title":"chief-of-staff","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchief-of-staff%2FSKILL.md -->","frontmatter":{"name":"chief-of-staff","description":"C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically. Use when a founder question needs routing to the right advisor — e.g. 'should we raise now or cut burn?' — or when a multi-domain decision needs a board meeting convened.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"orchestration","updated":"2026-03-05","frameworks":"routing-matrix, synthesis-framework, decision-log, board-protocol"}},"isInternal":false,"tokens":1688,"sizeBytes":6731},{"name":"comp_frameworks.md","path":"c-level-advisor/skills/chro-advisor/references/comp_frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chro-advisor/references/comp_frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchro-advisor%2Freferences%2Fcomp_frameworks.md -->","isInternal":false,"tokens":3292,"sizeBytes":12570},{"name":"org_design.md","path":"c-level-advisor/skills/chro-advisor/references/org_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chro-advisor/references/org_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchro-advisor%2Freferences%2Forg_design.md -->","isInternal":false,"tokens":3098,"sizeBytes":13711},{"name":"people_strategy.md","path":"c-level-advisor/skills/chro-advisor/references/people_strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chro-advisor/references/people_strategy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchro-advisor%2Freferences%2Fpeople_strategy.md -->","isInternal":false,"tokens":3016,"sizeBytes":12788},{"name":"SKILL.md","path":"c-level-advisor/skills/chro-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/chro-advisor/SKILL.md","title":"chro-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fchro-advisor%2FSKILL.md -->","frontmatter":{"name":"chro-advisor","description":"People leadership for scaling companies. Hiring strategy, compensation design, org structure, culture, and retention. Use when building hiring plans, designing comp frameworks, restructuring teams, managing performance, building culture, or when user mentions CHRO, HR, people strategy, talent, headcount, compensation, org design, retention, or performance management.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"chro-leadership","updated":"2026-03-05","python-tools":"hiring_plan_modeler.py, comp_benchmarker.py","frameworks":"people-strategy, comp-frameworks, org-design"}},"isInternal":false,"tokens":1713,"sizeBytes":7241},{"name":"compliance_roadmap.md","path":"c-level-advisor/skills/ciso-advisor/references/compliance_roadmap.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ciso-advisor/references/compliance_roadmap.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fciso-advisor%2Freferences%2Fcompliance_roadmap.md -->","isInternal":false,"tokens":4419,"sizeBytes":16627},{"name":"incident_response.md","path":"c-level-advisor/skills/ciso-advisor/references/incident_response.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ciso-advisor/references/incident_response.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fciso-advisor%2Freferences%2Fincident_response.md -->","isInternal":false,"tokens":3588,"sizeBytes":16423},{"name":"security_strategy.md","path":"c-level-advisor/skills/ciso-advisor/references/security_strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ciso-advisor/references/security_strategy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fciso-advisor%2Freferences%2Fsecurity_strategy.md -->","isInternal":false,"tokens":2932,"sizeBytes":12079},{"name":"SKILL.md","path":"c-level-advisor/skills/ciso-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ciso-advisor/SKILL.md","title":"ciso-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fciso-advisor%2FSKILL.md -->","frontmatter":{"name":"ciso-advisor","description":"Security leadership for growth-stage companies. Risk quantification in dollars, compliance roadmap (SOC 2/ISO 27001/HIPAA/GDPR), security architecture strategy, incident response leadership, and board-level security reporting. Use when building security programs, justifying security budget, selecting compliance frameworks, managing incidents, assessing vendor risk, or when user mentions CISO, security strategy, compliance roadmap, zero trust, or board security reporting.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"ciso-leadership","updated":"2026-03-05","python-tools":"risk_quantifier.py, compliance_tracker.py","frameworks":"risk-based-security, zero-trust, defense-in-depth"}},"isInternal":false,"tokens":1634,"sizeBytes":7275},{"name":"brand_positioning.md","path":"c-level-advisor/skills/cmo-advisor/references/brand_positioning.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cmo-advisor/references/brand_positioning.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcmo-advisor%2Freferences%2Fbrand_positioning.md -->","isInternal":false,"tokens":3727,"sizeBytes":16585},{"name":"growth_frameworks.md","path":"c-level-advisor/skills/cmo-advisor/references/growth_frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cmo-advisor/references/growth_frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcmo-advisor%2Freferences%2Fgrowth_frameworks.md -->","isInternal":false,"tokens":4352,"sizeBytes":18927},{"name":"marketing_org.md","path":"c-level-advisor/skills/cmo-advisor/references/marketing_org.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cmo-advisor/references/marketing_org.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcmo-advisor%2Freferences%2Fmarketing_org.md -->","isInternal":false,"tokens":2600,"sizeBytes":11595},{"name":"SKILL.md","path":"c-level-advisor/skills/cmo-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cmo-advisor/SKILL.md","title":"cmo-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcmo-advisor%2FSKILL.md -->","frontmatter":{"name":"cmo-advisor","description":"Marketing leadership for scaling companies. Brand positioning, growth model design, marketing budget allocation, and marketing org design. Use when designing brand strategy, selecting growth models (PLG vs sales-led vs community-led), allocating marketing budgets, building marketing teams, or when user mentions CMO, brand strategy, growth model, CAC, LTV, channel mix, or marketing ROI.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"cmo-leadership","updated":"2026-03-05","python-tools":"marketing_budget_modeler.py, growth_model_simulator.py","frameworks":"brand-positioning, growth-frameworks, marketing-org"}},"isInternal":false,"tokens":1946,"sizeBytes":8523},{"name":"implementation-guide.md","path":"c-level-advisor/skills/company-os/references/implementation-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/company-os/references/implementation-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcompany-os%2Freferences%2Fimplementation-guide.md -->","isInternal":false,"tokens":2392,"sizeBytes":9990},{"name":"os-comparison.md","path":"c-level-advisor/skills/company-os/references/os-comparison.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/company-os/references/os-comparison.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcompany-os%2Freferences%2Fos-comparison.md -->","isInternal":false,"tokens":2537,"sizeBytes":10996},{"name":"SKILL.md","path":"c-level-advisor/skills/company-os/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/company-os/SKILL.md","title":"company-os","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcompany-os%2FSKILL.md -->","frontmatter":{"name":"company-os","description":"The meta-framework for how a company runs — the connective tissue between all C-suite roles. Covers operating system selection (EOS, Scaling Up, OKR-native, hybrid), accountability charts, scorecards, meeting pulse, issue resolution, and 90-day rocks. Use when setting up company operations, selecting a management framework, designing meeting rhythms, building accountability systems, implementing OKRs, or when user mentions EOS, Scaling Up, operating system, L10 meetings, rocks, scorecard, accountability chart, or quarterly planning.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"company-operations","updated":"2026-03-05","frameworks":"os-comparison, implementation-guide"}},"isInternal":false,"tokens":2510,"sizeBytes":10798},{"name":"ci-playbook.md","path":"c-level-advisor/skills/competitive-intel/references/ci-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/competitive-intel/references/ci-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcompetitive-intel%2Freferences%2Fci-playbook.md -->","isInternal":false,"tokens":2325,"sizeBytes":9978},{"name":"SKILL.md","path":"c-level-advisor/skills/competitive-intel/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/competitive-intel/SKILL.md","title":"competitive-intel","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcompetitive-intel%2FSKILL.md -->","frontmatter":{"name":"competitive-intel","description":"Systematic competitor tracking that feeds CMO positioning, CRO battlecards, and CPO roadmap decisions. Use when analyzing competitors, building sales battlecards, tracking market moves, positioning against alternatives, or when user mentions competitive intelligence, competitive analysis, competitor research, battlecards, win/loss, or market positioning.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"competitive-strategy","updated":"2026-03-05","frameworks":"ci-playbook, battlecard-template"}},"isInternal":false,"tokens":1897,"sizeBytes":8315},{"name":"battlecard-template.md","path":"c-level-advisor/skills/competitive-intel/templates/battlecard-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/competitive-intel/templates/battlecard-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcompetitive-intel%2Ftemplates%2Fbattlecard-template.md -->","isInternal":false,"tokens":877,"sizeBytes":3589},{"name":"anonymization-protocol.md","path":"c-level-advisor/skills/context-engine/references/anonymization-protocol.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/context-engine/references/anonymization-protocol.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcontext-engine%2Freferences%2Fanonymization-protocol.md -->","isInternal":false,"tokens":1372,"sizeBytes":5766},{"name":"SKILL.md","path":"c-level-advisor/skills/context-engine/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/context-engine/SKILL.md","title":"context-engine","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcontext-engine%2FSKILL.md -->","frontmatter":{"name":"context-engine","description":"Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (older than 90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls. Use when starting any C-suite advisor session, when context looks stale or missing, or before sending company data to an external service.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"orchestration","updated":"2026-03-05","frameworks":"context-loading, anonymization, context-enrichment"}},"isInternal":false,"tokens":1044,"sizeBytes":4517},{"name":"ops_cadence.md","path":"c-level-advisor/skills/coo-advisor/references/ops_cadence.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/coo-advisor/references/ops_cadence.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcoo-advisor%2Freferences%2Fops_cadence.md -->","isInternal":false,"tokens":4723,"sizeBytes":18849},{"name":"process_frameworks.md","path":"c-level-advisor/skills/coo-advisor/references/process_frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/coo-advisor/references/process_frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcoo-advisor%2Freferences%2Fprocess_frameworks.md -->","isInternal":false,"tokens":4458,"sizeBytes":20077},{"name":"scaling_playbook.md","path":"c-level-advisor/skills/coo-advisor/references/scaling_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/coo-advisor/references/scaling_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcoo-advisor%2Freferences%2Fscaling_playbook.md -->","isInternal":false,"tokens":5698,"sizeBytes":24048},{"name":"SKILL.md","path":"c-level-advisor/skills/coo-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/coo-advisor/SKILL.md","title":"coo-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcoo-advisor%2FSKILL.md -->","frontmatter":{"name":"coo-advisor","description":"Operations leadership for scaling companies. Process design, OKR execution, operational cadence, and scaling playbooks. Use when designing operations, setting up OKRs, building processes, scaling teams, analyzing bottlenecks, planning operational cadence, or when user mentions COO, operations, process improvement, OKRs, scaling, operational efficiency, or execution.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"coo-leadership","updated":"2026-03-05","python-tools":"ops_efficiency_analyzer.py, okr_tracker.py","frameworks":"scaling-playbook, ops-cadence, process-frameworks"}},"isInternal":false,"tokens":1470,"sizeBytes":6452},{"name":"pmf_playbook.md","path":"c-level-advisor/skills/cpo-advisor/references/pmf_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cpo-advisor/references/pmf_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcpo-advisor%2Freferences%2Fpmf_playbook.md -->","isInternal":false,"tokens":2853,"sizeBytes":11877},{"name":"product_org_design.md","path":"c-level-advisor/skills/cpo-advisor/references/product_org_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cpo-advisor/references/product_org_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcpo-advisor%2Freferences%2Fproduct_org_design.md -->","isInternal":false,"tokens":3484,"sizeBytes":15025},{"name":"product_strategy.md","path":"c-level-advisor/skills/cpo-advisor/references/product_strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cpo-advisor/references/product_strategy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcpo-advisor%2Freferences%2Fproduct_strategy.md -->","isInternal":false,"tokens":3997,"sizeBytes":16866},{"name":"SKILL.md","path":"c-level-advisor/skills/cpo-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cpo-advisor/SKILL.md","title":"cpo-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcpo-advisor%2FSKILL.md -->","frontmatter":{"name":"cpo-advisor","description":"Product leadership for scaling companies. Product vision, portfolio strategy, product-market fit, and product org design. Use when setting product vision, managing a product portfolio, measuring PMF, designing product teams, prioritizing at the portfolio level, reporting to the board on product, or when user mentions CPO, product strategy, product-market fit, product organization, portfolio prioritization, or roadmap strategy.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"cpo-leadership","updated":"2026-03-05","python-tools":"pmf_scorer.py, portfolio_analyzer.py","frameworks":"pmf-playbook, product-strategy, product-org-design"}},"isInternal":false,"tokens":2082,"sizeBytes":9090},{"name":"nrr_playbook.md","path":"c-level-advisor/skills/cro-advisor/references/nrr_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cro-advisor/references/nrr_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcro-advisor%2Freferences%2Fnrr_playbook.md -->","isInternal":false,"tokens":3843,"sizeBytes":15504},{"name":"pricing_strategy.md","path":"c-level-advisor/skills/cro-advisor/references/pricing_strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cro-advisor/references/pricing_strategy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcro-advisor%2Freferences%2Fpricing_strategy.md -->","isInternal":false,"tokens":3603,"sizeBytes":15234},{"name":"sales_playbook.md","path":"c-level-advisor/skills/cro-advisor/references/sales_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cro-advisor/references/sales_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcro-advisor%2Freferences%2Fsales_playbook.md -->","isInternal":false,"tokens":4171,"sizeBytes":16845},{"name":"SKILL.md","path":"c-level-advisor/skills/cro-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cro-advisor/SKILL.md","title":"cro-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcro-advisor%2FSKILL.md -->","frontmatter":{"name":"cro-advisor","description":"Revenue leadership for B2B SaaS companies. Revenue forecasting, sales model design, pricing strategy, net revenue retention, and sales team scaling. Use when designing the revenue engine, setting quotas, modeling NRR, evaluating pricing, building board forecasts, or when user mentions CRO, chief revenue officer, revenue strategy, sales model, ARR growth, NRR, expansion revenue, churn, pricing strategy, or sales capacity.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"cro-leadership","updated":"2026-03-05","python-tools":"revenue_forecast_model.py, churn_analyzer.py","frameworks":"sales-playbook, pricing-strategy, nrr-playbook"}},"isInternal":false,"tokens":2122,"sizeBytes":8876},{"name":"interview-guide.md","path":"c-level-advisor/skills/cs-onboard/references/interview-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cs-onboard/references/interview-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcs-onboard%2Freferences%2Finterview-guide.md -->","isInternal":false,"tokens":1757,"sizeBytes":7747},{"name":"SKILL.md","path":"c-level-advisor/skills/cs-onboard/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cs-onboard/SKILL.md","title":"cs-onboard","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcs-onboard%2FSKILL.md -->","frontmatter":{"name":"cs-onboard","description":"Founder onboarding interview that captures company context across 7 dimensions. Invoke with /cs-onboard setup for initial interview or /cs-onboard update for quarterly refresh. Generates ~/.claude/company-context.md used by all C-suite advisor skills. Use when setting up the C-suite advisors for the first time, or when company context is missing or more than 90 days old — e.g. after a fundraise or pivot.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"orchestration","updated":"2026-03-05","frameworks":"founder-interview, context-capture, quarterly-refresh"}},"isInternal":false,"tokens":1125,"sizeBytes":4845},{"name":"company-context-template.md","path":"c-level-advisor/skills/cs-onboard/templates/company-context-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cs-onboard/templates/company-context-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcs-onboard%2Ftemplates%2Fcompany-context-template.md -->","isInternal":false,"tokens":785,"sizeBytes":3100},{"name":"architecture_decision_records.md","path":"c-level-advisor/skills/cto-advisor/references/architecture_decision_records.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cto-advisor/references/architecture_decision_records.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcto-advisor%2Freferences%2Farchitecture_decision_records.md -->","isInternal":false,"tokens":2039,"sizeBytes":8716},{"name":"engineering_metrics.md","path":"c-level-advisor/skills/cto-advisor/references/engineering_metrics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cto-advisor/references/engineering_metrics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcto-advisor%2Freferences%2Fengineering_metrics.md -->","isInternal":false,"tokens":2961,"sizeBytes":12365},{"name":"technology_evaluation_framework.md","path":"c-level-advisor/skills/cto-advisor/references/technology_evaluation_framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cto-advisor/references/technology_evaluation_framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcto-advisor%2Freferences%2Ftechnology_evaluation_framework.md -->","isInternal":false,"tokens":2499,"sizeBytes":9875},{"name":"SKILL.md","path":"c-level-advisor/skills/cto-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/cto-advisor/SKILL.md","title":"cto-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fcto-advisor%2FSKILL.md -->","frontmatter":{"name":"cto-advisor","description":"Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.","license":"MIT","metadata":{"version":"2.0.0","author":"Alireza Rezvani","category":"c-level","domain":"cto-leadership","updated":"2026-03-05","python-tools":"tech_debt_analyzer.py, team_scaling_calculator.py","frameworks":"architecture-decisions, engineering-metrics, technology-evaluation"}},"isInternal":false,"tokens":2751,"sizeBytes":11982},{"name":"culture-playbook.md","path":"c-level-advisor/skills/culture-architect/references/culture-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/culture-architect/references/culture-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fculture-architect%2Freferences%2Fculture-playbook.md -->","isInternal":false,"tokens":2795,"sizeBytes":12449},{"name":"SKILL.md","path":"c-level-advisor/skills/culture-architect/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/culture-architect/SKILL.md","title":"culture-architect","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fculture-architect%2FSKILL.md -->","frontmatter":{"name":"culture-architect","description":"Build, measure, and evolve company culture as operational behavior — not wall posters. Covers mission/vision/values workshops, values-to-behaviors translation, culture code creation, culture health assessment, and cultural rituals by stage. Use when building company values, assessing culture health, designing cultural rituals, creating culture codes, handling culture clashes, or when user mentions culture, values, culture debt, founder culture, or culture code.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"culture-leadership","updated":"2026-03-05","frameworks":"culture-playbook, culture-code-template"}},"isInternal":false,"tokens":1934,"sizeBytes":8619},{"name":"culture-code-template.md","path":"c-level-advisor/skills/culture-architect/templates/culture-code-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/culture-architect/templates/culture-code-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fculture-architect%2Ftemplates%2Fculture-code-template.md -->","isInternal":false,"tokens":1102,"sizeBytes":4833},{"name":"SKILL.md","path":"c-level-advisor/skills/decision-logger/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/decision-logger/SKILL.md","title":"decision-logger","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fdecision-logger%2FSKILL.md -->","frontmatter":{"name":"decision-logger","description":"Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging decisions after a board meeting, reviewing past decisions with /decision-logger decisions, or checking overdue action items with /decision-logger review. Invoked automatically by the board-meeting skill after Phase 5 founder approval.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"decision-memory","updated":"2026-03-05","python-tools":"scripts/decision_tracker.py"}},"isInternal":false,"tokens":1420,"sizeBytes":5794},{"name":"decision-entry.md","path":"c-level-advisor/skills/decision-logger/templates/decision-entry.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/decision-logger/templates/decision-entry.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fdecision-logger%2Ftemplates%2Fdecision-entry.md -->","isInternal":false,"tokens":578,"sizeBytes":2316},{"name":"founder-toolkit.md","path":"c-level-advisor/skills/founder-coach/references/founder-toolkit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/founder-coach/references/founder-toolkit.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Ffounder-coach%2Freferences%2Ffounder-toolkit.md -->","isInternal":false,"tokens":2199,"sizeBytes":9406},{"name":"leadership-growth.md","path":"c-level-advisor/skills/founder-coach/references/leadership-growth.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/founder-coach/references/leadership-growth.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Ffounder-coach%2Freferences%2Fleadership-growth.md -->","isInternal":false,"tokens":1896,"sizeBytes":8666},{"name":"SKILL.md","path":"c-level-advisor/skills/founder-coach/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/founder-coach/SKILL.md","title":"founder-coach","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Ffounder-coach%2FSKILL.md -->","frontmatter":{"name":"founder-coach","description":"Personal leadership development for founders and first-time CEOs. Covers founder archetype identification, delegation frameworks, energy management, CEO calendar audits, leadership style evolution, blind spot identification, imposter syndrome, founder mental health, and succession planning. Use when a founder feels like the bottleneck, struggles to delegate, is burning out, transitioning from IC to executive, managing a board, or when user mentions founder mode, CEO growth, leadership development, delegation, burnout, or imposter syndrome.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"founder-development","updated":"2026-03-05","frameworks":"leadership-growth, founder-toolkit"}},"isInternal":false,"tokens":3182,"sizeBytes":14192},{"name":"contracts_playbook.md","path":"c-level-advisor/skills/general-counsel-advisor/references/contracts_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/general-counsel-advisor/references/contracts_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fgeneral-counsel-advisor%2Freferences%2Fcontracts_playbook.md -->","isInternal":false,"tokens":1781,"sizeBytes":7861},{"name":"ip_and_regulatory.md","path":"c-level-advisor/skills/general-counsel-advisor/references/ip_and_regulatory.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/general-counsel-advisor/references/ip_and_regulatory.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fgeneral-counsel-advisor%2Freferences%2Fip_and_regulatory.md -->","isInternal":false,"tokens":2439,"sizeBytes":10746},{"name":"term_sheet_decoder.md","path":"c-level-advisor/skills/general-counsel-advisor/references/term_sheet_decoder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/general-counsel-advisor/references/term_sheet_decoder.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fgeneral-counsel-advisor%2Freferences%2Fterm_sheet_decoder.md -->","isInternal":false,"tokens":2676,"sizeBytes":11893},{"name":"SKILL.md","path":"c-level-advisor/skills/general-counsel-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/general-counsel-advisor/SKILL.md","title":"general-counsel-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fgeneral-counsel-advisor%2FSKILL.md -->","frontmatter":{"name":"general-counsel-advisor","description":"General Counsel advisory for startups: contract review (MSA, SaaS, NDA, DPA, employment), IP strategy, term sheet decoding, and regulatory landscape mapping. Use when reviewing any contract or term sheet, deciding when to engage outside counsel, defining IP strategy, evaluating regulatory exposure (HIPAA, GDPR, FDA, fintech), or when user mentions general counsel, GC, legal review, contract risk, term sheet, IP assignment, or regulatory exposure. NOT a substitute for licensed counsel — surfaces questions to bring to qualified attorneys.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"general-counsel-leadership","updated":"2026-05-12","python-tools":"contract_risk_scanner.py, term_sheet_analyzer.py","frameworks":"contract-review, ip-strategy, term-sheet-decoding, regulatory-mapping"}},"isInternal":false,"tokens":2192,"sizeBytes":9120},{"name":"narrative-frameworks.md","path":"c-level-advisor/skills/internal-narrative/references/narrative-frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/internal-narrative/references/narrative-frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Finternal-narrative%2Freferences%2Fnarrative-frameworks.md -->","isInternal":false,"tokens":2399,"sizeBytes":10442},{"name":"SKILL.md","path":"c-level-advisor/skills/internal-narrative/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/internal-narrative/SKILL.md","title":"internal-narrative","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Finternal-narrative%2FSKILL.md -->","frontmatter":{"name":"internal-narrative","description":"Build and maintain one coherent company story across all audiences — employees, investors, customers, candidates, and partners. Detects narrative contradictions and ensures the same truth is framed for each audience's needs. Use when preparing investor updates, all-hands presentations, board communications, recruiting narratives, crisis communications, or when user mentions company narrative, messaging consistency, storytelling, all-hands, investor update, or crisis communication.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"narrative-strategy","updated":"2026-03-05","frameworks":"narrative-frameworks, all-hands-template"}},"isInternal":false,"tokens":2265,"sizeBytes":10629},{"name":"all-hands-template.md","path":"c-level-advisor/skills/internal-narrative/templates/all-hands-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/internal-narrative/templates/all-hands-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Finternal-narrative%2Ftemplates%2Fall-hands-template.md -->","isInternal":false,"tokens":926,"sizeBytes":3778},{"name":"market-entry-playbook.md","path":"c-level-advisor/skills/intl-expansion/references/market-entry-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/intl-expansion/references/market-entry-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fintl-expansion%2Freferences%2Fmarket-entry-playbook.md -->","isInternal":false,"tokens":1506,"sizeBytes":6282},{"name":"regional-guide.md","path":"c-level-advisor/skills/intl-expansion/references/regional-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/intl-expansion/references/regional-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fintl-expansion%2Freferences%2Fregional-guide.md -->","isInternal":false,"tokens":1321,"sizeBytes":6059},{"name":"SKILL.md","path":"c-level-advisor/skills/intl-expansion/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/intl-expansion/SKILL.md","title":"intl-expansion","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fintl-expansion%2FSKILL.md -->","frontmatter":{"name":"intl-expansion","description":"International market expansion strategy. Market selection, entry modes, localization, regulatory compliance, and go-to-market by region. Use when expanding to new countries, evaluating international markets, planning localization, or building regional teams.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"international-strategy","updated":"2026-03-05"}},"isInternal":false,"tokens":1016,"sizeBytes":4548},{"name":"due-diligence-checklist.md","path":"c-level-advisor/skills/ma-playbook/references/due-diligence-checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ma-playbook/references/due-diligence-checklist.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fma-playbook%2Freferences%2Fdue-diligence-checklist.md -->","isInternal":false,"tokens":1155,"sizeBytes":4943},{"name":"integration-playbook.md","path":"c-level-advisor/skills/ma-playbook/references/integration-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ma-playbook/references/integration-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fma-playbook%2Freferences%2Fintegration-playbook.md -->","isInternal":false,"tokens":1317,"sizeBytes":5733},{"name":"SKILL.md","path":"c-level-advisor/skills/ma-playbook/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/ma-playbook/SKILL.md","title":"ma-playbook","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fma-playbook%2FSKILL.md -->","frontmatter":{"name":"ma-playbook","description":"M&A strategy for acquiring companies or being acquired. Due diligence, valuation, integration, and deal structure. Use when evaluating acquisitions, preparing for acquisition, M&A due diligence, integration planning, or deal negotiation.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"ma-strategy","updated":"2026-03-05"}},"isInternal":false,"tokens":1376,"sizeBytes":6121},{"name":"health-benchmarks.md","path":"c-level-advisor/skills/org-health-diagnostic/references/health-benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/org-health-diagnostic/references/health-benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Forg-health-diagnostic%2Freferences%2Fhealth-benchmarks.md -->","isInternal":false,"tokens":2793,"sizeBytes":9094},{"name":"SKILL.md","path":"c-level-advisor/skills/org-health-diagnostic/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/org-health-diagnostic/SKILL.md","title":"org-health-diagnostic","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Forg-health-diagnostic%2FSKILL.md -->","frontmatter":{"name":"org-health-diagnostic","description":"Cross-functional organizational health check combining signals from all C-suite roles. Scores 8 dimensions on a traffic-light scale with drill-down recommendations. Use when assessing overall company health, preparing for board reviews, identifying at-risk functions, or when user mentions org health, health check, or health dashboard.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"organizational-health","updated":"2026-03-05","python-tools":"health_scorer.py","frameworks":"health-benchmarks"}},"isInternal":false,"tokens":2381,"sizeBytes":8601},{"name":"scenario-planning.md","path":"c-level-advisor/skills/scenario-war-room/references/scenario-planning.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/scenario-war-room/references/scenario-planning.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fscenario-war-room%2Freferences%2Fscenario-planning.md -->","isInternal":false,"tokens":1944,"sizeBytes":8011},{"name":"SKILL.md","path":"c-level-advisor/skills/scenario-war-room/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/scenario-war-room/SKILL.md","title":"scenario-war-room","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fscenario-war-room%2FSKILL.md -->","frontmatter":{"name":"scenario-war-room","description":"Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all business functions simultaneously. Use when facing complex risk scenarios, strategic decisions with major downside, or when the user asks 'what if X AND Y both happen?'","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"strategic-planning","updated":"2026-03-05","python-tools":"scenario_modeler.py","frameworks":"scenario-planning"}},"isInternal":false,"tokens":1988,"sizeBytes":8027},{"name":"alignment-playbook.md","path":"c-level-advisor/skills/strategic-alignment/references/alignment-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/strategic-alignment/references/alignment-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fstrategic-alignment%2Freferences%2Falignment-playbook.md -->","isInternal":false,"tokens":1831,"sizeBytes":8606},{"name":"SKILL.md","path":"c-level-advisor/skills/strategic-alignment/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/strategic-alignment/SKILL.md","title":"strategic-alignment","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fstrategic-alignment%2FSKILL.md -->","frontmatter":{"name":"strategic-alignment","description":"Cascades strategy from boardroom to individual contributor. Detects and fixes misalignment between company goals and team execution. Covers strategy articulation, cascade mapping, orphan goal detection, silo identification, communication gap analysis, and realignment protocols. Use when teams are pulling in different directions, OKRs don't connect, departments optimize locally at company expense, or when user mentions alignment, strategy cascade, silo, conflicting OKRs, or strategy communication.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"strategic-alignment","updated":"2026-03-05","python-tools":"alignment_checker.py","frameworks":"alignment-playbook"}},"isInternal":false,"tokens":2084,"sizeBytes":9462},{"name":"delivery_throughput.md","path":"c-level-advisor/skills/vpe-advisor/references/delivery_throughput.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/vpe-advisor/references/delivery_throughput.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Fdelivery_throughput.md -->","isInternal":false,"tokens":1718,"sizeBytes":7327},{"name":"eng_team_structure.md","path":"c-level-advisor/skills/vpe-advisor/references/eng_team_structure.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/vpe-advisor/references/eng_team_structure.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Feng_team_structure.md -->","isInternal":false,"tokens":1923,"sizeBytes":7950},{"name":"engineering_hiring_funnel.md","path":"c-level-advisor/skills/vpe-advisor/references/engineering_hiring_funnel.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/vpe-advisor/references/engineering_hiring_funnel.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Fengineering_hiring_funnel.md -->","isInternal":false,"tokens":1920,"sizeBytes":8312},{"name":"production_discipline.md","path":"c-level-advisor/skills/vpe-advisor/references/production_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/vpe-advisor/references/production_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Fproduction_discipline.md -->","isInternal":false,"tokens":1905,"sizeBytes":8002},{"name":"SKILL.md","path":"c-level-advisor/skills/vpe-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/skills/vpe-advisor/SKILL.md","title":"vpe-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fskills%2Fvpe-advisor%2FSKILL.md -->","frontmatter":{"name":"vpe-advisor","description":"VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and production discipline (on-call, deployment cadence, postmortem culture). Use when sprint velocity is dropping, eng hiring is broken, team structure is unclear, or deciding when to add a tech-lead manager. NOT a CTO skill (which owns architecture) — VPE owns delivery operations and how the team ships.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"vp-engineering-leadership","updated":"2026-05-13","python-tools":"delivery_throughput_analyzer.py, eng_hiring_funnel_calculator.py, eng_team_structure_designer.py","frameworks":"delivery-throughput, hiring-funnel, team-structure, production-discipline"}},"isInternal":false,"tokens":3248,"sizeBytes":13411},{"name":"delivery_throughput.md","path":"c-level-advisor/vpe-advisor/skills/vpe-advisor/references/delivery_throughput.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/vpe-advisor/skills/vpe-advisor/references/delivery_throughput.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fvpe-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Fdelivery_throughput.md -->","isInternal":false,"tokens":1718,"sizeBytes":7327},{"name":"eng_team_structure.md","path":"c-level-advisor/vpe-advisor/skills/vpe-advisor/references/eng_team_structure.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/vpe-advisor/skills/vpe-advisor/references/eng_team_structure.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fvpe-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Feng_team_structure.md -->","isInternal":false,"tokens":1923,"sizeBytes":7950},{"name":"engineering_hiring_funnel.md","path":"c-level-advisor/vpe-advisor/skills/vpe-advisor/references/engineering_hiring_funnel.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/vpe-advisor/skills/vpe-advisor/references/engineering_hiring_funnel.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fvpe-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Fengineering_hiring_funnel.md -->","isInternal":false,"tokens":1920,"sizeBytes":8312},{"name":"production_discipline.md","path":"c-level-advisor/vpe-advisor/skills/vpe-advisor/references/production_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/vpe-advisor/skills/vpe-advisor/references/production_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fvpe-advisor%2Fskills%2Fvpe-advisor%2Freferences%2Fproduction_discipline.md -->","isInternal":false,"tokens":1905,"sizeBytes":8002},{"name":"SKILL.md","path":"c-level-advisor/vpe-advisor/skills/vpe-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/vpe-advisor/skills/vpe-advisor/SKILL.md","title":"vpe-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fvpe-advisor%2Fskills%2Fvpe-advisor%2FSKILL.md -->","frontmatter":{"name":"vpe-advisor","description":"VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and production discipline (on-call, deployment cadence, postmortem culture). Use when sprint velocity is dropping, eng hiring is broken, team structure is unclear, or deciding when to add a tech-lead manager. NOT a CTO skill (which owns architecture) — VPE owns delivery operations and how the team ships.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"vp-engineering-leadership","updated":"2026-05-13","python-tools":"delivery_throughput_analyzer.py, eng_hiring_funnel_calculator.py, eng_team_structure_designer.py","frameworks":"delivery-throughput, hiring-funnel, team-structure, production-discipline"}},"isInternal":false,"tokens":3248,"sizeBytes":13411},{"name":"SKILL.md","path":"c-level-agents/skills/boardroom/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/boardroom/SKILL.md","title":"boardroom","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fboardroom%2FSKILL.md -->","frontmatter":{"name":"boardroom","description":"/c-level-agents:boardroom [brief] — 6-phase multi-role deliberation across the C-suite with Phase 2 isolation, critic pre-screen, and synthesis. Outputs a board memo. Use when a decision spans multiple executive domains — e.g. a pricing change touching finance, positioning, and product, or a raise-vs-cut runway call."},"isInternal":false,"tokens":1295,"sizeBytes":4934},{"name":"SKILL.md","path":"c-level-agents/skills/brief/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/brief/SKILL.md","title":"brief","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fbrief%2FSKILL.md -->","frontmatter":{"name":"brief","description":"/c-level-agents:brief [topic] — Generate a one-page strategy brief from an office-hours intake. First step in the strategic sprint pipeline. Use when a strategic question needs to be framed before boardroom deliberation — e.g. locking options, assumptions, and success criteria for a pricing change or a market-entry decision."},"isInternal":false,"tokens":1091,"sizeBytes":4115},{"name":"SKILL.md","path":"c-level-agents/skills/c-level-agents/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/c-level-agents/SKILL.md","title":"c-level-agents","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fc-level-agents%2FSKILL.md -->","frontmatter":{"name":"c-level-agents","description":"Founder-mode executive team. 13 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, GC, CDO, CAIO, CCO, VPE, Chief of Staff) and 21 /c-level-agents:* slash commands for forcing-question office hours, multi-role boardroom deliberation, strategic sprint pipeline, and meta routing. Use when the founder needs a virtual executive team, when invoking /c-level-agents:* commands, or when orchestrating multi-role decisions.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"c-level","domain":"executive-orchestration","updated":"2026-05-12","agents":"cs-cfo-advisor, cs-cmo-advisor, cs-cro-advisor, cs-cpo-advisor, cs-coo-advisor, cs-chro-advisor, cs-ciso-advisor, cs-general-counsel-advisor, cs-cdo-advisor, cs-caio-advisor, cs-cco-advisor, cs-vpe-advisor, cs-chief-of-staff","commands":"cs-office-hours, cs-cfo-review, cs-cmo-review, cs-cpo-review, cs-cro-review, cs-cto-review, cs-ciso-review, cs-gc-review, cs-cdo-review, cs-caio-review, cs-cco-review, cs-vpe-review, cs-brief, cs-boardroom, cs-decide, cs-execute, cs-post-mortem, cs-founder-mode, cs-onboard, cs-cross-eval, cs-freeze"}},"isInternal":false,"tokens":1487,"sizeBytes":5567},{"name":"SKILL.md","path":"c-level-agents/skills/caio-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/caio-review/SKILL.md","title":"caio-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcaio-review%2FSKILL.md -->","frontmatter":{"name":"caio-review","description":"/c-level-agents:caio-review [plan] — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost economics, or AI hiring. Use when shipping an AI feature without an eval set, choosing between API, fine-tune, and self-hosted, or classifying a use case under the EU AI Act."},"isInternal":false,"tokens":1559,"sizeBytes":6192},{"name":"SKILL.md","path":"c-level-agents/skills/cco-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cco-review/SKILL.md","title":"cco-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcco-review%2FSKILL.md -->","frontmatter":{"name":"cco-review","description":"/c-level-agents:cco-review [plan] — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team sizing, or CS team hiring. Use when gross retention is slipping, before approving CSM headcount, or when deciding which customer segments to keep or fire."},"isInternal":false,"tokens":1417,"sizeBytes":5389},{"name":"SKILL.md","path":"c-level-agents/skills/cdo-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cdo-review/SKILL.md","title":"cdo-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcdo-review%2FSKILL.md -->","frontmatter":{"name":"cdo-review","description":"/c-level-agents:cdo-review [plan] — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data productization, or data team hiring. Use when validating training-data rights before model work, choosing warehouse vs lakehouse vs mesh, or valuing data assets for productization or M&A."},"isInternal":false,"tokens":1335,"sizeBytes":5328},{"name":"SKILL.md","path":"c-level-agents/skills/cfo-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cfo-review/SKILL.md","title":"cfo-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcfo-review%2FSKILL.md -->","frontmatter":{"name":"cfo-review","description":"/c-level-agents:cfo-review [plan] — Numerate-skeptic interrogation of any plan that touches money. Unit economics, runway, dilution, capital allocation. Use when a plan commits meaningful spend — e.g. a hiring wave, a fundraise decision, or a new channel budget."},"isInternal":false,"tokens":926,"sizeBytes":3441},{"name":"SKILL.md","path":"c-level-agents/skills/ciso-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/ciso-review/SKILL.md","title":"ciso-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fciso-review%2FSKILL.md -->","frontmatter":{"name":"ciso-review","description":"/c-level-agents:ciso-review [plan] — Risk-paranoid interrogation of any plan that touches data, compliance, or production access. Use when launching features that handle customer data, before a SOC 2 / ISO audit, or after any incident or near-miss."},"isInternal":false,"tokens":908,"sizeBytes":3381},{"name":"SKILL.md","path":"c-level-agents/skills/cmo-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cmo-review/SKILL.md","title":"cmo-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcmo-review%2FSKILL.md -->","frontmatter":{"name":"cmo-review","description":"/c-level-agents:cmo-review [plan] — Narrative-first interrogation of positioning, ICP, message house, and channel mix. Use when launching a campaign or repositioning, or when CAC is rising and the one-sentence positioning test fails."},"isInternal":false,"tokens":892,"sizeBytes":3378},{"name":"SKILL.md","path":"c-level-agents/skills/cpo-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cpo-review/SKILL.md","title":"cpo-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcpo-review%2FSKILL.md -->","frontmatter":{"name":"cpo-review","description":"/c-level-agents:cpo-review [plan] — JTBD-driven interrogation of product roadmap, PMF signal, and portfolio focus. Use when committing a quarter's roadmap, deciding whether to kill a feature, or claiming PMF without a retention curve."},"isInternal":false,"tokens":891,"sizeBytes":3310},{"name":"SKILL.md","path":"c-level-agents/skills/cro-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cro-review/SKILL.md","title":"cro-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcro-review%2FSKILL.md -->","frontmatter":{"name":"cro-review","description":"/c-level-agents:cro-review [plan] — Pipeline-paranoid interrogation of revenue, win rate, NRR, and ramp time. Use when the forecast misses pipeline coverage, win rates drop, or before scaling the sales team."},"isInternal":false,"tokens":872,"sizeBytes":3241},{"name":"SKILL.md","path":"c-level-agents/skills/cross-eval/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cross-eval/SKILL.md","title":"cross-eval","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcross-eval%2FSKILL.md -->","frontmatter":{"name":"cross-eval","description":"/c-level-agents:cross-eval [memo] — Multi-model consensus on a board memo or strategy brief. Claude + Codex + Gemini cross-review with graceful degradation. Use when a high-stakes memo needs an independent sanity check before the boardroom — e.g. a bet-the-company pivot or fundraise terms."},"isInternal":false,"tokens":1122,"sizeBytes":4430},{"name":"SKILL.md","path":"c-level-agents/skills/cto-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/cto-review/SKILL.md","title":"cto-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fcto-review%2FSKILL.md -->","frontmatter":{"name":"cto-review","description":"/c-level-agents:cto-review [plan] — Architecture and scaling interrogation. Tech debt, scaling cliffs, team scaling, build-vs-buy. Use when committing to an architecture, planning for 10x load, or weighing a rebuild against a vendor."},"isInternal":false,"tokens":954,"sizeBytes":3539},{"name":"SKILL.md","path":"c-level-agents/skills/decide/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/decide/SKILL.md","title":"decide","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fdecide%2FSKILL.md -->","frontmatter":{"name":"decide","description":"/c-level-agents:decide [memo] — Log a decision to two-layer memory via decision-logger. Approved memo becomes durable; raw transcripts kept for reference. Use when the founder has approved a boardroom memo and the decision must become durable company memory — e.g. right after /c-level-agents:boardroom concludes."},"isInternal":false,"tokens":956,"sizeBytes":3751},{"name":"SKILL.md","path":"c-level-agents/skills/execute/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/execute/SKILL.md","title":"execute","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fexecute%2FSKILL.md -->","frontmatter":{"name":"execute","description":"/c-level-agents:execute [decision] — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision. Use when a logged decision needs to become an operating plan — e.g. turning an approved market-entry call into weekly milestones with DRIs."},"isInternal":false,"tokens":977,"sizeBytes":3539},{"name":"SKILL.md","path":"c-level-agents/skills/founder-mode/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/founder-mode/SKILL.md","title":"founder-mode","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Ffounder-mode%2FSKILL.md -->","frontmatter":{"name":"founder-mode","description":"/c-level-agents:founder-mode [question] — Auto-routes any founder question to the right C-role advisor or to /c-level-agents:boardroom for multi-role topics. The single-command entry point. Use when a founder asks any strategic question without knowing which advisor or command fits — e.g. 'runway pressure' routes to the CFO, 'gross retention dropped' routes to the CCO."},"isInternal":false,"tokens":1302,"sizeBytes":4811},{"name":"SKILL.md","path":"c-level-agents/skills/freeze/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/freeze/SKILL.md","title":"freeze","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Ffreeze%2FSKILL.md -->","frontmatter":{"name":"freeze","description":"/c-level-agents:freeze [decision] [days] — Lock a strategic decision for a cooldown period to prevent impulse reversal. Mirrors gstack's safety primitives for the business layer. Use when an irreversible decision was made under pressure — e.g. a layoff plan or multi-year contract — and deserves a cooling-off lock before execution."},"isInternal":false,"tokens":945,"sizeBytes":3899},{"name":"SKILL.md","path":"c-level-agents/skills/gc-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/gc-review/SKILL.md","title":"gc-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fgc-review%2FSKILL.md -->","frontmatter":{"name":"gc-review","description":"/c-level-agents:gc-review [plan] — General Counsel interrogation of contracts, IP, regulatory, term sheets, and employment-law surface. Use when reviewing a term sheet before signing, redlining a customer MSA, or checking IP assignment and regulatory exposure on a new product."},"isInternal":false,"tokens":1236,"sizeBytes":4781},{"name":"SKILL.md","path":"c-level-agents/skills/office-hours/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/office-hours/SKILL.md","title":"office-hours","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Foffice-hours%2FSKILL.md -->","frontmatter":{"name":"office-hours","description":"/c-level-agents:office-hours [topic] — YC-style 6-question founder interrogation before any advice. Forces clarity on problem, customer, distribution, defensibility, capital, and founder fit. Use when a founder question is too vague to route — e.g. 'should we grow faster?' — or before drafting a strategy brief."},"isInternal":false,"tokens":972,"sizeBytes":3900},{"name":"SKILL.md","path":"c-level-agents/skills/onboard/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/onboard/SKILL.md","title":"onboard","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fonboard%2FSKILL.md -->","frontmatter":{"name":"onboard","description":"/cs-onboard — Founder interview that populates ~/.claude/company-context.md using the canonical 7-dimension cs-onboard schema. The first command to run when starting with c-level-agents. Use when setting up the virtual C-suite for a new company, or when advisors lack company context — e.g. before a first /c-level-agents:boardroom or after a fundraise changes the numbers."},"isInternal":false,"tokens":1365,"sizeBytes":5201},{"name":"SKILL.md","path":"c-level-agents/skills/post-mortem/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/post-mortem/SKILL.md","title":"post-mortem","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fpost-mortem%2FSKILL.md -->","frontmatter":{"name":"post-mortem","description":"/c-level-agents:post-mortem [decision] — Honest retrospective on an executed decision, scored against original assumptions and dissent. Closes the strategic sprint loop. Use when a decision hits its 90-day review checkpoint or its kill criteria trigger — e.g. scoring last quarter's pricing change against its pre-committed success metrics."},"isInternal":false,"tokens":1086,"sizeBytes":4130},{"name":"SKILL.md","path":"c-level-agents/skills/vpe-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/skills/vpe-review/SKILL.md","title":"vpe-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2Fskills%2Fvpe-review%2FSKILL.md -->","frontmatter":{"name":"vpe-review","description":"/c-level-agents:vpe-review [plan] — Throughput-first VP of Engineering interrogation of any plan that touches delivery, eng hiring, team structure, or production discipline. Use when cycle time balloons, DORA metrics slide, or before committing to an eng hiring wave or a reorg."},"isInternal":false,"tokens":1280,"sizeBytes":4963},{"name":"channel_data_template.md","path":"commercial/skills/channel-economics/assets/channel_data_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/channel-economics/assets/channel_data_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Fassets%2Fchannel_data_template.md -->","isInternal":false,"tokens":2119,"sizeBytes":8041},{"name":"channel_anti_patterns.md","path":"commercial/skills/channel-economics/references/channel_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/channel-economics/references/channel_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Freferences%2Fchannel_anti_patterns.md -->","isInternal":false,"tokens":1797,"sizeBytes":7847},{"name":"channel_economics_canon.md","path":"commercial/skills/channel-economics/references/channel_economics_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/channel-economics/references/channel_economics_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Freferences%2Fchannel_economics_canon.md -->","isInternal":false,"tokens":1425,"sizeBytes":5753},{"name":"cost_to_serve_canon.md","path":"commercial/skills/channel-economics/references/cost_to_serve_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/channel-economics/references/cost_to_serve_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2Freferences%2Fcost_to_serve_canon.md -->","isInternal":false,"tokens":1396,"sizeBytes":6696},{"name":"SKILL.md","path":"commercial/skills/channel-economics/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/channel-economics/SKILL.md","title":"channel-economics","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fchannel-economics%2FSKILL.md -->","frontmatter":{"name":"channel-economics","description":"Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation, and the diminishing-returns inflection (e.g., 'which channel actually makes money — direct or partner?').","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","channel-economics","cost-to-serve","channel-mix","channel-roi","direct-vs-partner","unit-economics"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3042,"sizeBytes":13425},{"name":"forecast_intake_template.md","path":"commercial/skills/commercial-forecaster/assets/forecast_intake_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-forecaster/assets/forecast_intake_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-forecaster%2Fassets%2Fforecast_intake_template.md -->","isInternal":false,"tokens":1759,"sizeBytes":6089},{"name":"cohort_analysis_canon.md","path":"commercial/skills/commercial-forecaster/references/cohort_analysis_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-forecaster/references/cohort_analysis_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-forecaster%2Freferences%2Fcohort_analysis_canon.md -->","isInternal":false,"tokens":1631,"sizeBytes":6570},{"name":"forecast_anti_patterns.md","path":"commercial/skills/commercial-forecaster/references/forecast_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-forecaster/references/forecast_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-forecaster%2Freferences%2Fforecast_anti_patterns.md -->","isInternal":false,"tokens":2152,"sizeBytes":8732},{"name":"saas_forecasting_canon.md","path":"commercial/skills/commercial-forecaster/references/saas_forecasting_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-forecaster/references/saas_forecasting_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-forecaster%2Freferences%2Fsaas_forecasting_canon.md -->","isInternal":false,"tokens":1760,"sizeBytes":7139},{"name":"SKILL.md","path":"commercial/skills/commercial-forecaster/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-forecaster/SKILL.md","title":"commercial-forecaster","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-forecaster%2FSKILL.md -->","frontmatter":{"name":"commercial-forecaster","description":"Use when building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board number — especially when the CRO needs to walk the board through funnel math + cohort ARR + per-stage conversion assumptions without the theatre of a single undefended number. Decomposes pipeline into commit, best-case, and pipe-only tiers; projects cohort-level NRR/GRR to surface leaky cohorts before they show up in the consolidated number; scores per-stage funnel confidence so soft-floor stages get treated differently from high-confidence ones. Every output explicitly names the conversion rate used, the data window, and the weighting choice. For Head of Commercial, RevOps, VP Sales, and CRO at quarterly forecast or board prep. NOT financial close (see finance/financial-analysis). NOT strategic CRO hiring/territory (see c-level-advisor/cro-advisor). NOT pricing (see sibling pricing-strategist).","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","forecasting","bookings","arr","nrr","grr","cohort","funnel","pipeline-math"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2895,"sizeBytes":12234},{"name":"policy_design_template.md","path":"commercial/skills/commercial-policy/assets/policy_design_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-policy/assets/policy_design_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-policy%2Fassets%2Fpolicy_design_template.md -->","isInternal":false,"tokens":1780,"sizeBytes":6751},{"name":"discount_governance_canon.md","path":"commercial/skills/commercial-policy/references/discount_governance_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-policy/references/discount_governance_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-policy%2Freferences%2Fdiscount_governance_canon.md -->","isInternal":false,"tokens":1888,"sizeBytes":8246},{"name":"policy_anti_patterns.md","path":"commercial/skills/commercial-policy/references/policy_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-policy/references/policy_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-policy%2Freferences%2Fpolicy_anti_patterns.md -->","isInternal":false,"tokens":2557,"sizeBytes":10766},{"name":"policy_design_canon.md","path":"commercial/skills/commercial-policy/references/policy_design_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-policy/references/policy_design_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-policy%2Freferences%2Fpolicy_design_canon.md -->","isInternal":false,"tokens":1697,"sizeBytes":7607},{"name":"SKILL.md","path":"commercial/skills/commercial-policy/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-policy/SKILL.md","title":"commercial-policy","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-policy%2FSKILL.md -->","frontmatter":{"name":"commercial-policy","description":"Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under. Covers discount matrix design (ARR band x term length x payment terms x strategic value), commercial policy design, exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces). For Head of Commercial, Head of Deal Desk, VP Sales, or RevOps at the policy-design moment — NOT per-deal application (that is deal-desk) and NOT pricing model selection (that is pricing-strategist).","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","discount-policy","discount-matrix","exception-flow","governance","deal-framework","commercial-discipline"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3357,"sizeBytes":14342},{"name":"SKILL.md","path":"commercial/skills/commercial-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/commercial-skills/SKILL.md","title":"commercial-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fcommercial-skills%2FSKILL.md -->","frontmatter":{"name":"commercial-skills","description":"Use when reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on \"review this deal\", \"should we discount\", \"pricing model\", \"partner economics\", \"RFP response\", \"bookings forecast\", \"channel mix\". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth (sales execution) and c-level-advisor/cro-advisor (strategic CRO judgment).","context":"fork","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","pricing","deal-desk","partnerships","channel","rfp","forecast","cro","orchestrator"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2259,"sizeBytes":9261},{"name":"deal_intake_template.md","path":"commercial/skills/deal-desk/assets/deal_intake_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/deal-desk/assets/deal_intake_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fdeal-desk%2Fassets%2Fdeal_intake_template.md -->","isInternal":false,"tokens":1406,"sizeBytes":4909},{"name":"contract_landmines.md","path":"commercial/skills/deal-desk/references/contract_landmines.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/deal-desk/references/contract_landmines.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fdeal-desk%2Freferences%2Fcontract_landmines.md -->","isInternal":false,"tokens":2068,"sizeBytes":9221},{"name":"deal_desk_canon.md","path":"commercial/skills/deal-desk/references/deal_desk_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/deal-desk/references/deal_desk_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fdeal-desk%2Freferences%2Fdeal_desk_canon.md -->","isInternal":false,"tokens":1210,"sizeBytes":5256},{"name":"discount_economics.md","path":"commercial/skills/deal-desk/references/discount_economics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/deal-desk/references/discount_economics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fdeal-desk%2Freferences%2Fdiscount_economics.md -->","isInternal":false,"tokens":1554,"sizeBytes":6214},{"name":"SKILL.md","path":"commercial/skills/deal-desk/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/deal-desk/SKILL.md","title":"deal-desk","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fdeal-desk%2FSKILL.md -->","frontmatter":{"name":"deal-desk","description":"Use when reviewing a specific inbound deal before close — when sales has asked for a discount that exceeds AE authority, when the customer has redlined the MSA, when per-deal economics (margin after discount, multi-year payment shape, indemnity exposure) need to be quantified, or when discount approval needs to be routed to a named human approver (Sales Director, VP Sales, CFO, CRO, General Counsel). Covers deal review, discount approval routing, per-deal margin scoring, deal exception handling, MSA redline triage, contract landmine detection (uncapped indemnity, MFN, perpetual license-back, missing DPA), and named-approver chain assembly. NEVER auto-approves — every output is a numeric scorecard plus a routing recommendation to a named human.","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","deal-desk","discount","margin","approval","redline","msa","terms"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2730,"sizeBytes":11343},{"name":"partnership_intake_template.md","path":"commercial/skills/partnerships-architect/assets/partnership_intake_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/partnerships-architect/assets/partnership_intake_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpartnerships-architect%2Fassets%2Fpartnership_intake_template.md -->","isInternal":false,"tokens":1174,"sizeBytes":4756},{"name":"channel_partner_canon.md","path":"commercial/skills/partnerships-architect/references/channel_partner_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/partnerships-architect/references/channel_partner_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpartnerships-architect%2Freferences%2Fchannel_partner_canon.md -->","isInternal":false,"tokens":1635,"sizeBytes":7267},{"name":"joint_gtm_canon.md","path":"commercial/skills/partnerships-architect/references/joint_gtm_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/partnerships-architect/references/joint_gtm_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpartnerships-architect%2Freferences%2Fjoint_gtm_canon.md -->","isInternal":false,"tokens":1641,"sizeBytes":6966},{"name":"partnership_anti_patterns.md","path":"commercial/skills/partnerships-architect/references/partnership_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/partnerships-architect/references/partnership_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpartnerships-architect%2Freferences%2Fpartnership_anti_patterns.md -->","isInternal":false,"tokens":1979,"sizeBytes":8822},{"name":"SKILL.md","path":"commercial/skills/partnerships-architect/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/partnerships-architect/SKILL.md","title":"partnerships-architect","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpartnerships-architect%2FSKILL.md -->","frontmatter":{"name":"partnerships-architect","description":"Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic alliance review — not technical sale enablement, not channel cost economics, not M&A.","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","partnerships","channel-partners","joint-gtm","revshare","oem","reseller","strategic-alliance"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2926,"sizeBytes":12962},{"name":"pricing_brief_template.md","path":"commercial/skills/pricing-strategist/assets/pricing_brief_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/pricing-strategist/assets/pricing_brief_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpricing-strategist%2Fassets%2Fpricing_brief_template.md -->","isInternal":false,"tokens":909,"sizeBytes":3396},{"name":"packaging_anti_patterns.md","path":"commercial/skills/pricing-strategist/references/packaging_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/pricing-strategist/references/packaging_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpricing-strategist%2Freferences%2Fpackaging_anti_patterns.md -->","isInternal":false,"tokens":1470,"sizeBytes":6152},{"name":"saas_pricing_canon.md","path":"commercial/skills/pricing-strategist/references/saas_pricing_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/pricing-strategist/references/saas_pricing_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpricing-strategist%2Freferences%2Fsaas_pricing_canon.md -->","isInternal":false,"tokens":1245,"sizeBytes":5217},{"name":"van_westendorp_methodology.md","path":"commercial/skills/pricing-strategist/references/van_westendorp_methodology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/pricing-strategist/references/van_westendorp_methodology.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpricing-strategist%2Freferences%2Fvan_westendorp_methodology.md -->","isInternal":false,"tokens":1531,"sizeBytes":6579},{"name":"SKILL.md","path":"commercial/skills/pricing-strategist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/pricing-strategist/SKILL.md","title":"pricing-strategist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Fpricing-strategist%2FSKILL.md -->","frontmatter":{"name":"pricing-strategist","description":"Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","pricing","packaging","wtp","van-westendorp","value-based-pricing","saas-pricing"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2253,"sizeBytes":9361},{"name":"rfp_intake_template.md","path":"commercial/skills/rfp-responder/assets/rfp_intake_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/rfp-responder/assets/rfp_intake_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Frfp-responder%2Fassets%2Frfp_intake_template.md -->","isInternal":false,"tokens":1221,"sizeBytes":4612},{"name":"rfp_anti_patterns.md","path":"commercial/skills/rfp-responder/references/rfp_anti_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/rfp-responder/references/rfp_anti_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Frfp-responder%2Freferences%2Frfp_anti_patterns.md -->","isInternal":false,"tokens":2004,"sizeBytes":9055},{"name":"rfp_strategy_canon.md","path":"commercial/skills/rfp-responder/references/rfp_strategy_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/rfp-responder/references/rfp_strategy_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Frfp-responder%2Freferences%2Frfp_strategy_canon.md -->","isInternal":false,"tokens":1380,"sizeBytes":5862},{"name":"shipley_method_canon.md","path":"commercial/skills/rfp-responder/references/shipley_method_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/rfp-responder/references/shipley_method_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Frfp-responder%2Freferences%2Fshipley_method_canon.md -->","isInternal":false,"tokens":1261,"sizeBytes":5758},{"name":"SKILL.md","path":"commercial/skills/rfp-responder/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/skills/rfp-responder/SKILL.md","title":"rfp-responder","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2Fskills%2Frfp-responder%2FSKILL.md -->","frontmatter":{"name":"rfp-responder","description":"Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.","context":"fork","license":"MIT","metadata":{"version":"2.8.0","author":"claude-code-skills","tags":["commercial","rfp","rfi","rfq","shipley","win-theme","proof-points","structured-response","bid-management"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":3027,"sizeBytes":12968},{"name":"SKILL.md","path":"compliance-os/skills/ai-act-readiness/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/ai-act-readiness/SKILL.md","title":"ai-act-readiness","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Fai-act-readiness%2FSKILL.md -->","frontmatter":{"name":"ai-act-readiness","description":"/compliance-os:ai-act-readiness [system] — EU AI Act 6-question forcing interrogation. Use during AI-system intake, before EU deployment, or during annual compliance refresh as Article 113 obligations phase in (2025-02-02 / 2025-08-02 / 2026-08-02 / 2027-08-02)."},"isInternal":false,"tokens":1939,"sizeBytes":7427},{"name":"SKILL.md","path":"compliance-os/skills/aims-audit/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/aims-audit/SKILL.md","title":"aims-audit","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Faims-audit%2FSKILL.md -->","frontmatter":{"name":"aims-audit","description":"/compliance-os:aims-audit [scope] — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. 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Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario library? (4) Across selected frameworks, what's the unified evidence checklist with reuse map? Use when standing up a multi-framework program, planning the annual audit calendar, or preparing for certification stage 1. Does NOT replace per-framework skills (it orchestrates them).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"compliance-os","domain":"multi-framework-compliance-orchestration","updated":"2026-05-13","python-tools":"framework_selector.py, cross_framework_mapper.py, audit_simulator.py, evidence_pool_generator.py","frameworks":"iso-27001, iso-13485, iso-42001, iso-14971, eu-ai-act, eu-mdr-745, gdpr, soc-2, fda-qsr, nist-csf, nis2, hipaa"}},"isInternal":false,"tokens":3118,"sizeBytes":13416},{"name":"SKILL.md","path":"compliance-os/skills/compliance-readiness/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/compliance-readiness/SKILL.md","title":"compliance-readiness","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Fcompliance-readiness%2FSKILL.md -->","frontmatter":{"name":"compliance-readiness","description":"/compliance-os:compliance-readiness [program] — Multi-framework compliance officer 6-question forcing interrogation of any compliance program. Use before starting a new framework, planning the annual audit calendar, or preparing for certification stage 1."},"isInternal":false,"tokens":1368,"sizeBytes":5769},{"name":"SKILL.md","path":"compliance-os/skills/fda-qsr-audit-prep/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/fda-qsr-audit-prep/SKILL.md","title":"fda-qsr-audit-prep","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Ffda-qsr-audit-prep%2FSKILL.md -->","frontmatter":{"name":"fda-qsr-audit-prep","description":"/compliance-os:fda-qsr-audit-prep [scope] — FDA 21 CFR 820 (QSR / QMSR) audit 6-question forcing interrogation. Post-Feb 2026 substantially harmonized with ISO 13485. Use before annual internal QSR audit, pre-FDA-inspection readiness, or Form 483 response."},"isInternal":false,"tokens":1688,"sizeBytes":6576},{"name":"SKILL.md","path":"compliance-os/skills/gdpr-audit-prep/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/gdpr-audit-prep/SKILL.md","title":"gdpr-audit-prep","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Fgdpr-audit-prep%2FSKILL.md -->","frontmatter":{"name":"gdpr-audit-prep","description":"/compliance-os:gdpr-audit-prep [scope] — GDPR audit 6-question Article-cited forcing interrogation. Use before annual internal GDPR review, post-breach internal audit, DPA investigation readiness, or acquisition due diligence."},"isInternal":false,"tokens":1796,"sizeBytes":6984},{"name":"SKILL.md","path":"compliance-os/skills/iso13485-audit-prep/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/iso13485-audit-prep/SKILL.md","title":"iso13485-audit-prep","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Fiso13485-audit-prep%2FSKILL.md -->","frontmatter":{"name":"iso13485-audit-prep","description":"/compliance-os:iso13485-audit-prep [scope] — ISO 13485 QMS audit 6-question forcing interrogation. Design controls + CAPA + post-market focused. Use before Clause 8.2.4 internal audit, MDR / FDA QSR alignment review, or product-launch DHF closure audit."},"isInternal":false,"tokens":1741,"sizeBytes":6878},{"name":"SKILL.md","path":"compliance-os/skills/iso27001-audit-prep/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/iso27001-audit-prep/SKILL.md","title":"iso27001-audit-prep","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Fiso27001-audit-prep%2FSKILL.md -->","frontmatter":{"name":"iso27001-audit-prep","description":"/compliance-os:iso27001-audit-prep [scope] — ISO 27001 ISMS audit readiness 6-question forcing interrogation. Use before annual Clause 9.2 internal audit, surveillance audit prep, or stage 1 certification readiness."},"isInternal":false,"tokens":1558,"sizeBytes":5848},{"name":"SKILL.md","path":"compliance-os/skills/soc2-audit-prep/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/skills/soc2-audit-prep/SKILL.md","title":"soc2-audit-prep","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2Fskills%2Fsoc2-audit-prep%2FSKILL.md -->","frontmatter":{"name":"soc2-audit-prep","description":"/compliance-os:soc2-audit-prep [scope] — SOC 2 Type II readiness 6-question forcing interrogation. Observation-period focused. Use before Type II observation begins, mid-period checkpoint, or pre-field-test month-10 readiness."},"isInternal":false,"tokens":1538,"sizeBytes":6244},{"name":"index.md","path":"docs/plugins/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/plugins/index.md","title":"Plugins Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fplugins%2Findex.md -->","frontmatter":{"title":"Claude Code Plugin Marketplace — 78 Agent Plugins","description":"78 installable agent plugins for Claude Code, Codex CLI, Gemini CLI, and OpenClaw. 14 domain bundles + 64 standalone packages covering engineering, marketing, product, C-level advisory, compliance, commercial, finance, productivity, and research. One-command install."},"isInternal":false,"tokens":4824,"sizeBytes":18529},{"name":"agent-launcher-orchestrator.md","path":"docs/skills/agent-launcher/agent-launcher-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/agent-launcher/agent-launcher-orchestrator.md","title":"Agent-launcher Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fagent-launcher-orchestrator.md -->","frontmatter":{"title":"agent-launcher — Domain Orchestrator — Agent Skill for Claude Managed Agents","description":"Use when a user wants to build, launch, grade, or schedule a Claude Managed Agent (CMA) in their own Anthropic account — 'build me an agent', 'launch."},"isInternal":false,"tokens":1399,"sizeBytes":5167},{"name":"grade-iterate.md","path":"docs/skills/agent-launcher/grade-iterate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/agent-launcher/grade-iterate.md","title":"Agent-launcher Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fgrade-iterate.md -->","frontmatter":{"title":"Phase 3 — Grade → Iterate (the bounded loop) — Agent Skill for Claude Managed Agents","description":"Phase 3 of building a Claude Managed Agent — the bounded grade→iterate loop. 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Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1195,"sizeBytes":4530},{"name":"run-without-you.md","path":"docs/skills/agent-launcher/run-without-you.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/agent-launcher/run-without-you.md","title":"Agent-launcher Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Frun-without-you.md -->","frontmatter":{"title":"Phase 4 — Run Without You (the recurring loop) — Agent Skill for Claude Managed Agents","description":"Phase 4 of building a Claude Managed Agent — make it run without you. Turn a graded agent into a recurring scheduled deployment (POSIX-cron), an. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1104,"sizeBytes":4212},{"name":"stage-launch.md","path":"docs/skills/agent-launcher/stage-launch.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/agent-launcher/stage-launch.md","title":"Agent-launcher Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fstage-launch.md -->","frontmatter":{"title":"Phase 2 — Stage → Launch — Agent Skill for Claude Managed Agents","description":"Phase 2 of building a Claude Managed Agent — turn a validated build sheet into exact API payloads and a resumable BYOK curl launch script, then. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":969,"sizeBytes":3696},{"name":"wrap-up.md","path":"docs/skills/agent-launcher/wrap-up.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/agent-launcher/wrap-up.md","title":"Agent-launcher Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fagent-launcher%2Fwrap-up.md -->","frontmatter":{"title":"Wrap-up — close it out — Agent Skill for Claude Managed Agents","description":"Close out a launched Claude Managed Agent — recap every primitive the founder now owns, regenerate the single-file overview page, and suggest the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":740,"sizeBytes":2966},{"name":"business-growth-skills.md","path":"docs/skills/business-growth/business-growth-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/business-growth-skills.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Fbusiness-growth-skills.md -->","frontmatter":{"title":"Business & Growth Skills — Router — Agent Skill for Growth","description":"Router/index for the 4 business & growth skills bundled in this plugin: customer-success-manager (health scoring, churn risk, expansion). Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":508,"sizeBytes":2132},{"name":"business-growth.md","path":"docs/skills/business-growth/business-growth.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/business-growth.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Fbusiness-growth.md -->","frontmatter":{"title":"Business & Growth Skills — Agent Skill for Growth","description":"4 business growth agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Customer success (health scoring, churn), sales."},"isInternal":false,"tokens":434,"sizeBytes":1820},{"name":"contract-and-proposal-writer.md","path":"docs/skills/business-growth/contract-and-proposal-writer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/contract-and-proposal-writer.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Fcontract-and-proposal-writer.md -->","frontmatter":{"title":"Contract & Proposal Writer — Agent Skill for Growth","description":"Generate professional, jurisdiction-aware business documents: freelance contracts, project proposals, SOWs, NDAs, and MSAs. Structured Markdown. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3424,"sizeBytes":14037},{"name":"customer-success-manager.md","path":"docs/skills/business-growth/customer-success-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/customer-success-manager.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Fcustomer-success-manager.md -->","frontmatter":{"title":"Customer Success Manager — Agent Skill for Growth","description":"Monitors customer health, predicts churn risk, and identifies expansion opportunities using weighted scoring models for SaaS customer success. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1982,"sizeBytes":9134},{"name":"index.md","path":"docs/skills/business-growth/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/index.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Findex.md -->","frontmatter":{"title":"Business & Growth Skills — Agent Skills & Codex Plugins","description":"5 business & growth skills — business growth agent skill and Claude Code plugin for customer success, sales, and revenue ops. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":330,"sizeBytes":1451},{"name":"revenue-operations.md","path":"docs/skills/business-growth/revenue-operations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/revenue-operations.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Frevenue-operations.md -->","frontmatter":{"title":"Revenue Operations — Agent Skill for Growth","description":"Analyzes sales pipeline health, revenue forecasting accuracy, and go-to-market efficiency metrics for SaaS revenue optimization. Use when analyzing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2554,"sizeBytes":10579},{"name":"sales-engineer.md","path":"docs/skills/business-growth/sales-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-growth/sales-engineer.md","title":"Business-growth Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-growth%2Fsales-engineer.md -->","frontmatter":{"title":"Sales Engineer Skill — Agent Skill for Growth","description":"Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2127,"sizeBytes":9645},{"name":"business-operations-skills.md","path":"docs/skills/business-operations/business-operations-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/business-operations-skills.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Fbusiness-operations-skills.md -->","frontmatter":{"title":"Business Operations — Domain Orchestrator — Claude Code Plugin & Agent Skill","description":"Use when running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2134,"sizeBytes":9015},{"name":"capacity-planner.md","path":"docs/skills/business-operations/capacity-planner.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/capacity-planner.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Fcapacity-planner.md -->","frontmatter":{"title":"capacity-planner — Claude Code Plugin & Agent Skill","description":"Use when an ops leader (Director of CX, Head of Support, VP Ops, Head of BizOps, Head of IT ops, Head of Finance ops) is sizing ops capacity. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3110,"sizeBytes":11945},{"name":"index.md","path":"docs/skills/business-operations/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/index.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Findex.md -->","frontmatter":{"title":"Business Operations Skills — Agent Skills & Codex Plugins","description":"7 business operations skills — business operations agent skill and Claude Code plugin for process mapping, vendor management, capacity planning, and internal comms. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":470,"sizeBytes":2076},{"name":"internal-comms.md","path":"docs/skills/business-operations/internal-comms.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/internal-comms.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Finternal-comms.md -->","frontmatter":{"title":"internal-comms — Tactical Internal Change-Management Authoring — Claude Code Plugin & Agent Skill","description":"Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3106,"sizeBytes":13587},{"name":"knowledge-ops.md","path":"docs/skills/business-operations/knowledge-ops.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/knowledge-ops.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Fknowledge-ops.md -->","frontmatter":{"title":"knowledge-ops — Claude Code Plugin & Agent Skill","description":"Use when a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3839,"sizeBytes":16039},{"name":"process-mapper.md","path":"docs/skills/business-operations/process-mapper.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/process-mapper.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Fprocess-mapper.md -->","frontmatter":{"title":"process-mapper — Claude Code Plugin & Agent Skill","description":"Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2110,"sizeBytes":8724},{"name":"procurement-optimizer.md","path":"docs/skills/business-operations/procurement-optimizer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/procurement-optimizer.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Fprocurement-optimizer.md -->","frontmatter":{"title":"Procurement Optimizer — Spend Categorization + Supplier Rationalization — Claude Code Plugin & Agent Skill","description":"Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs a spend audit. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3216,"sizeBytes":14183},{"name":"vendor-management.md","path":"docs/skills/business-operations/vendor-management.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/business-operations/vendor-management.md","title":"Business-operations Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fbusiness-operations%2Fvendor-management.md -->","frontmatter":{"title":"Vendor Management — Operational Third-Party Performance — Claude Code Plugin & Agent Skill","description":"Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2750,"sizeBytes":11275},{"name":"agent-protocol.md","path":"docs/skills/c-level-advisor/agent-protocol.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/agent-protocol.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fagent-protocol.md -->","frontmatter":{"title":"Inter-Agent Protocol — Agent Skill for Executives","description":"Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4233,"sizeBytes":17127},{"name":"arquiteto-de-empresa.md","path":"docs/skills/c-level-advisor/arquiteto-de-empresa.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/arquiteto-de-empresa.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Farquiteto-de-empresa.md -->","frontmatter":{"title":"Company Architect — Agent Skill for Executives","description":"Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1873,"sizeBytes":7265},{"name":"board-deck-builder.md","path":"docs/skills/c-level-advisor/board-deck-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/board-deck-builder.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fboard-deck-builder.md -->","frontmatter":{"title":"Board Deck Builder — Agent Skill for Executives","description":"Assembles comprehensive board and investor update decks by pulling perspectives from all C-suite roles. Use when preparing board meetings, investor. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1999,"sizeBytes":7821},{"name":"board-meeting.md","path":"docs/skills/c-level-advisor/board-meeting.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/board-meeting.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fboard-meeting.md -->","frontmatter":{"title":"Board Meeting Protocol — Agent Skill for Executives","description":"Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1830,"sizeBytes":6989},{"name":"c-level-advisor.md","path":"docs/skills/c-level-advisor/c-level-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-advisor.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-advisor.md -->","frontmatter":{"title":"C-Level Advisory Ecosystem — Agent Skill for Executives","description":"10 C-level advisory agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO."},"isInternal":false,"tokens":1503,"sizeBytes":6166},{"name":"c-level-agents-boardroom.md","path":"docs/skills/c-level-advisor/c-level-agents-boardroom.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-boardroom.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-boardroom.md -->","frontmatter":{"title":"/c-level-agents:boardroom — Multi-Role Boardroom Deliberation — Agent Skill for Executives","description":"/c-level-agents:boardroom <brief> — 6-phase multi-role deliberation across the C-suite with Phase 2 isolation, critic pre-screen, and synthesis. Outputs a board. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1478,"sizeBytes":5565},{"name":"c-level-agents-brief.md","path":"docs/skills/c-level-advisor/c-level-agents-brief.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-brief.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-brief.md -->","frontmatter":{"title":"/c-level-agents:brief — One-Page Strategy Brief — Agent Skill for Executives","description":"/c-level-agents:brief <topic> — Generate a one-page strategy brief from an office-hours intake. First step in the strategic sprint pipeline. Use when a strategic. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1267,"sizeBytes":4709},{"name":"c-level-agents-caio-review.md","path":"docs/skills/c-level-advisor/c-level-agents-caio-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-caio-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-caio-review.md -->","frontmatter":{"title":"/c-level-agents:caio-review — CAIO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:caio-review <plan> — Eval-demanding Chief AI Officer interrogation of any plan that involves AI: model selection, risk classification, cost. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1707,"sizeBytes":6738},{"name":"c-level-agents-cco-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cco-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cco-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cco-review.md -->","frontmatter":{"title":"/c-level-agents:cco-review — CCO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cco-review <plan> — Retention-obsessed Chief Customer Officer interrogation of any plan that touches customer retention, segmentation, CS team. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1573,"sizeBytes":5947},{"name":"c-level-agents-cdo-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cdo-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cdo-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cdo-review.md -->","frontmatter":{"title":"/c-level-agents:cdo-review — CDO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cdo-review <plan> — Decision-driven Chief Data Officer interrogation of any plan that touches training data, data architecture, data. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1501,"sizeBytes":5912},{"name":"c-level-agents-cfo-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cfo-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cfo-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cfo-review.md -->","frontmatter":{"title":"/c-level-agents:cfo-review — CFO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cfo-review <plan> — Numerate-skeptic interrogation of any plan that touches money. Unit economics, runway, dilution, capital allocation. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1071,"sizeBytes":3984},{"name":"c-level-agents-ciso-review.md","path":"docs/skills/c-level-advisor/c-level-agents-ciso-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-ciso-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-ciso-review.md -->","frontmatter":{"title":"/c-level-agents:ciso-review — CISO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:ciso-review <plan> — Risk-paranoid interrogation of any plan that touches data, compliance, or production access. Use when launching features. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1085,"sizeBytes":4030},{"name":"c-level-agents-cmo-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cmo-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cmo-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cmo-review.md -->","frontmatter":{"title":"/c-level-agents:cmo-review — CMO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cmo-review <plan> — Narrative-first interrogation of positioning, ICP, message house, and channel mix. Use when launching a campaign or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1073,"sizeBytes":4038},{"name":"c-level-agents-cpo-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cpo-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cpo-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cpo-review.md -->","frontmatter":{"title":"/c-level-agents:cpo-review — CPO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cpo-review <plan> — JTBD-driven interrogation of product roadmap, PMF signal, and portfolio focus. Use when committing a quarter's roadmap. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1055,"sizeBytes":3905},{"name":"c-level-agents-cro-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cro-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cro-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cro-review.md -->","frontmatter":{"title":"/c-level-agents:cro-review — CRO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cro-review <plan> — Pipeline-paranoid interrogation of revenue, win rate, NRR, and ramp time. Use when the forecast misses pipeline coverage, win. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1060,"sizeBytes":3937},{"name":"c-level-agents-cross-eval.md","path":"docs/skills/c-level-advisor/c-level-agents-cross-eval.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cross-eval.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cross-eval.md -->","frontmatter":{"title":"/c-level-agents:cross-eval — Multi-Model Consensus — Agent Skill for Executives","description":"/c-level-agents:cross-eval <memo> — Multi-model consensus on a board memo or strategy brief. Claude + Codex + Gemini cross-review with graceful degradation. Use."},"isInternal":false,"tokens":1273,"sizeBytes":4950},{"name":"c-level-agents-cto-review.md","path":"docs/skills/c-level-advisor/c-level-agents-cto-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-cto-review.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-cto-review.md -->","frontmatter":{"title":"/c-level-agents:cto-review — CTO Forcing Questions — Agent Skill for Executives","description":"/c-level-agents:cto-review <plan> — Architecture and scaling interrogation. Tech debt, scaling cliffs, team scaling, build-vs-buy. Use when committing to an. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1137,"sizeBytes":4196},{"name":"c-level-agents-decide.md","path":"docs/skills/c-level-advisor/c-level-agents-decide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-decide.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-decide.md -->","frontmatter":{"title":"/c-level-agents:decide — Log the Decision — Agent Skill for Executives","description":"/c-level-agents:decide <memo> — Log a decision to two-layer memory via decision-logger. Approved memo becomes durable; raw transcripts kept for reference. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1173,"sizeBytes":4481},{"name":"c-level-agents-execute.md","path":"docs/skills/c-level-advisor/c-level-agents-execute.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-execute.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-execute.md -->","frontmatter":{"title":"/c-level-agents:execute — 90-Day Execution Plan — Agent Skill for Executives","description":"/c-level-agents:execute <decision> — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision. Use when a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1170,"sizeBytes":4207},{"name":"c-level-agents-founder-mode.md","path":"docs/skills/c-level-advisor/c-level-agents-founder-mode.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/c-level-agents-founder-mode.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fc-level-agents-founder-mode.md -->","frontmatter":{"title":"/c-level-agents:founder-mode — The Auto-Router — Agent Skill for Executives","description":"/c-level-agents:founder-mode <question> — Auto-routes any founder question to the right C-role advisor or to /c-level-agents:boardroom for multi-role topics. The. 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Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1976,"sizeBytes":8712},{"name":"decision-logger.md","path":"docs/skills/c-level-advisor/decision-logger.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/decision-logger.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fdecision-logger.md -->","frontmatter":{"title":"Decision Logger — Agent Skill for Executives","description":"Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1506,"sizeBytes":6085},{"name":"executive-mentor-board-prep.md","path":"docs/skills/c-level-advisor/executive-mentor-board-prep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/executive-mentor-board-prep.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fexecutive-mentor-board-prep.md -->","frontmatter":{"title":"/em:board-prep — Board Meeting Preparation — Agent Skill for Executives","description":"Board meeting preparation for the adversarial scenario, not the friendly one. Forces numbers-cold mastery, anticipates hard questions, builds a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1647,"sizeBytes":7051},{"name":"executive-mentor-challenge.md","path":"docs/skills/c-level-advisor/executive-mentor-challenge.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/executive-mentor-challenge.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fexecutive-mentor-challenge.md -->","frontmatter":{"title":"/em:challenge — Pre-Mortem Plan Analysis — Agent Skill for Executives","description":"Pre-mortem plan analysis. Imagine the plan failed 12 months from now and work backwards to find the weaknesses. Surfaces assumptions, dependencies. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1679,"sizeBytes":7239},{"name":"executive-mentor-hard-call.md","path":"docs/skills/c-level-advisor/executive-mentor-hard-call.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/executive-mentor-hard-call.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fexecutive-mentor-hard-call.md -->","frontmatter":{"title":"/em:hard-call — Framework for Decisions With No Good Options — Agent Skill for Executives","description":"/em:hard-call — Framework for decisions with no good options. Use when every option is painful and a structured 10/10/10 + regret-minimization pass. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1897,"sizeBytes":8189},{"name":"executive-mentor-postmortem.md","path":"docs/skills/c-level-advisor/executive-mentor-postmortem.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/executive-mentor-postmortem.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fexecutive-mentor-postmortem.md -->","frontmatter":{"title":"/em:postmortem — Honest Analysis of What Went Wrong — Agent Skill for Executives","description":"/em:postmortem — Honest analysis of what went wrong. Use after a failed launch, missed quarter, or bad hire to run a blameless 5-Whys retrospective. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1932,"sizeBytes":8573},{"name":"executive-mentor-stress-test.md","path":"docs/skills/c-level-advisor/executive-mentor-stress-test.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/executive-mentor-stress-test.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fexecutive-mentor-stress-test.md -->","frontmatter":{"title":"/em:stress-test — Business Assumption Stress Testing — Agent Skill for Executives","description":"/em:stress-test — Business assumption stress testing. Use before betting on a plan whose core assumptions are unvalidated — e.g. stress-testing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1939,"sizeBytes":8459},{"name":"executive-mentor.md","path":"docs/skills/c-level-advisor/executive-mentor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/executive-mentor.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fexecutive-mentor.md -->","frontmatter":{"title":"Executive Mentor — Agent Skill for Executives","description":"Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for brutal board meetings, dissects decisions with no good. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1886,"sizeBytes":7946},{"name":"founder-coach.md","path":"docs/skills/c-level-advisor/founder-coach.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/founder-coach.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Ffounder-coach.md -->","frontmatter":{"title":"Founder Development Coach — Agent Skill for Executives","description":"Personal leadership development for founders and first-time CEOs. Covers founder archetype identification, delegation frameworks, energy management. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3207,"sizeBytes":14214},{"name":"general-counsel-advisor.md","path":"docs/skills/c-level-advisor/general-counsel-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/general-counsel-advisor.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fgeneral-counsel-advisor.md -->","frontmatter":{"title":"General Counsel Advisor — Agent Skill for Executives","description":"General Counsel advisory for startups: contract review (MSA, SaaS, NDA, DPA, employment), IP strategy, term sheet decoding, and regulatory landscape. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2272,"sizeBytes":9360},{"name":"index.md","path":"docs/skills/c-level-advisor/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/index.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Findex.md -->","frontmatter":{"title":"C-Level Advisory Skills — Agent Skills & Codex Plugins","description":"40 c-level advisory skills — executive advisory agent skill and Claude Code plugin for strategic decisions and board meetings. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":1518,"sizeBytes":6677},{"name":"internal-narrative.md","path":"docs/skills/c-level-advisor/internal-narrative.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/internal-narrative.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Finternal-narrative.md -->","frontmatter":{"title":"Internal Narrative Builder — Agent Skill for Executives","description":"Build and maintain one coherent company story across all audiences — employees, investors, customers, candidates, and partners. Detects narrative. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2306,"sizeBytes":10710},{"name":"intl-expansion.md","path":"docs/skills/c-level-advisor/intl-expansion.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/intl-expansion.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fintl-expansion.md -->","frontmatter":{"title":"International Expansion — Agent Skill for Executives","description":"International market expansion strategy. Market selection, entry modes, localization, regulatory compliance, and go-to-market by region. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1108,"sizeBytes":4900},{"name":"ma-playbook.md","path":"docs/skills/c-level-advisor/ma-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/ma-playbook.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fma-playbook.md -->","frontmatter":{"title":"M&A Playbook — Agent Skill for Executives","description":"M&A strategy for acquiring companies or being acquired. Due diligence, valuation, integration, and deal structure. Use when evaluating acquisitions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1652,"sizeBytes":7177},{"name":"org-health-diagnostic.md","path":"docs/skills/c-level-advisor/org-health-diagnostic.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/org-health-diagnostic.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Forg-health-diagnostic.md -->","frontmatter":{"title":"Org Health Diagnostic — Agent Skill for Executives","description":"Cross-functional organizational health check combining signals from all C-suite roles. Scores 8 dimensions on a traffic-light scale with drill-down. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2441,"sizeBytes":8818},{"name":"scenario-war-room.md","path":"docs/skills/c-level-advisor/scenario-war-room.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/scenario-war-room.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fscenario-war-room.md -->","frontmatter":{"title":"Scenario War Room — Agent Skill for Executives","description":"Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2048,"sizeBytes":8245},{"name":"strategic-alignment.md","path":"docs/skills/c-level-advisor/strategic-alignment.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/strategic-alignment.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fstrategic-alignment.md -->","frontmatter":{"title":"Strategic Alignment Engine — Agent Skill for Executives","description":"Cascades strategy from boardroom to individual contributor. Detects and fixes misalignment between company goals and team execution. Covers strategy. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2116,"sizeBytes":9515},{"name":"vpe-advisor.md","path":"docs/skills/c-level-advisor/vpe-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/c-level-advisor/vpe-advisor.md","title":"C-level-advisor Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fc-level-advisor%2Fvpe-advisor.md -->","frontmatter":{"title":"VP of Engineering Advisor — Agent Skill for Executives","description":"VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing →. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3318,"sizeBytes":13568},{"name":"channel-economics.md","path":"docs/skills/commercial/channel-economics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/channel-economics.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fchannel-economics.md -->","frontmatter":{"title":"channel-economics — Claude Code Plugin & Agent Skill","description":"Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2977,"sizeBytes":13120},{"name":"commercial-forecaster.md","path":"docs/skills/commercial/commercial-forecaster.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/commercial-forecaster.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fcommercial-forecaster.md -->","frontmatter":{"title":"commercial-forecaster — Claude Code Plugin & Agent Skill","description":"Use when building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board number . Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2814,"sizeBytes":11803},{"name":"commercial-policy.md","path":"docs/skills/commercial/commercial-policy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/commercial-policy.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fcommercial-policy.md -->","frontmatter":{"title":"commercial-policy — Claude Code Plugin & Agent Skill","description":"Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3320,"sizeBytes":14116},{"name":"commercial-skills.md","path":"docs/skills/commercial/commercial-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/commercial-skills.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fcommercial-skills.md -->","frontmatter":{"title":"Commercial — Domain Orchestrator — Claude Code Plugin & Agent Skill","description":"Use when reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2214,"sizeBytes":9098},{"name":"deal-desk.md","path":"docs/skills/commercial/deal-desk.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/deal-desk.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fdeal-desk.md -->","frontmatter":{"title":"deal-desk — Claude Code Plugin & Agent Skill","description":"Use when reviewing a specific inbound deal before close — when sales has asked for a discount that exceeds AE authority, when the customer has. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2677,"sizeBytes":11087},{"name":"index.md","path":"docs/skills/commercial/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/index.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Findex.md -->","frontmatter":{"title":"Commercial Skills — Agent Skills & Codex Plugins","description":"8 commercial skills — commercial agent skill and Claude Code plugin for pricing strategy, deal desk, partnerships, and RFP response. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":458,"sizeBytes":1986},{"name":"partnerships-architect.md","path":"docs/skills/commercial/partnerships-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/partnerships-architect.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fpartnerships-architect.md -->","frontmatter":{"title":"partnerships-architect — Claude Code Plugin & Agent Skill","description":"Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral /. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2892,"sizeBytes":12777},{"name":"pricing-strategist.md","path":"docs/skills/commercial/pricing-strategist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/pricing-strategist.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Fpricing-strategist.md -->","frontmatter":{"title":"pricing-strategist — Claude Code Plugin & Agent Skill","description":"Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2259,"sizeBytes":9373},{"name":"rfp-responder.md","path":"docs/skills/commercial/rfp-responder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/commercial/rfp-responder.md","title":"Commercial Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcommercial%2Frfp-responder.md -->","frontmatter":{"title":"rfp-responder — Claude Code Plugin & Agent Skill","description":"Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response . Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2972,"sizeBytes":12665},{"name":"ai-act-readiness.md","path":"docs/skills/compliance-os/ai-act-readiness.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/ai-act-readiness.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fai-act-readiness.md -->","frontmatter":{"title":"/compliance-os:ai-act-readiness — EU AI Act Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:ai-act-readiness [system] — EU AI Act 6-question forcing interrogation. Use during AI-system intake, before EU deployment, or during. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2162,"sizeBytes":8325},{"name":"aims-audit.md","path":"docs/skills/compliance-os/aims-audit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/aims-audit.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Faims-audit.md -->","frontmatter":{"title":"/compliance-os:aims-audit — AIMS ISO 42001 Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:aims-audit [scope] — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. Use before certification stage 1, before. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1681,"sizeBytes":6364},{"name":"compliance-os.md","path":"docs/skills/compliance-os/compliance-os.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/compliance-os.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fcompliance-os.md -->","frontmatter":{"title":"Compliance OS — Meta-Orchestrator — Claude Code Plugin & Agent Skill","description":"Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3116,"sizeBytes":13462},{"name":"compliance-readiness.md","path":"docs/skills/compliance-os/compliance-readiness.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/compliance-readiness.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fcompliance-readiness.md -->","frontmatter":{"title":"/compliance-os:compliance-readiness — Compliance Officer Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:compliance-readiness [program] — Multi-framework compliance officer 6-question forcing interrogation of any compliance program. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1556,"sizeBytes":6475},{"name":"fda-qsr-audit-prep.md","path":"docs/skills/compliance-os/fda-qsr-audit-prep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/fda-qsr-audit-prep.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Ffda-qsr-audit-prep.md -->","frontmatter":{"title":"/compliance-os:fda-qsr-audit-prep — FDA QSR Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:fda-qsr-audit-prep [scope] — FDA 21 CFR 820 (QSR / QMSR) audit 6-question forcing interrogation. Post-Feb 2026 substantially. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1910,"sizeBytes":7394},{"name":"gdpr-audit-prep.md","path":"docs/skills/compliance-os/gdpr-audit-prep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/gdpr-audit-prep.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fgdpr-audit-prep.md -->","frontmatter":{"title":"/compliance-os:gdpr-audit-prep — GDPR DPO Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:gdpr-audit-prep [scope] — GDPR audit 6-question Article-cited forcing interrogation. Use before annual internal GDPR review. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2085,"sizeBytes":8029},{"name":"index.md","path":"docs/skills/compliance-os/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/index.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Findex.md -->","frontmatter":{"title":"Compliance OS Skills — Agent Skills & Codex Plugins","description":"9 compliance os skills — compliance readiness agent skill and Claude Code plugin for ISO 13485, ISO 27001, SOC 2, GDPR, FDA QSR, and EU AI Act audit prep. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":613,"sizeBytes":2128},{"name":"iso13485-audit-prep.md","path":"docs/skills/compliance-os/iso13485-audit-prep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/iso13485-audit-prep.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fiso13485-audit-prep.md -->","frontmatter":{"title":"/compliance-os:iso13485-audit-prep — ISO 13485 QMS Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:iso13485-audit-prep [scope] — ISO 13485 QMS audit 6-question forcing interrogation. Design controls + CAPA + post-market focused. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1992,"sizeBytes":7811},{"name":"iso27001-audit-prep.md","path":"docs/skills/compliance-os/iso27001-audit-prep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/iso27001-audit-prep.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fiso27001-audit-prep.md -->","frontmatter":{"title":"/compliance-os:iso27001-audit-prep — ISO 27001 ISMS Audit Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:iso27001-audit-prep [scope] — ISO 27001 ISMS audit readiness 6-question forcing interrogation. Use before annual Clause 9.2 internal. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1854,"sizeBytes":6923},{"name":"soc2-audit-prep.md","path":"docs/skills/compliance-os/soc2-audit-prep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/compliance-os/soc2-audit-prep.md","title":"Compliance-os Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fcompliance-os%2Fsoc2-audit-prep.md -->","frontmatter":{"title":"/compliance-os:soc2-audit-prep — SOC 2 Type II Forcing Questions — Claude Code Plugin & Agent Skill","description":"/compliance-os:soc2-audit-prep [scope] — SOC 2 Type II readiness 6-question forcing interrogation. Observation-period focused. Use before Type II. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1802,"sizeBytes":7199},{"name":"a11y-audit.md","path":"docs/skills/engineering-team/a11y-audit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/a11y-audit.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fa11y-audit.md -->","frontmatter":{"title":"Accessibility Audit — Agent Skill & Codex Plugin","description":"Accessibility audit skill for scanning, fixing, and verifying WCAG 2.2 Level A and AA compliance across React, Next.js, Vue, Angular, Svelte, and. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2843,"sizeBytes":11347},{"name":"adversarial-reviewer.md","path":"docs/skills/engineering-team/adversarial-reviewer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/adversarial-reviewer.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fadversarial-reviewer.md -->","frontmatter":{"title":"Adversarial Code Reviewer — Agent Skill & Codex Plugin","description":"Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2776,"sizeBytes":12142},{"name":"ai-security.md","path":"docs/skills/engineering-team/ai-security.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/ai-security.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fai-security.md -->","frontmatter":{"title":"AI Security — Agent Skill & Codex Plugin","description":"Use when assessing AI/ML systems for prompt injection, jailbreak vulnerabilities, model inversion risk, data poisoning exposure, or agent tool abuse. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4018,"sizeBytes":18763},{"name":"aws-solution-architect.md","path":"docs/skills/engineering-team/aws-solution-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/aws-solution-architect.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Faws-solution-architect.md -->","frontmatter":{"title":"AWS Solution Architect — Agent Skill & Codex Plugin","description":"Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2545,"sizeBytes":10538},{"name":"azure-cloud-architect.md","path":"docs/skills/engineering-team/azure-cloud-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/azure-cloud-architect.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fazure-cloud-architect.md -->","frontmatter":{"title":"Azure Cloud Architect — Agent Skill & Codex Plugin","description":"Design Azure architectures for startups and enterprises. Use when asked to design Azure infrastructure, create Bicep/ARM templates, optimize Azure. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3410,"sizeBytes":14185},{"name":"cloud-security.md","path":"docs/skills/engineering-team/cloud-security.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/cloud-security.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fcloud-security.md -->","frontmatter":{"title":"Cloud Security — Agent Skill & Codex Plugin","description":"Use when assessing cloud infrastructure for security misconfigurations, IAM privilege escalation paths, S3 public exposure, open security group. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3893,"sizeBytes":17444},{"name":"code-reviewer.md","path":"docs/skills/engineering-team/code-reviewer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/code-reviewer.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fcode-reviewer.md -->","frontmatter":{"title":"Code Reviewer — Agent Skill & Codex Plugin","description":"Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. Analyzes PRs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1651,"sizeBytes":6908},{"name":"email-template-builder.md","path":"docs/skills/engineering-team/email-template-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/email-template-builder.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Femail-template-builder.md -->","frontmatter":{"title":"Email Template Builder — Agent Skill & Codex Plugin","description":"Build complete transactional email systems: React Email templates, provider integration (Resend, Postmark, SendGrid, AWS SES), preview server, i18n. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4150,"sizeBytes":15956},{"name":"embedded-iot-mentor.md","path":"docs/skills/engineering-team/embedded-iot-mentor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/embedded-iot-mentor.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fembedded-iot-mentor.md -->","frontmatter":{"title":"Embedded / IoT Mentor — Agent Skill & Codex Plugin","description":"Mentor for embedded and IoT hardware projects. Helps select MCUs, dev boards, and toolchains, decides where sensor readings end up (phone, PC. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2487,"sizeBytes":10604},{"name":"engineering-skills.md","path":"docs/skills/engineering-team/engineering-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/engineering-skills.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fengineering-skills.md -->","frontmatter":{"title":"Engineering Team Skills — Agent Skill & Codex Plugin","description":"Index of the engineering-team skills bundle for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. Architecture, frontend, backend."},"isInternal":false,"tokens":909,"sizeBytes":3649},{"name":"engineering-team.md","path":"docs/skills/engineering-team/engineering-team.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/engineering-team.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fengineering-team.md -->","frontmatter":{"title":"Engineering Team Skills — Agent Skill & Codex Plugin","description":"23 engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. Architecture, frontend, backend, QA."},"isInternal":false,"tokens":899,"sizeBytes":3604},{"name":"epic-design.md","path":"docs/skills/engineering-team/epic-design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/epic-design.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fepic-design.md -->","frontmatter":{"title":"Epic Design Skill — Agent Skill & Codex Plugin","description":"Build immersive, cinematic 2.5D interactive websites using scroll storytelling, parallax depth, text animations, and premium scroll effects — no. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3880,"sizeBytes":16128},{"name":"gcp-cloud-architect.md","path":"docs/skills/engineering-team/gcp-cloud-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/gcp-cloud-architect.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fgcp-cloud-architect.md -->","frontmatter":{"title":"GCP Cloud Architect — Agent Skill & Codex Plugin","description":"Design GCP architectures for startups and enterprises. Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3185,"sizeBytes":13376},{"name":"google-workspace-cli.md","path":"docs/skills/engineering-team/google-workspace-cli.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/google-workspace-cli.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fgoogle-workspace-cli.md -->","frontmatter":{"title":"Google Workspace CLI — Agent Skill & Codex Plugin","description":"Google Workspace administration via the gws CLI (github.com/googleworkspace/cli). Install, authenticate, and automate Gmail, Drive, Sheets, Calendar. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3037,"sizeBytes":12480},{"name":"incident-commander.md","path":"docs/skills/engineering-team/incident-commander.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/incident-commander.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fincident-commander.md -->","frontmatter":{"title":"Incident Commander Skill — Agent Skill & Codex Plugin","description":"Comprehensive incident response framework from detection through resolution and post-incident review. Battle-tested SRE/DevOps practices: severity. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3359,"sizeBytes":15660},{"name":"incident-response.md","path":"docs/skills/engineering-team/incident-response.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/incident-response.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fincident-response.md -->","frontmatter":{"title":"Incident Response — Agent Skill & Codex Plugin","description":"Use when a security incident has been detected or declared and needs classification, triage, escalation path determination, and forensic evidence. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3704,"sizeBytes":16196},{"name":"index.md","path":"docs/skills/engineering-team/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/index.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Findex.md -->","frontmatter":{"title":"Engineering - Core Skills — Agent Skills & Codex Plugins","description":"54 engineering - core skills — engineering agent skill and Claude Code plugin for code generation, DevOps, architecture, and testing. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":1456,"sizeBytes":6677},{"name":"ms365-tenant-manager.md","path":"docs/skills/engineering-team/ms365-tenant-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/ms365-tenant-manager.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fms365-tenant-manager.md -->","frontmatter":{"title":"Microsoft 365 Tenant Manager — Agent Skill & Codex Plugin","description":"Microsoft 365 tenant administration for Global Administrators. Automate M365 tenant setup, Office 365 admin tasks, Azure AD user management, Exchange. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2689,"sizeBytes":11389},{"name":"named-persona-adversarial-review.md","path":"docs/skills/engineering-team/named-persona-adversarial-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/named-persona-adversarial-review.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fnamed-persona-adversarial-review.md -->","frontmatter":{"title":"Named-Persona Adversarial Review — Agent Skill & Codex Plugin","description":"Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Complements. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2850,"sizeBytes":11992},{"name":"playwright-pro-browserstack.md","path":"docs/skills/engineering-team/playwright-pro-browserstack.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-browserstack.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-browserstack.md -->","frontmatter":{"title":"BrowserStack Integration — Agent Skill & Codex Plugin","description":"Run tests on BrowserStack. Use when user mentions 'browserstack', 'cross-browser', 'cloud testing', 'browser matrix', 'test on safari', 'test on. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1372,"sizeBytes":5692},{"name":"playwright-pro-coverage.md","path":"docs/skills/engineering-team/playwright-pro-coverage.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-coverage.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-coverage.md -->","frontmatter":{"title":"Analyze Test Coverage Gaps — Agent Skill & Codex Plugin","description":"Analyze test coverage gaps. Use when user says 'test coverage', 'what's not tested', 'coverage gaps', 'missing tests', 'coverage report', or 'what. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":841,"sizeBytes":3317},{"name":"playwright-pro-fix.md","path":"docs/skills/engineering-team/playwright-pro-fix.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-fix.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-fix.md -->","frontmatter":{"title":"Fix Failing or Flaky Tests — Agent Skill & Codex Plugin","description":"Fix failing or flaky Playwright tests. Use when user says 'fix test', 'flaky test', 'test failing', 'debug test', 'test broken', 'test passes. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":917,"sizeBytes":3631},{"name":"playwright-pro-generate.md","path":"docs/skills/engineering-team/playwright-pro-generate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-generate.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-generate.md -->","frontmatter":{"title":"Generate Playwright Tests — Agent Skill & Codex Plugin","description":"Generate Playwright tests. Use when user says 'write tests', 'generate tests', 'add tests for', 'test this component', 'e2e test', 'create test for'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1280,"sizeBytes":5234},{"name":"playwright-pro-init.md","path":"docs/skills/engineering-team/playwright-pro-init.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-init.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-init.md -->","frontmatter":{"title":"Initialize Playwright Project — Agent Skill & Codex Plugin","description":"Set up Playwright in a project. Use when user says 'set up playwright', 'add e2e tests', 'configure playwright', 'testing setup', 'init playwright'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1408,"sizeBytes":5283},{"name":"playwright-pro-migrate.md","path":"docs/skills/engineering-team/playwright-pro-migrate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-migrate.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-migrate.md -->","frontmatter":{"title":"Migrate to Playwright — Agent Skill & Codex Plugin","description":"Migrate from Cypress or Selenium to Playwright. Use when user mentions 'cypress', 'selenium', 'migrate tests', 'convert tests', 'switch to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1130,"sizeBytes":4780},{"name":"playwright-pro-pw-init.md","path":"docs/skills/engineering-team/playwright-pro-pw-init.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-pw-init.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-pw-init.md -->","frontmatter":{"title":"Initialize Playwright Project — Agent Skill & Codex Plugin","description":"Set up Playwright in a project. Use when user says 'set up playwright', 'add e2e tests', 'configure playwright', 'testing setup', 'init playwright'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1409,"sizeBytes":5286},{"name":"playwright-pro-pw-review.md","path":"docs/skills/engineering-team/playwright-pro-pw-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-pw-review.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-pw-review.md -->","frontmatter":{"title":"Review Playwright Tests — Agent Skill & Codex Plugin","description":"Review Playwright tests for quality. Use when user says 'review tests', 'check test quality', 'audit tests', 'improve tests', 'test code review', or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":930,"sizeBytes":3675},{"name":"playwright-pro-pw.md","path":"docs/skills/engineering-team/playwright-pro-pw.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-pw.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-pw.md -->","frontmatter":{"title":"Playwright Pro — Agent Skill & Codex Plugin","description":"Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1507,"sizeBytes":6134},{"name":"playwright-pro-report.md","path":"docs/skills/engineering-team/playwright-pro-report.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-report.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-report.md -->","frontmatter":{"title":"Smart Test Reporting — Agent Skill & Codex Plugin","description":"Generate test report. Use when user says 'test report', 'results summary', 'test status', 'show results', 'test dashboard', or 'how did tests go'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":942,"sizeBytes":3542},{"name":"playwright-pro-review.md","path":"docs/skills/engineering-team/playwright-pro-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-review.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-review.md -->","frontmatter":{"title":"Review Playwright Tests — Agent Skill & Codex Plugin","description":"Review Playwright tests for quality. Use when user says 'review tests', 'check test quality', 'audit tests', 'improve tests', 'test code review', or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":929,"sizeBytes":3672},{"name":"playwright-pro-testrail.md","path":"docs/skills/engineering-team/playwright-pro-testrail.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro-testrail.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro-testrail.md -->","frontmatter":{"title":"TestRail Integration — Agent Skill & Codex Plugin","description":"Sync tests with TestRail. Use when user mentions 'testrail', 'test management', 'test cases', 'test run', 'sync test cases', 'push results to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1160,"sizeBytes":4454},{"name":"playwright-pro.md","path":"docs/skills/engineering-team/playwright-pro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/playwright-pro.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fplaywright-pro.md -->","frontmatter":{"title":"Playwright Pro — Agent Skill & Codex Plugin","description":"Production-grade Playwright testing toolkit. Use when the user mentions Playwright tests, end-to-end testing, browser automation, fixing flaky tests. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1365,"sizeBytes":5582},{"name":"red-green-proof.md","path":"docs/skills/engineering-team/red-green-proof.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/red-green-proof.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fred-green-proof.md -->","frontmatter":{"title":"Red-Green-Proof — Agent Skill & Codex Plugin","description":"Turns a suspected bug into a proven one. Verify the cause against reality before claiming it, write a test that FAILS on the current code, apply the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2209,"sizeBytes":9696},{"name":"red-team.md","path":"docs/skills/engineering-team/red-team.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/red-team.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fred-team.md -->","frontmatter":{"title":"Red Team — Agent Skill & Codex Plugin","description":"Use when planning or executing authorized red team engagements, attack path analysis, or offensive security simulations. Covers MITRE ATT&CK. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3820,"sizeBytes":16669},{"name":"security-pen-testing.md","path":"docs/skills/engineering-team/security-pen-testing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/security-pen-testing.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsecurity-pen-testing.md -->","frontmatter":{"title":"Security Penetration Testing — Agent Skill & Codex Plugin","description":"Use when the user asks to perform security audits, penetration testing, vulnerability scanning, OWASP Top 10 checks, or offensive security. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3552,"sizeBytes":15291},{"name":"self-improving-agent-extract.md","path":"docs/skills/engineering-team/self-improving-agent-extract.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-extract.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-extract.md -->","frontmatter":{"title":"/si:extract — Create Skills from Patterns — Agent Skill & Codex Plugin","description":"Turn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples. Use when the user runs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1575,"sizeBytes":6282},{"name":"self-improving-agent-memory-review.md","path":"docs/skills/engineering-team/self-improving-agent-memory-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-memory-review.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-memory-review.md -->","frontmatter":{"title":"/si:memory-review — Analyze Auto-Memory — Agent Skill & Codex Plugin","description":"Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1220,"sizeBytes":4829},{"name":"self-improving-agent-memory-status.md","path":"docs/skills/engineering-team/self-improving-agent-memory-status.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-memory-status.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-memory-status.md -->","frontmatter":{"title":"/si:memory-status — Memory Health Dashboard — Agent Skill & Codex Plugin","description":"Memory health dashboard showing line counts, topic files, capacity, stale entries, and recommendations. Use when the user runs /si:memory-status or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1007,"sizeBytes":3504},{"name":"self-improving-agent-promote.md","path":"docs/skills/engineering-team/self-improving-agent-promote.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-promote.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-promote.md -->","frontmatter":{"title":"/si:promote — Graduate Learnings to Rules — Agent Skill & Codex Plugin","description":"Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1309,"sizeBytes":5192},{"name":"self-improving-agent-remember.md","path":"docs/skills/engineering-team/self-improving-agent-remember.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-remember.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-remember.md -->","frontmatter":{"title":"/si:remember — Save Knowledge Explicitly — Agent Skill & Codex Plugin","description":"Explicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":976,"sizeBytes":3800},{"name":"self-improving-agent-review.md","path":"docs/skills/engineering-team/self-improving-agent-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-review.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-review.md -->","frontmatter":{"title":"/si:review — Analyze Auto-Memory — Agent Skill & Codex Plugin","description":"Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:review or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1216,"sizeBytes":4773},{"name":"self-improving-agent-status.md","path":"docs/skills/engineering-team/self-improving-agent-status.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent-status.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent-status.md -->","frontmatter":{"title":"/si:status — Memory Health Dashboard — Agent Skill & Codex Plugin","description":"Memory health dashboard showing line counts, topic files, capacity, stale entries, and recommendations. Use when the user runs /si:status or asks how. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":997,"sizeBytes":3429},{"name":"self-improving-agent.md","path":"docs/skills/engineering-team/self-improving-agent.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/self-improving-agent.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fself-improving-agent.md -->","frontmatter":{"title":"Self-Improving Agent — Agent Skill & Codex Plugin","description":"Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and."},"isInternal":false,"tokens":1675,"sizeBytes":7416},{"name":"senior-architect.md","path":"docs/skills/engineering-team/senior-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-architect.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-architect.md -->","frontmatter":{"title":"Senior Architect — Agent Skill & Codex Plugin","description":"This skill should be used when the user asks to 'design system architecture', 'evaluate microservices vs monolith', 'create architecture diagrams'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2481,"sizeBytes":11268},{"name":"senior-backend.md","path":"docs/skills/engineering-team/senior-backend.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-backend.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-backend.md -->","frontmatter":{"title":"Senior Backend Engineer — Agent Skill & Codex Plugin","description":"Designs and implements backend systems including REST APIs, microservices, database architectures, authentication flows, and security hardening. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3694,"sizeBytes":15395},{"name":"senior-computer-vision.md","path":"docs/skills/engineering-team/senior-computer-vision.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-computer-vision.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-computer-vision.md -->","frontmatter":{"title":"Senior Computer Vision Engineer — Agent Skill & Codex Plugin","description":"Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3703,"sizeBytes":13229},{"name":"senior-data-engineer.md","path":"docs/skills/engineering-team/senior-data-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-data-engineer.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-data-engineer.md -->","frontmatter":{"title":"Senior Data Engineer — Agent Skill & Codex Plugin","description":"Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1464,"sizeBytes":6161},{"name":"senior-data-scientist.md","path":"docs/skills/engineering-team/senior-data-scientist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-data-scientist.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-data-scientist.md -->","frontmatter":{"title":"Senior Data Scientist — Agent Skill & Codex Plugin","description":"World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2394,"sizeBytes":9423},{"name":"senior-devops.md","path":"docs/skills/engineering-team/senior-devops.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-devops.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-devops.md -->","frontmatter":{"title":"Senior Devops — Agent Skill & Codex Plugin","description":"Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2710,"sizeBytes":11200},{"name":"senior-frontend.md","path":"docs/skills/engineering-team/senior-frontend.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-frontend.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-frontend.md -->","frontmatter":{"title":"Senior Frontend — Agent Skill & Codex Plugin","description":"Frontend development skill for React, Next.js, TypeScript, and Tailwind CSS applications. Use when building React components, optimizing Next.js. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4001,"sizeBytes":16176},{"name":"senior-fullstack.md","path":"docs/skills/engineering-team/senior-fullstack.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-fullstack.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-fullstack.md -->","frontmatter":{"title":"Senior Fullstack — Agent Skill & Codex Plugin","description":"Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3506,"sizeBytes":14921},{"name":"senior-ml-engineer.md","path":"docs/skills/engineering-team/senior-ml-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-ml-engineer.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-ml-engineer.md -->","frontmatter":{"title":"Senior ML Engineer — Agent Skill & Codex Plugin","description":"ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2297,"sizeBytes":9770},{"name":"senior-prompt-engineer.md","path":"docs/skills/engineering-team/senior-prompt-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-prompt-engineer.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-prompt-engineer.md -->","frontmatter":{"title":"Senior Prompt Engineer — Agent Skill & Codex Plugin","description":"Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2343,"sizeBytes":10295},{"name":"senior-qa.md","path":"docs/skills/engineering-team/senior-qa.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-qa.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-qa.md -->","frontmatter":{"title":"Senior QA Engineer — Agent Skill & Codex Plugin","description":"Generates unit tests, integration tests, and E2E tests for React/Next.js applications. Scans components to create Jest + React Testing Library test. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2087,"sizeBytes":8791},{"name":"senior-secops.md","path":"docs/skills/engineering-team/senior-secops.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-secops.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-secops.md -->","frontmatter":{"title":"Senior SecOps Engineer — Agent Skill & Codex Plugin","description":"Senior SecOps engineer skill for application security, vulnerability management, compliance verification, and secure development practices. Runs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3975,"sizeBytes":16177},{"name":"senior-security.md","path":"docs/skills/engineering-team/senior-security.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/senior-security.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsenior-security.md -->","frontmatter":{"title":"Senior Security Engineer — Threat Modeling + Security Router — Agent Skill & Codex Plugin","description":"Use when the user asks for STRIDE threat modeling, DREAD risk scoring, data-flow-diagram threat analysis, or a quick secret scan — or when a security. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1695,"sizeBytes":6947},{"name":"snowflake-development.md","path":"docs/skills/engineering-team/snowflake-development.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/snowflake-development.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fsnowflake-development.md -->","frontmatter":{"title":"Snowflake Development — Agent Skill & Codex Plugin","description":"Use when writing Snowflake SQL, building data pipelines with Dynamic Tables or Streams/Tasks, using Cortex AI functions, creating Cortex Agents. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3152,"sizeBytes":13341},{"name":"stripe-integration-expert.md","path":"docs/skills/engineering-team/stripe-integration-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/stripe-integration-expert.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fstripe-integration-expert.md -->","frontmatter":{"title":"Stripe Integration Expert — Agent Skill & Codex Plugin","description":"Production-grade Stripe integrations: subscriptions with trials and proration, one-time payments, usage-based billing, checkout sessions, idempotent. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3417,"sizeBytes":15280},{"name":"tdd-guide.md","path":"docs/skills/engineering-team/tdd-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/tdd-guide.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Ftdd-guide.md -->","frontmatter":{"title":"TDD Guide — Agent Skill & Codex Plugin","description":"Test-driven development skill for writing unit tests, generating test fixtures and mocks, analyzing coverage gaps, and guiding red-green-refactor. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3387,"sizeBytes":14083},{"name":"tech-stack-evaluator.md","path":"docs/skills/engineering-team/tech-stack-evaluator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/tech-stack-evaluator.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Ftech-stack-evaluator.md -->","frontmatter":{"title":"Technology Stack Evaluator — Agent Skill & Codex Plugin","description":"Technology stack evaluation and comparison with TCO analysis, security assessment, and ecosystem health scoring. Use when comparing frameworks. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1091,"sizeBytes":4843},{"name":"threat-detection.md","path":"docs/skills/engineering-team/threat-detection.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering-team/threat-detection.md","title":"Engineering-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering-team%2Fthreat-detection.md -->","frontmatter":{"title":"Threat Detection — Agent Skill & Codex Plugin","description":"Use when hunting for threats in an environment, analyzing IOCs, or detecting behavioral anomalies in telemetry. Covers hypothesis-driven threat. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3562,"sizeBytes":14982},{"name":"agent-designer.md","path":"docs/skills/engineering/agent-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agent-designer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagent-designer.md -->","frontmatter":{"title":"Agent Designer — Multi-Agent System Architecture — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents."},"isInternal":false,"tokens":1009,"sizeBytes":4460},{"name":"agent-harness.md","path":"docs/skills/engineering/agent-harness.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agent-harness.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagent-harness.md -->","frontmatter":{"title":"Agent Harness — Agent Skill for Codex & OpenClaw","description":"Turn any domain folder of skills into a bounded agentic loop: compile a goal into a verifiable task plan, execute tasks with the domain's own tools."},"isInternal":false,"tokens":2027,"sizeBytes":8370},{"name":"agent-memory.md","path":"docs/skills/engineering/agent-memory.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agent-memory.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagent-memory.md -->","frontmatter":{"title":"Agent Memory — promotion is earned, not asserted — Agent Skill for Codex & OpenClaw","description":"Use when a project's CLAUDE.md has grown past what anyone reads and you want the agent to learn durable facts from its own sessions instead — or when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1238,"sizeBytes":5120},{"name":"agent-regression-evals.md","path":"docs/skills/engineering/agent-regression-evals.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agent-regression-evals.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagent-regression-evals.md -->","frontmatter":{"title":"Agent Regression Evals — prove the change did not make it worse — Agent Skill for Codex & OpenClaw","description":"Use when an agent, prompt, model or tool change needs proof it did not make the agent worse — setting up a regression eval suite, deciding whether a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1569,"sizeBytes":6191},{"name":"agent-workflow-designer.md","path":"docs/skills/engineering/agent-workflow-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agent-workflow-designer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagent-workflow-designer.md -->","frontmatter":{"title":"Agent Workflow Designer — Agent Skill for Codex & OpenClaw","description":"Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":663,"sizeBytes":3139},{"name":"agenthub-board.md","path":"docs/skills/engineering/agenthub-board.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-board.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-board.md -->","frontmatter":{"title":"/hub:board — Message Board — Agent Skill for Codex & OpenClaw","description":"Read, write, and browse the AgentHub message board for agent coordination. Use when the user runs /hub:board or asks to post, read, or inspect. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":741,"sizeBytes":3006},{"name":"agenthub-eval.md","path":"docs/skills/engineering/agenthub-eval.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-eval.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-eval.md -->","frontmatter":{"title":"/hub:eval — Evaluate Agent Results — Agent Skill for Codex & OpenClaw","description":"Evaluate and rank agent results by metric or LLM judge for an AgentHub session. Use when the user runs /hub:eval or asks to score, compare, or pick a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":794,"sizeBytes":3061},{"name":"agenthub-hub-init.md","path":"docs/skills/engineering/agenthub-hub-init.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-hub-init.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-hub-init.md -->","frontmatter":{"title":"/hub:hub-init — Create New Session — Agent Skill for Codex & OpenClaw","description":"Create a new AgentHub collaboration session with task, agent count, and evaluation criteria. Use when the user runs /hub:hub-init or asks to start a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":872,"sizeBytes":3425},{"name":"agenthub-hub-run.md","path":"docs/skills/engineering/agenthub-hub-run.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-hub-run.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-hub-run.md -->","frontmatter":{"title":"/hub:hub-run — One-Shot Lifecycle — Agent Skill for Codex & OpenClaw","description":"One-shot lifecycle command that chains init → baseline → spawn → eval → merge in a single invocation. Use when the user runs /hub:hub-run or asks to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1154,"sizeBytes":4515},{"name":"agenthub-hub-status.md","path":"docs/skills/engineering/agenthub-hub-status.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-hub-status.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-hub-status.md -->","frontmatter":{"title":"/hub:hub-status — Session Status — Agent Skill for Codex & OpenClaw","description":"Show DAG state, agent progress, and branch status for an AgentHub session. Use when the user runs /hub:hub-status or asks how the AgentHub agents are. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":871,"sizeBytes":3111},{"name":"agenthub-init.md","path":"docs/skills/engineering/agenthub-init.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-init.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-init.md -->","frontmatter":{"title":"/hub:hub-init — Create New Session — Agent Skill for Codex & OpenClaw","description":"Create a new AgentHub collaboration session with task, agent count, and evaluation criteria. Use when the user runs /hub:hub-init or asks to start a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":871,"sizeBytes":3421},{"name":"agenthub-merge.md","path":"docs/skills/engineering/agenthub-merge.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-merge.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-merge.md -->","frontmatter":{"title":"/hub:merge — Merge Winner — Agent Skill for Codex & OpenClaw","description":"Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":761,"sizeBytes":2931},{"name":"agenthub-run.md","path":"docs/skills/engineering/agenthub-run.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-run.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-run.md -->","frontmatter":{"title":"/hub:run — One-Shot Lifecycle — Agent Skill for Codex & OpenClaw","description":"One-shot lifecycle command that chains init → baseline → spawn → eval → merge in a single invocation. Use when the user runs /hub:run or asks to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1144,"sizeBytes":4479},{"name":"agenthub-spawn.md","path":"docs/skills/engineering/agenthub-spawn.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-spawn.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-spawn.md -->","frontmatter":{"title":"/hub:spawn — Launch Parallel Agents — Agent Skill for Codex & OpenClaw","description":"Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":943,"sizeBytes":4034},{"name":"agenthub-status.md","path":"docs/skills/engineering/agenthub-status.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub-status.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub-status.md -->","frontmatter":{"title":"/hub:hub-status — Session Status — Agent Skill for Codex & OpenClaw","description":"Show DAG state, agent progress, and branch status for an AgentHub session. Use when the user runs /hub:hub-status or asks how the AgentHub agents are. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":870,"sizeBytes":3107},{"name":"agenthub.md","path":"docs/skills/engineering/agenthub.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/agenthub.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fagenthub.md -->","frontmatter":{"title":"AgentHub — Multi-Agent Collaboration — Agent Skill for Codex & OpenClaw","description":"Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2005,"sizeBytes":8181},{"name":"api-design-reviewer.md","path":"docs/skills/engineering/api-design-reviewer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/api-design-reviewer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fapi-design-reviewer.md -->","frontmatter":{"title":"API Design Reviewer — Agent Skill for Codex & OpenClaw","description":"Comprehensive REST API design review with automated linting, breaking-change detection, and design scorecards. Catches inconsistent conventions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3134,"sizeBytes":13332},{"name":"api-test-suite-builder.md","path":"docs/skills/engineering/api-test-suite-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/api-test-suite-builder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fapi-test-suite-builder.md -->","frontmatter":{"title":"API Test Suite Builder — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to generate API tests, create integration test suites, test REST endpoints, or build contract tests. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1856,"sizeBytes":6944},{"name":"autoresearch-agent-ar-resume.md","path":"docs/skills/engineering/autoresearch-agent-ar-resume.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-ar-resume.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-ar-resume.md -->","frontmatter":{"title":"/ar:ar-resume — Resume Experiment — Agent Skill for Codex & OpenClaw","description":"Resume a paused experiment. Checkout the experiment branch, read results history, continue iterating. Use when the user runs /ar:ar-resume or asks to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":704,"sizeBytes":2710},{"name":"autoresearch-agent-ar-run.md","path":"docs/skills/engineering/autoresearch-agent-ar-run.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-ar-run.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-ar-run.md -->","frontmatter":{"title":"/ar:ar-run — Single Experiment Iteration — Agent Skill for Codex & OpenClaw","description":"Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:ar-run or asks for one manual. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":766,"sizeBytes":3146},{"name":"autoresearch-agent-ar-status.md","path":"docs/skills/engineering/autoresearch-agent-ar-status.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-ar-status.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-ar-status.md -->","frontmatter":{"title":"/ar:ar-status — Experiment Dashboard — Agent Skill for Codex & OpenClaw","description":"Show experiment dashboard with results, active loops, and progress. Use when the user runs /ar:ar-status or asks how an autoresearch experiment is. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":645,"sizeBytes":2573},{"name":"autoresearch-agent-loop.md","path":"docs/skills/engineering/autoresearch-agent-loop.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-loop.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-loop.md -->","frontmatter":{"title":"/ar:loop — Autonomous Experiment Loop — Agent Skill for Codex & OpenClaw","description":"Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling. Use when the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1227,"sizeBytes":4769},{"name":"autoresearch-agent-resume.md","path":"docs/skills/engineering/autoresearch-agent-resume.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-resume.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-resume.md -->","frontmatter":{"title":"/ar:ar-resume — Resume Experiment — Agent Skill for Codex & OpenClaw","description":"Resume a paused experiment. Checkout the experiment branch, read results history, continue iterating. Use when the user runs /ar:ar-resume or asks to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":700,"sizeBytes":2701},{"name":"autoresearch-agent-run.md","path":"docs/skills/engineering/autoresearch-agent-run.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-run.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-run.md -->","frontmatter":{"title":"/ar:run — Single Experiment Iteration — Agent Skill for Codex & OpenClaw","description":"Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:run or asks for one manual. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":759,"sizeBytes":3125},{"name":"autoresearch-agent-setup.md","path":"docs/skills/engineering/autoresearch-agent-setup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-setup.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-setup.md -->","frontmatter":{"title":"/ar:setup — Create New Experiment — Agent Skill for Codex & OpenClaw","description":"Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator. Use when the user. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":899,"sizeBytes":3520},{"name":"autoresearch-agent-status.md","path":"docs/skills/engineering/autoresearch-agent-status.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent-status.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent-status.md -->","frontmatter":{"title":"/ar:ar-status — Experiment Dashboard — Agent Skill for Codex & OpenClaw","description":"Show experiment dashboard with results, active loops, and progress. Use when the user runs /ar:ar-status or asks how an autoresearch experiment is going. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":645,"sizeBytes":2576},{"name":"autoresearch-agent.md","path":"docs/skills/engineering/autoresearch-agent.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/autoresearch-agent.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fautoresearch-agent.md -->","frontmatter":{"title":"Autoresearch Agent — Agent Skill for Codex & OpenClaw","description":"Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2986,"sizeBytes":12466},{"name":"behuman.md","path":"docs/skills/engineering/behuman.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/behuman.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fbehuman.md -->","frontmatter":{"title":"BeHuman — Self-Mirror Consciousness Loop — Agent Skill for Codex & OpenClaw","description":"Use when the user wants more human-like AI responses — less robotic, less listy, more authentic. Triggers: 'behuman', 'be real', 'like a human'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1953,"sizeBytes":8523},{"name":"book-to-skill.md","path":"docs/skills/engineering/book-to-skill.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/book-to-skill.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fbook-to-skill.md -->","frontmatter":{"title":"Book-to-Skill Converter — Agent Skill for Codex & OpenClaw","description":"Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2959,"sizeBytes":12108},{"name":"boost-asio-pro.md","path":"docs/skills/engineering/boost-asio-pro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/boost-asio-pro.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fboost-asio-pro.md -->","frontmatter":{"title":"Boost.Asio / standalone Asio — Agent Skill for Codex & OpenClaw","description":"Use when writing or reviewing asynchronous C++ networking code with Boost.Asio or standalone Asio — TCP/UDP servers and clients, SSL/TLS, timers. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3031,"sizeBytes":11549},{"name":"browser-automation.md","path":"docs/skills/engineering/browser-automation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/browser-automation.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fbrowser-automation.md -->","frontmatter":{"title":"Browser Automation — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to automate browser tasks, scrape websites, fill forms, capture screenshots, extract structured data from web pages, or build. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3360,"sizeBytes":15126},{"name":"caveman.md","path":"docs/skills/engineering/caveman.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/caveman.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fcaveman.md -->","frontmatter":{"title":"Caveman Mode — Agent Skill for Codex & OpenClaw","description":"Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":787,"sizeBytes":3154},{"name":"changelog-generator.md","path":"docs/skills/engineering/changelog-generator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/changelog-generator.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fchangelog-generator.md -->","frontmatter":{"title":"Changelog Generator — Agent Skill for Codex & OpenClaw","description":"Produce consistent, auditable release notes from Conventional Commits. Separates commit parsing, semantic-bump logic, and changelog rendering for. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2011,"sizeBytes":8475},{"name":"chaos-engineering.md","path":"docs/skills/engineering/chaos-engineering.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/chaos-engineering.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fchaos-engineering.md -->","frontmatter":{"title":"Chaos Engineering — Agent Skill for Codex & OpenClaw","description":"Use when planning, running, or learning from chaos engineering experiments. Triggers on 'chaos experiment', 'fault injection', 'gameday', 'resilience. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2485,"sizeBytes":10515},{"name":"ci-cd-pipeline-builder.md","path":"docs/skills/engineering/ci-cd-pipeline-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/ci-cd-pipeline-builder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fci-cd-pipeline-builder.md -->","frontmatter":{"title":"CI/CD Pipeline Builder — Agent Skill for Codex & OpenClaw","description":"Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":982,"sizeBytes":4221},{"name":"claude-coach.md","path":"docs/skills/engineering/claude-coach.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/claude-coach.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fclaude-coach.md -->","frontmatter":{"title":"Claude Coach — Your Power-User Companion — Agent Skill for Codex & OpenClaw","description":"Personal coach that teaches users to become Claude power users. Use this skill the FIRST time a user asks to 'learn Claude', 'be a power user'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1976,"sizeBytes":8583},{"name":"code-tour.md","path":"docs/skills/engineering/code-tour.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/code-tour.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fcode-tour.md -->","frontmatter":{"title":"Code Tour — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to create a CodeTour .tour file — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1761,"sizeBytes":6765},{"name":"codebase-onboarding.md","path":"docs/skills/engineering/codebase-onboarding.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/codebase-onboarding.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fcodebase-onboarding.md -->","frontmatter":{"title":"Codebase Onboarding — Agent Skill for Codex & OpenClaw","description":"Analyze a codebase and generate onboarding documentation for engineers, tech leads, and contractors. Fast fact-gathering and repeatable onboarding. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":672,"sizeBytes":3082},{"name":"coding-agent-rollout.md","path":"docs/skills/engineering/coding-agent-rollout.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/coding-agent-rollout.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fcoding-agent-rollout.md -->","frontmatter":{"title":"Claude Code Team Rollout — Agent Skill for Codex & OpenClaw","description":"Use when rolling Claude Code out to a team or organization, or auditing a rollout already under way — writing or reviewing shared and managed."},"isInternal":false,"tokens":1421,"sizeBytes":5739},{"name":"collab-proof.md","path":"docs/skills/engineering/collab-proof.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/collab-proof.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fcollab-proof.md -->","frontmatter":{"title":"collab-proof — Agent Skill for Codex & OpenClaw","description":"Use when you want to understand what Claude contributed vs what you drove in a session. Triggers on: /collab-proof, session retrospective, ai. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3813,"sizeBytes":15103},{"name":"data-quality-auditor.md","path":"docs/skills/engineering/data-quality-auditor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/data-quality-auditor.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdata-quality-auditor.md -->","frontmatter":{"title":"Profile from CSV — Agent Skill for Codex & OpenClaw","description":"Audit datasets for completeness, consistency, accuracy, and validity. Profile data distributions, detect anomalies and outliers, surface structural. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2241,"sizeBytes":9600},{"name":"database-designer.md","path":"docs/skills/engineering/database-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/database-designer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdatabase-designer.md -->","frontmatter":{"title":"Database Designer - POWERFUL Tier Skill — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to design database schemas, plan data migrations, optimize queries, choose between SQL and NoSQL, or model data relationships. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3039,"sizeBytes":13418},{"name":"database-schema-designer.md","path":"docs/skills/engineering/database-schema-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/database-schema-designer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdatabase-schema-designer.md -->","frontmatter":{"title":"Database Schema Designer — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to create ERD diagrams, normalize database schemas, design table relationships, or plan schema migrations. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1989,"sizeBytes":8141},{"name":"deep-learning-book.md","path":"docs/skills/engineering/deep-learning-book.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/deep-learning-book.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdeep-learning-book.md -->","frontmatter":{"title":"Deep Learning — Study Companion — Agent Skill for Codex & OpenClaw","description":"Study companion and working knowledge base for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), read free at. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3094,"sizeBytes":12199},{"name":"demo-video.md","path":"docs/skills/engineering/demo-video.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/demo-video.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdemo-video.md -->","frontmatter":{"title":"Demo Video — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to create a demo video, product walkthrough, feature showcase, animated presentation, marketing video, or GIF from screenshots. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1423,"sizeBytes":5786},{"name":"dependency-auditor.md","path":"docs/skills/engineering/dependency-auditor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/dependency-auditor.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdependency-auditor.md -->","frontmatter":{"title":"Dependency Auditor — Agent Skill for Codex & OpenClaw","description":"Audit and manage dependencies across multi-language projects. Identifies vulnerabilities, license conflicts, transitive dependency risks, and. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1152,"sizeBytes":5044},{"name":"docker-development.md","path":"docs/skills/engineering/docker-development.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/docker-development.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fdocker-development.md -->","frontmatter":{"title":"Docker Development — Agent Skill for Codex & OpenClaw","description":"Docker and container development agent skill and plugin for Dockerfile optimization, docker-compose orchestration, multi-stage builds, and container. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2900,"sizeBytes":12083},{"name":"engineering-advanced-skills.md","path":"docs/skills/engineering/engineering-advanced-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/engineering-advanced-skills.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fengineering-advanced-skills.md -->","frontmatter":{"title":"Engineering Advanced Skills (POWERFUL Tier) — Agent Skill for Codex & OpenClaw","description":"Index of 37 advanced engineering agent skills for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Use when browsing or choosing among the."},"isInternal":false,"tokens":1085,"sizeBytes":4481},{"name":"engineering.md","path":"docs/skills/engineering/engineering.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/engineering.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fengineering.md -->","frontmatter":{"title":"Engineering Advanced Skills (POWERFUL Tier) — Agent Skill for Codex & OpenClaw","description":"25 advanced engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Agent design, RAG, MCP servers, CI/CD."},"isInternal":false,"tokens":749,"sizeBytes":3094},{"name":"env-secrets-manager.md","path":"docs/skills/engineering/env-secrets-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/env-secrets-manager.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fenv-secrets-manager.md -->","frontmatter":{"title":"Env & Secrets Manager — Agent Skill for Codex & OpenClaw","description":"Manage environment-variable hygiene and secrets safety across local development and production. Practical auditing, drift awareness, rotation. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2402,"sizeBytes":11137},{"name":"feature-flags-architect.md","path":"docs/skills/engineering/feature-flags-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/feature-flags-architect.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Ffeature-flags-architect.md -->","frontmatter":{"title":"Feature Flags Architect — Agent Skill for Codex & OpenClaw","description":"Use when adding, retiring, or auditing feature flags. Triggers on 'add a flag', 'ship behind a flag', 'rollout plan', 'kill switch', 'stale flags'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2473,"sizeBytes":9822},{"name":"focused-fix.md","path":"docs/skills/engineering/focused-fix.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/focused-fix.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Ffocused-fix.md -->","frontmatter":{"title":"Focused Fix — Deep-Dive Feature Repair — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to fix, debug, or make a specific feature/module/area work end-to-end. Triggers: 'make X work', 'fix the Y feature', 'the Z. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3560,"sizeBytes":14731},{"name":"full-page-screenshot.md","path":"docs/skills/engineering/full-page-screenshot.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/full-page-screenshot.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Ffull-page-screenshot.md -->","frontmatter":{"title":"Full Page Screenshot — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to capture a full-page screenshot, long screenshot, or complete page capture of a web page. Handles SPA scroll containers. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1534,"sizeBytes":6185},{"name":"git-worktree-manager.md","path":"docs/skills/engineering/git-worktree-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/git-worktree-manager.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fgit-worktree-manager.md -->","frontmatter":{"title":"Git Worktree Manager — Agent Skill for Codex & OpenClaw","description":"Run parallel feature work safely with Git worktrees. Standardizes branch isolation, port allocation, environment sync, and cleanup so each worktree. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1798,"sizeBytes":7930},{"name":"grill-me.md","path":"docs/skills/engineering/grill-me.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/grill-me.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fgrill-me.md -->","frontmatter":{"title":"Grill Me — Agent Skill for Codex & OpenClaw","description":"Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":739,"sizeBytes":3042},{"name":"grill-with-docs.md","path":"docs/skills/engineering/grill-with-docs.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/grill-with-docs.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fgrill-with-docs.md -->","frontmatter":{"title":"Grill with Docs — Agent Skill for Codex & OpenClaw","description":"Docs-anchored grilling session — challenges a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), and. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2014,"sizeBytes":8213},{"name":"handoff.md","path":"docs/skills/engineering/handoff.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/handoff.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fhandoff.md -->","frontmatter":{"title":"Handoff — Agent Skill for Codex & OpenClaw","description":"Compact the current conversation into a handoff document for another agent to pick up. References existing artifacts (PRDs, plans, ADRs, issues. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":619,"sizeBytes":2393},{"name":"helm-chart-builder.md","path":"docs/skills/engineering/helm-chart-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/helm-chart-builder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fhelm-chart-builder.md -->","frontmatter":{"title":"Helm Chart Builder — Agent Skill for Codex & OpenClaw","description":"Helm chart development agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw — chart scaffolding, values design, template."},"isInternal":false,"tokens":3653,"sizeBytes":15629},{"name":"hivemind.md","path":"docs/skills/engineering/hivemind.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/hivemind.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fhivemind.md -->","frontmatter":{"title":"Hivemind: Claude Code as Orchestrator, opencode as Free Worker Swarm — Agent Skill for Codex & OpenClaw","description":"Orchestrate free opencode workers from Claude Code to cut token costs. Use when delegating grunt work to a single worker or a parallel swarm."},"isInternal":false,"tokens":3171,"sizeBytes":12594},{"name":"human-gate.md","path":"docs/skills/engineering/human-gate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/human-gate.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fhuman-gate.md -->","frontmatter":{"title":"Human Gate — Agent Skill for Codex & OpenClaw","description":"Runs the human-verification lane of an agent loop, and proves review happened before work is called done. Builds a single-file HTML review page. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1524,"sizeBytes":5861},{"name":"index.md","path":"docs/skills/engineering/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/index.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Findex.md -->","frontmatter":{"title":"Engineering - POWERFUL Skills — Agent Skills & Codex Plugins","description":"90 engineering - powerful skills — advanced agent-native skill and Claude Code plugin for AI agent design, infrastructure, and automation. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":1704,"sizeBytes":6959},{"name":"interview-system-designer.md","path":"docs/skills/engineering/interview-system-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/interview-system-designer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Finterview-system-designer.md -->","frontmatter":{"title":"Interview System Designer — Agent Skill for Codex & OpenClaw","description":"This skill should be used when the user asks to 'design interview processes', 'create hiring pipelines', 'calibrate interview loops', 'generate. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":569,"sizeBytes":2649},{"name":"karpathy-coder.md","path":"docs/skills/engineering/karpathy-coder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/karpathy-coder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fkarpathy-coder.md -->","frontmatter":{"title":"Karpathy Coder — Active Coding Discipline — Agent Skill for Codex & OpenClaw","description":"Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1460,"sizeBytes":5940},{"name":"kubernetes-operator.md","path":"docs/skills/engineering/kubernetes-operator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/kubernetes-operator.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fkubernetes-operator.md -->","frontmatter":{"title":"Kubernetes Operator — Agent Skill for Codex & OpenClaw","description":"Use when building a Kubernetes Operator — custom controllers that reconcile CRD state. Triggers on 'build an operator', 'CRD design', 'reconcile. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2707,"sizeBytes":11165},{"name":"llm-cost-optimizer.md","path":"docs/skills/engineering/llm-cost-optimizer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/llm-cost-optimizer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fllm-cost-optimizer.md -->","frontmatter":{"title":"LLM Cost Optimizer — Agent Skill for Codex & OpenClaw","description":"Use proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize token usage', 'which model. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2515,"sizeBytes":11552},{"name":"llm-wiki.md","path":"docs/skills/engineering/llm-wiki.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/llm-wiki.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fllm-wiki.md -->","frontmatter":{"title":"LLM Wiki — Second Brain for Claude Code + Obsidian — Agent Skill for Codex & OpenClaw","description":"Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2565,"sizeBytes":10386},{"name":"mcp-server-builder.md","path":"docs/skills/engineering/mcp-server-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/mcp-server-builder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fmcp-server-builder.md -->","frontmatter":{"title":"MCP Server Builder — Agent Skill for Codex & OpenClaw","description":"Design and ship production-ready MCP (Model Context Protocol) servers from OpenAPI contracts instead of hand-written tool wrappers. Python and."},"isInternal":false,"tokens":1104,"sizeBytes":4973},{"name":"memory-engineering.md","path":"docs/skills/engineering/memory-engineering.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/memory-engineering.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fmemory-engineering.md -->","frontmatter":{"title":"Memory Engineering — engineer the forgetting, not just the remembering — Agent Skill for Codex & OpenClaw","description":"Use when designing, reviewing, or paying for an agent memory system — adding memory to an agent, choosing between long-context / RAG / graph /. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1775,"sizeBytes":7343},{"name":"migration-architect.md","path":"docs/skills/engineering/migration-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/migration-architect.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fmigration-architect.md -->","frontmatter":{"title":"Migration Architect — Agent Skill for Codex & OpenClaw","description":"Zero-downtime migration planning, compatibility validation, and rollback strategy generation. Tools for system, database, and infrastructure. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3474,"sizeBytes":17168},{"name":"minimalist.md","path":"docs/skills/engineering/minimalist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/minimalist.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fminimalist.md -->","frontmatter":{"title":"Minimalist — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to write code efficiently, avoid over-engineering, reduce dependencies, or prevent unnecessary abstractions. Enforces a strict. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":877,"sizeBytes":3744},{"name":"monorepo-navigator.md","path":"docs/skills/engineering/monorepo-navigator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/monorepo-navigator.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fmonorepo-navigator.md -->","frontmatter":{"title":"Monorepo Navigator — Agent Skill for Codex & OpenClaw","description":"Navigate, manage, and optimize monorepos. Covers Turborepo, Nx, pnpm workspaces, and Lerna. Cross-package impact analysis, selective builds/tests on. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1235,"sizeBytes":5303},{"name":"observability-designer.md","path":"docs/skills/engineering/observability-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/observability-designer.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fobservability-designer.md -->","frontmatter":{"title":"Observability Designer (POWERFUL) — Agent Skill for Codex & OpenClaw","description":"Design production-ready observability strategies combining metrics, logs, and traces. Includes SLI/SLO design, golden-signals monitoring, alert. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2860,"sizeBytes":14379},{"name":"performance-profiler.md","path":"docs/skills/engineering/performance-profiler.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/performance-profiler.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fperformance-profiler.md -->","frontmatter":{"title":"Performance Profiler — Agent Skill for Codex & OpenClaw","description":"Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks, generates flamegraphs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":790,"sizeBytes":3353},{"name":"pr-review-expert.md","path":"docs/skills/engineering/pr-review-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/pr-review-expert.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fpr-review-expert.md -->","frontmatter":{"title":"PR Review Expert — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to review pull requests, analyze code changes, check for security issues in PRs, or assess code quality of diffs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3576,"sizeBytes":13270},{"name":"prompt-governance.md","path":"docs/skills/engineering/prompt-governance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/prompt-governance.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fprompt-governance.md -->","frontmatter":{"title":"Prompt Governance — Agent Skill for Codex & OpenClaw","description":"Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2499,"sizeBytes":11472},{"name":"rag-architect.md","path":"docs/skills/engineering/rag-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/rag-architect.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Frag-architect.md -->","frontmatter":{"title":"RAG Architect — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1210,"sizeBytes":4850},{"name":"runbook-generator.md","path":"docs/skills/engineering/runbook-generator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/runbook-generator.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Frunbook-generator.md -->","frontmatter":{"title":"Runbook Generator — Agent Skill for Codex & OpenClaw","description":"Generate operational runbooks from a service name — deployment, incident response, maintenance, and rollback workflows. Templated structure. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":563,"sizeBytes":2576},{"name":"secrets-vault-manager.md","path":"docs/skills/engineering/secrets-vault-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/secrets-vault-manager.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fsecrets-vault-manager.md -->","frontmatter":{"title":"Secrets Vault Manager — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to set up secret management infrastructure, integrate HashiCorp Vault, configure cloud secret stores (AWS Secrets Manager. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3483,"sizeBytes":15121},{"name":"security-guidance.md","path":"docs/skills/engineering/security-guidance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/security-guidance.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fsecurity-guidance.md -->","frontmatter":{"title":"Security Guidance Hook — Agent Skill for Codex & OpenClaw","description":"PreToolUse security-anti-pattern hook for Claude Code. Catches 12 common security risks (command injection, XSS, SQL injection, unsafe."},"isInternal":false,"tokens":1838,"sizeBytes":7744},{"name":"self-eval.md","path":"docs/skills/engineering/self-eval.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/self-eval.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fself-eval.md -->","frontmatter":{"title":"Self-Eval: Honest Work Evaluation — Agent Skill for Codex & OpenClaw","description":"Honestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2041,"sizeBytes":8967},{"name":"ship-gate.md","path":"docs/skills/engineering/ship-gate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/ship-gate.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fship-gate.md -->","frontmatter":{"title":"Ship Gate — Agent Skill for Codex & OpenClaw","description":"Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1771,"sizeBytes":6867},{"name":"skill-doctor.md","path":"docs/skills/engineering/skill-doctor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/skill-doctor.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fskill-doctor.md -->","frontmatter":{"title":"skill-doctor — grade the agent setup from real sessions — Agent Skill for Codex & OpenClaw","description":"Use when the user wants their agent setup graded from real conversation history, asks which installed skills are actually working, or wants."},"isInternal":false,"tokens":1641,"sizeBytes":6656},{"name":"skill-security-auditor.md","path":"docs/skills/engineering/skill-security-auditor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/skill-security-auditor.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fskill-security-auditor.md -->","frontmatter":{"title":"Skill Security Auditor — Agent Skill for Codex & OpenClaw","description":"Security audit and vulnerability scanner for AI agent skills before installation. Use when: (1) evaluating a skill from an untrusted source, (2)."},"isInternal":false,"tokens":2036,"sizeBytes":8060},{"name":"skill-tester.md","path":"docs/skills/engineering/skill-tester.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/skill-tester.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fskill-tester.md -->","frontmatter":{"title":"Skill Tester — Agent Skill for Codex & OpenClaw","description":"Validate, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1300,"sizeBytes":5376},{"name":"skillopt-sleep.md","path":"docs/skills/engineering/skillopt-sleep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/skillopt-sleep.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fskillopt-sleep.md -->","frontmatter":{"title":"SkillOpt-Sleep: offline self-evolution for a local Claude agent — Agent Skill for Codex & OpenClaw","description":"Use when the user wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1917,"sizeBytes":7515},{"name":"slo-architect.md","path":"docs/skills/engineering/slo-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/slo-architect.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fslo-architect.md -->","frontmatter":{"title":"SLO Architect — Agent Skill for Codex & OpenClaw","description":"Use when defining, reviewing, or operating SLOs/SLIs/error budgets. Triggers on 'define an SLO', 'what should our SLO be', 'error budget', 'burn. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2822,"sizeBytes":10945},{"name":"spec-driven-workflow.md","path":"docs/skills/engineering/spec-driven-workflow.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/spec-driven-workflow.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fspec-driven-workflow.md -->","frontmatter":{"title":"Spec-Driven Workflow — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to write specs before code, define acceptance criteria, plan features before implementation, generate tests from. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3727,"sizeBytes":16499},{"name":"spinning-up-deep-rl.md","path":"docs/skills/engineering/spinning-up-deep-rl.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/spinning-up-deep-rl.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fspinning-up-deep-rl.md -->","isInternal":false,"tokens":3056,"sizeBytes":11503},{"name":"sql-database-assistant.md","path":"docs/skills/engineering/sql-database-assistant.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/sql-database-assistant.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fsql-database-assistant.md -->","frontmatter":{"title":"SQL Database Assistant - POWERFUL Tier Skill — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to write SQL queries, optimize database performance, generate migrations, explore database schemas, or work with ORMs like. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4012,"sizeBytes":16694},{"name":"statistical-analyst.md","path":"docs/skills/engineering/statistical-analyst.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/statistical-analyst.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fstatistical-analyst.md -->","frontmatter":{"title":"Z-test for two proportions (A/B conversion rates) — Agent Skill for Codex & OpenClaw","description":"Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes. Use when you. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2699,"sizeBytes":10708},{"name":"strict-api.md","path":"docs/skills/engineering/strict-api.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/strict-api.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fstrict-api.md -->","frontmatter":{"title":"Strict API Verification — Agent Skill for Codex & OpenClaw","description":"Use when the user says 'no hallucinations', 'verify APIs', 'reality check', or 'don't invent functions'. Prevents the agent from calling methods. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":919,"sizeBytes":3888},{"name":"tc-tracker.md","path":"docs/skills/engineering/tc-tracker.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/tc-tracker.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Ftc-tracker.md -->","frontmatter":{"title":"TC Tracker — Agent Skill for Codex & OpenClaw","description":"Use when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions. Covers. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2785,"sizeBytes":11367},{"name":"tech-debt-tracker.md","path":"docs/skills/engineering/tech-debt-tracker.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/tech-debt-tracker.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Ftech-debt-tracker.md -->","frontmatter":{"title":"Tech Debt Tracker — Agent Skill for Codex & OpenClaw","description":"Scan codebases for technical debt, score severity, track trends, and generate prioritized remediation plans. Use when users mention tech debt, code. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1121,"sizeBytes":5203},{"name":"terraform-patterns.md","path":"docs/skills/engineering/terraform-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/terraform-patterns.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fterraform-patterns.md -->","frontmatter":{"title":"Terraform Patterns — Agent Skill for Codex & OpenClaw","description":"Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state."},"isInternal":false,"tokens":5437,"sizeBytes":22494},{"name":"universal-scraping-architect.md","path":"docs/skills/engineering/universal-scraping-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/universal-scraping-architect.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Funiversal-scraping-architect.md -->","frontmatter":{"title":"Universal Scraping Architect — Agent Skill for Codex & OpenClaw","description":"Use for web scraping, crawling, document extraction, API parsing, or building validation-heavy data pipelines using Firecrawl or local Python scripts. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1188,"sizeBytes":5274},{"name":"workflow-builder.md","path":"docs/skills/engineering/workflow-builder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/workflow-builder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fworkflow-builder.md -->","frontmatter":{"title":"Workflow Builder — Agent Skill for Codex & OpenClaw","description":"Design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool. Use when a user wants."},"isInternal":false,"tokens":1385,"sizeBytes":5874},{"name":"write-a-skill.md","path":"docs/skills/engineering/write-a-skill.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/write-a-skill.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fwrite-a-skill.md -->","frontmatter":{"title":"Writing Skills — Agent Skill for Codex & OpenClaw","description":"Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1269,"sizeBytes":5413},{"name":"zero-hallucination-coder.md","path":"docs/skills/engineering/zero-hallucination-coder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/engineering/zero-hallucination-coder.md","title":"Engineering Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fengineering%2Fzero-hallucination-coder.md -->","frontmatter":{"title":"Zero-Hallucination Coder — Agent Skill for Codex & OpenClaw","description":"Runs a disciplined Discuss → Map → Decompose → Execute → Verify loop that grounds code in verified structure — no invented APIs, no assumed imports. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3342,"sizeBytes":14149},{"name":"business-investment-advisor.md","path":"docs/skills/finance/business-investment-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/business-investment-advisor.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Fbusiness-investment-advisor.md -->","frontmatter":{"title":"Business Investment Advisor — Agent Skill for Finance","description":"Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2366,"sizeBytes":10419},{"name":"finance-skills.md","path":"docs/skills/finance/finance-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/finance-skills.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Ffinance-skills.md -->","frontmatter":{"title":"Finance Skills — Router — Agent Skill for Finance","description":"Router/index for the finance skills bundled in this plugin: financial-analyst (ratio analysis, DCF valuation, budget variance, rolling forecasts). Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":566,"sizeBytes":2344},{"name":"finance.md","path":"docs/skills/finance/finance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/finance.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Ffinance.md -->","frontmatter":{"title":"Finance Skills — Agent Skill for Finance","description":"Financial analyst agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Ratio analysis, DCF valuation, budget variance."},"isInternal":false,"tokens":382,"sizeBytes":1540},{"name":"financial-analyst.md","path":"docs/skills/finance/financial-analyst.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/financial-analyst.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Ffinancial-analyst.md -->","frontmatter":{"title":"Financial Analyst Skill — Agent Skill for Finance","description":"Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1638,"sizeBytes":7520},{"name":"index.md","path":"docs/skills/finance/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/index.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Findex.md -->","frontmatter":{"title":"Finance Skills — Agent Skills & Codex Plugins","description":"7 finance skills — finance agent skill and Claude Code plugin for DCF valuation, budgeting, and SaaS metrics. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":386,"sizeBytes":1633},{"name":"month-end-close.md","path":"docs/skills/finance/month-end-close.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/month-end-close.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Fmonth-end-close.md -->","frontmatter":{"title":"Month-End Close — Agent Skill for Finance","description":"Use when running, planning or speeding up a month-end (or quarter-end) close — building or reviewing the close checklist and calendar, reconciling a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1442,"sizeBytes":5921},{"name":"passive-deal-screener.md","path":"docs/skills/finance/passive-deal-screener.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/passive-deal-screener.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Fpassive-deal-screener.md -->","frontmatter":{"title":"Passive Deal Screener — Agent Skill for Finance","description":"Screens private investment opportunities from the passive LP (limited-partner) perspective — equity syndications, preferred equity, hard money /. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2617,"sizeBytes":10123},{"name":"saas-metrics-coach.md","path":"docs/skills/finance/saas-metrics-coach.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/saas-metrics-coach.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Fsaas-metrics-coach.md -->","frontmatter":{"title":"SaaS Metrics Coach — Agent Skill for Finance","description":"SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how their SaaS. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1574,"sizeBytes":6223},{"name":"stock-analysis.md","path":"docs/skills/finance/stock-analysis.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/finance/stock-analysis.md","title":"Finance Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Ffinance%2Fstock-analysis.md -->","frontmatter":{"title":"Stock Analysis — Agent Skill for Finance","description":"Produce a rigorous, sector-relative, multi-factor fundamental analysis of a publicly listed company — Indian (NSE/BSE) or US/global. Use when the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":7556,"sizeBytes":33992},{"name":"index.md","path":"docs/skills/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/index.md","title":"Skills Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Findex.md -->","frontmatter":{"title":"345 Agent Skills — Browse by Domain","description":"Browse 345 production-ready agent skills across 17 domains — engineering, product, marketing, C-level advisory, compliance, commercial, research, and finance. Installable as Claude Code plugins, Codex skills, Gemini CLI skills, and 10 more AI coding tools.","hide":["edit"]},"isInternal":false,"tokens":2507,"sizeBytes":9994},{"name":"design-system.md","path":"docs/skills/markdown-html/design-system.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/markdown-html/design-system.md","title":"Markdown-html Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarkdown-html%2Fdesign-system.md -->","frontmatter":{"title":"Design System — Onboarding + Shared Brand Tokens — Agent Skill for HTML Output","description":"Captures the user's brand identity once via a 10-question onboarding wizard (primary/accent HEX + heading + body Google Fonts + design style. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2820,"sizeBytes":10889},{"name":"index.md","path":"docs/skills/markdown-html/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/markdown-html/index.md","title":"Markdown-html Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarkdown-html%2Findex.md -->","frontmatter":{"title":"Markdown to HTML Skills — Agent Skills & Codex Plugins","description":"5 markdown to html skills — markdown-to-interactive-HTML converter agent skill and Claude Code plugin for single-file documents, code reviews, and slide decks. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":414,"sizeBytes":1727},{"name":"markdown-html-orchestrator.md","path":"docs/skills/markdown-html/markdown-html-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/markdown-html/markdown-html-orchestrator.md","title":"Markdown-html Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarkdown-html%2Fmarkdown-html-orchestrator.md -->","frontmatter":{"title":"Markdown → HTML — Domain Orchestrator — Agent Skill for HTML Output","description":"Use when a user wants to convert any markdown file in their Claude project into a single-file, lightly-interactive HTML — long-form documents (specs. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2694,"sizeBytes":10642},{"name":"md-document.md","path":"docs/skills/markdown-html/md-document.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/markdown-html/md-document.md","title":"Markdown-html Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarkdown-html%2Fmd-document.md -->","frontmatter":{"title":"md-document — Long-form Markdown to HTML — Agent Skill for HTML Output","description":"Converts long-form markdown (specs, RFCs, reports, plans, explainers) into a single-file, lightly-interactive HTML document with sticky TOC. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1576,"sizeBytes":6101},{"name":"md-review.md","path":"docs/skills/markdown-html/md-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/markdown-html/md-review.md","title":"Markdown-html Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarkdown-html%2Fmd-review.md -->","frontmatter":{"title":"md-review — Code-review markdown → 2-column HTML — Agent Skill for HTML Output","description":"Converts a markdown PR writeup or code review (one with ```diff fenced blocks and severity-tagged GFM callouts [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT]. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1601,"sizeBytes":6350},{"name":"md-slides.md","path":"docs/skills/markdown-html/md-slides.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/markdown-html/md-slides.md","title":"Markdown-html Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarkdown-html%2Fmd-slides.md -->","frontmatter":{"title":"md-slides — Markdown deck → single-file HTML presentation — Agent Skill for HTML Output","description":"Converts a markdown deck (slides separated by `---` HR boundaries or by `# ` H1 headings, with optional HTML-comment `notes:` presenter-notes blocks). Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1591,"sizeBytes":6294},{"name":"ab-test-setup.md","path":"docs/skills/marketing-skill/ab-test-setup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/ab-test-setup.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fab-test-setup.md -->","frontmatter":{"title":"A/B Test Setup — Agent Skill for Marketing","description":"When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions 'A/B test,' 'split test,' 'experiment,'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2476,"sizeBytes":10704},{"name":"ad-creative.md","path":"docs/skills/marketing-skill/ad-creative.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/ad-creative.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fad-creative.md -->","frontmatter":{"title":"Ad Creative — Agent Skill for Marketing","description":"When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2747,"sizeBytes":11671},{"name":"aeo.md","path":"docs/skills/marketing-skill/aeo.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/aeo.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Faeo.md -->","frontmatter":{"title":"Answer Engine Optimization (AEO) — Agent Skill for Marketing","description":"Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as."},"isInternal":false,"tokens":2674,"sizeBytes":10996},{"name":"ai-decision-authority.md","path":"docs/skills/marketing-skill/ai-decision-authority.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/ai-decision-authority.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fai-decision-authority.md -->","frontmatter":{"title":"AI Decision Authority — Agent Skill for Marketing","description":"Routes marketing and GTM decisions into three AI governance zones (AI-Primary, Collaborative, Human-Primary) by stakes and reversibility. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1393,"sizeBytes":6412},{"name":"analytics-tracking.md","path":"docs/skills/marketing-skill/analytics-tracking.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/analytics-tracking.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fanalytics-tracking.md -->","frontmatter":{"title":"Analytics Tracking — Agent Skill for Marketing","description":"Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3645,"sizeBytes":15447},{"name":"app-store-optimization.md","path":"docs/skills/marketing-skill/app-store-optimization.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/app-store-optimization.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fapp-store-optimization.md -->","frontmatter":{"title":"App Store Optimization (ASO) — Agent Skill for Marketing","description":"App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4350,"sizeBytes":18672},{"name":"brand-guidelines.md","path":"docs/skills/marketing-skill/brand-guidelines.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/brand-guidelines.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fbrand-guidelines.md -->","frontmatter":{"title":"Brand Guidelines — Agent Skill for Marketing","description":"When the user wants to apply, document, or enforce brand guidelines for any product or company. Also use when the user mentions 'brand guidelines,'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1149,"sizeBytes":5530},{"name":"business-name-fit.md","path":"docs/skills/marketing-skill/business-name-fit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/business-name-fit.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fbusiness-name-fit.md -->","frontmatter":{"title":"Business Name Fit — Agent Skill for Marketing","description":"Suggest, pick, or vet a business, startup, or product name that stays true to the founder's cultural origin while working professionally in the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2526,"sizeBytes":11249},{"name":"campaign-analytics.md","path":"docs/skills/marketing-skill/campaign-analytics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/campaign-analytics.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcampaign-analytics.md -->","frontmatter":{"title":"Campaign Analytics — Agent Skill for Marketing","description":"Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1909,"sizeBytes":8565},{"name":"churn-prevention.md","path":"docs/skills/marketing-skill/churn-prevention.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/churn-prevention.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fchurn-prevention.md -->","frontmatter":{"title":"Churn Prevention — Agent Skill for Marketing","description":"Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2665,"sizeBytes":11436},{"name":"cold-email.md","path":"docs/skills/marketing-skill/cold-email.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/cold-email.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcold-email.md -->","frontmatter":{"title":"Cold Email Outreach — Agent Skill for Marketing","description":"When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them. Use when the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3431,"sizeBytes":14735},{"name":"competitor-alternatives.md","path":"docs/skills/marketing-skill/competitor-alternatives.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/competitor-alternatives.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcompetitor-alternatives.md -->","frontmatter":{"title":"Competitor & Alternative Pages — Agent Skill for Marketing","description":"When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2497,"sizeBytes":11473},{"name":"content-creator.md","path":"docs/skills/marketing-skill/content-creator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/content-creator.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcontent-creator.md -->","frontmatter":{"title":"Content Creator → Redirected — Agent Skill for Marketing","description":"Deprecated redirect skill that routes legacy 'content creator' requests to the correct specialist. Use when a user invokes 'content creator', asks to. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":769,"sizeBytes":3369},{"name":"content-humanizer.md","path":"docs/skills/marketing-skill/content-humanizer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/content-humanizer.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcontent-humanizer.md -->","frontmatter":{"title":"Content Humanizer — Agent Skill for Marketing","description":"Makes AI-generated content sound genuinely human — not just cleaned up, but alive. Use when content feels robotic, uses too many AI clichés, lacks. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3499,"sizeBytes":15195},{"name":"content-production.md","path":"docs/skills/marketing-skill/content-production.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/content-production.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcontent-production.md -->","frontmatter":{"title":"Content Production — Agent Skill for Marketing","description":"Full content production pipeline — takes a topic from blank page to published-ready piece. Use when you need to execute content: write a blog post. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2738,"sizeBytes":11854},{"name":"content-strategy.md","path":"docs/skills/marketing-skill/content-strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/content-strategy.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcontent-strategy.md -->","isInternal":false,"tokens":1544,"sizeBytes":7258},{"name":"copy-editing.md","path":"docs/skills/marketing-skill/copy-editing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/copy-editing.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcopy-editing.md -->","frontmatter":{"title":"Copy Editing — Agent Skill for Marketing","description":"When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3925,"sizeBytes":17083},{"name":"copywriting.md","path":"docs/skills/marketing-skill/copywriting.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/copywriting.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fcopywriting.md -->","frontmatter":{"title":"Copywriting — Agent Skill for Marketing","description":"When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2476,"sizeBytes":10823},{"name":"email-sequence.md","path":"docs/skills/marketing-skill/email-sequence.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/email-sequence.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Femail-sequence.md -->","frontmatter":{"title":"Email Sequence Design — Agent Skill for Marketing","description":"When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1336,"sizeBytes":6192},{"name":"form-cro.md","path":"docs/skills/marketing-skill/form-cro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/form-cro.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fform-cro.md -->","frontmatter":{"title":"Form CRO — Agent Skill for Marketing","description":"When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2089,"sizeBytes":9593},{"name":"free-tool-strategy.md","path":"docs/skills/marketing-skill/free-tool-strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/free-tool-strategy.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Ffree-tool-strategy.md -->","frontmatter":{"title":"Free Tool Strategy — Agent Skill for Marketing","description":"When the user wants to build a free tool for marketing — lead generation, SEO value, or brand awareness. Use when they mention 'engineering as. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2927,"sizeBytes":12549},{"name":"index.md","path":"docs/skills/marketing-skill/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/index.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Findex.md -->","frontmatter":{"title":"Marketing Skills — Agent Skills & Codex Plugins","description":"50 marketing skills — marketing agent skill and Claude Code plugin for content, SEO, CRO, and growth. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":2164,"sizeBytes":9554},{"name":"launch-strategy.md","path":"docs/skills/marketing-skill/launch-strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/launch-strategy.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Flaunch-strategy.md -->","frontmatter":{"title":"Launch Strategy — Agent Skill for Marketing","description":"When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1286,"sizeBytes":6069},{"name":"local-seo-manager.md","path":"docs/skills/marketing-skill/local-seo-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/local-seo-manager.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Flocal-seo-manager.md -->","frontmatter":{"title":"Local SEO Manager — Agent Skill for Marketing","description":"Manage local SEO for service-area businesses — appliance repair, HVAC, plumbing, cleaning, and any business that serves customers at their location. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3238,"sizeBytes":13808},{"name":"marketing-context.md","path":"docs/skills/marketing-skill/marketing-context.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-context.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-context.md -->","frontmatter":{"title":"Marketing Context — Agent Skill for Marketing","description":"Create and maintain the marketing context document that all marketing skills read before starting. Use when the user mentions 'marketing context,'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1770,"sizeBytes":8005},{"name":"marketing-demand-acquisition.md","path":"docs/skills/marketing-skill/marketing-demand-acquisition.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-demand-acquisition.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-demand-acquisition.md -->","frontmatter":{"title":"Marketing Demand & Acquisition — Agent Skill for Marketing","description":"Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2664,"sizeBytes":10523},{"name":"marketing-ideas.md","path":"docs/skills/marketing-skill/marketing-ideas.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-ideas.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-ideas.md -->","frontmatter":{"title":"Marketing Ideas for SaaS — Agent Skill for Marketing","description":"When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1936,"sizeBytes":8326},{"name":"marketing-ops.md","path":"docs/skills/marketing-skill/marketing-ops.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-ops.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-ops.md -->","frontmatter":{"title":"Marketing Ops — Agent Skill for Marketing","description":"Central router for the marketing skill ecosystem. Use when unsure which marketing skill to use, when orchestrating a multi-skill campaign, or when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2896,"sizeBytes":11692},{"name":"marketing-psychology.md","path":"docs/skills/marketing-skill/marketing-psychology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-psychology.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-psychology.md -->","frontmatter":{"title":"Marketing Psychology — Agent Skill for Marketing","description":"When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1661,"sizeBytes":7239},{"name":"marketing-skill.md","path":"docs/skills/marketing-skill/marketing-skill.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-skill.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-skill.md -->","frontmatter":{"title":"Marketing Skills Division — Agent Skill for Marketing","description":"42 marketing agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more coding agents. 7 pods: content, SEO, CRO."},"isInternal":false,"tokens":1045,"sizeBytes":4255},{"name":"marketing-skills.md","path":"docs/skills/marketing-skill/marketing-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-skills.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-skills.md -->","frontmatter":{"title":"Marketing Skills — Directory + Router — Agent Skill for Marketing","description":"Directory and router for the marketing skills library. Use when you need to find the right marketing skill for a task, see what marketing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1453,"sizeBytes":5538},{"name":"marketing-strategy-pmm.md","path":"docs/skills/marketing-skill/marketing-strategy-pmm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/marketing-strategy-pmm.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fmarketing-strategy-pmm.md -->","frontmatter":{"title":"Marketing Strategy & PMM — Agent Skill for Marketing","description":"Product marketing skill for positioning, GTM strategy, competitive intelligence, and product launches. Use when the user asks about product. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3000,"sizeBytes":12383},{"name":"onboarding-cro.md","path":"docs/skills/marketing-skill/onboarding-cro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/onboarding-cro.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fonboarding-cro.md -->","frontmatter":{"title":"Onboarding CRO — Agent Skill for Marketing","description":"When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2044,"sizeBytes":9251},{"name":"page-cro.md","path":"docs/skills/marketing-skill/page-cro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/page-cro.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fpage-cro.md -->","frontmatter":{"title":"Page Conversion Rate Optimization (CRO) — Agent Skill for Marketing","description":"When the user wants to optimize, improve, or increase conversions on any marketing page — including homepage, landing pages, pricing pages, feature. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2140,"sizeBytes":9786},{"name":"paid-ads.md","path":"docs/skills/marketing-skill/paid-ads.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/paid-ads.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fpaid-ads.md -->","frontmatter":{"title":"Paid Ads — Agent Skill for Marketing","description":"When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3202,"sizeBytes":13738},{"name":"paywall-upgrade-cro.md","path":"docs/skills/marketing-skill/paywall-upgrade-cro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/paywall-upgrade-cro.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fpaywall-upgrade-cro.md -->","frontmatter":{"title":"Paywall and Upgrade Screen CRO — Agent Skill for Marketing","description":"When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1852,"sizeBytes":8088},{"name":"popup-cro.md","path":"docs/skills/marketing-skill/popup-cro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/popup-cro.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fpopup-cro.md -->","frontmatter":{"title":"Popup CRO — Agent Skill for Marketing","description":"When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1797,"sizeBytes":8043},{"name":"pricing-strategy.md","path":"docs/skills/marketing-skill/pricing-strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/pricing-strategy.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fpricing-strategy.md -->","frontmatter":{"title":"Pricing Strategy — Agent Skill for Marketing","description":"Design, optimize, and communicate SaaS pricing — tier structure, value metrics, pricing pages, and price increase strategy. Use when building a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3362,"sizeBytes":14627},{"name":"programmatic-seo.md","path":"docs/skills/marketing-skill/programmatic-seo.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/programmatic-seo.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fprogrammatic-seo.md -->","frontmatter":{"title":"Programmatic SEO — Agent Skill for Marketing","description":"When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions 'programmatic SEO,' 'template. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2461,"sizeBytes":10945},{"name":"prompt-engineer-toolkit.md","path":"docs/skills/marketing-skill/prompt-engineer-toolkit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/prompt-engineer-toolkit.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fprompt-engineer-toolkit.md -->","frontmatter":{"title":"Prompt Engineer Toolkit — Agent Skill for Marketing","description":"Turns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1378,"sizeBytes":6187},{"name":"referral-program.md","path":"docs/skills/marketing-skill/referral-program.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/referral-program.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Freferral-program.md -->","frontmatter":{"title":"Referral Program — Agent Skill for Marketing","description":"When the user wants to design, launch, or optimize a referral or affiliate program. Use when they mention 'referral program,' 'affiliate program,'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3176,"sizeBytes":14270},{"name":"schema-markup.md","path":"docs/skills/marketing-skill/schema-markup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/schema-markup.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fschema-markup.md -->","frontmatter":{"title":"Schema Markup Implementation — Agent Skill for Marketing","description":"When the user wants to implement, audit, or validate structured data (schema markup) on their website. Use when the user mentions 'structured data,'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2646,"sizeBytes":11778},{"name":"seo-audit.md","path":"docs/skills/marketing-skill/seo-audit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/seo-audit.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fseo-audit.md -->","frontmatter":{"title":"SEO Audit — Agent Skill for Marketing","description":"When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions 'SEO audit,' 'technical SEO,' 'why am I. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1949,"sizeBytes":8216},{"name":"signup-flow-cro.md","path":"docs/skills/marketing-skill/signup-flow-cro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/signup-flow-cro.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fsignup-flow-cro.md -->","frontmatter":{"title":"Signup Flow CRO — Agent Skill for Marketing","description":"When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions 'signup. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2206,"sizeBytes":9884},{"name":"site-architecture.md","path":"docs/skills/marketing-skill/site-architecture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/site-architecture.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fsite-architecture.md -->","frontmatter":{"title":"Site Architecture & Internal Linking — Agent Skill for Marketing","description":"When the user wants to audit, redesign, or plan their website's structure, URL hierarchy, navigation design, or internal linking strategy. Use when. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3177,"sizeBytes":14088},{"name":"social-content.md","path":"docs/skills/marketing-skill/social-content.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/social-content.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fsocial-content.md -->","frontmatter":{"title":"Social Content — Agent Skill for Marketing","description":"When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2689,"sizeBytes":11779},{"name":"social-media-analyzer.md","path":"docs/skills/marketing-skill/social-media-analyzer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/social-media-analyzer.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fsocial-media-analyzer.md -->","frontmatter":{"title":"Social Media Analyzer — Agent Skill for Marketing","description":"Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use when analyzing social. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2241,"sizeBytes":8719},{"name":"social-media-manager.md","path":"docs/skills/marketing-skill/social-media-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/social-media-manager.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fsocial-media-manager.md -->","frontmatter":{"title":"Social Media Manager — Agent Skill for Marketing","description":"When the user wants to develop social media strategy, plan content calendars, manage community engagement, or grow their social presence across. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2213,"sizeBytes":9780},{"name":"video-content-strategist.md","path":"docs/skills/marketing-skill/video-content-strategist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/video-content-strategist.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fvideo-content-strategist.md -->","frontmatter":{"title":"Video Content Strategist — Agent Skill for Marketing","description":"Use when planning video content strategy, writing video scripts, optimizing YouTube channels, building short-form video pipelines (Reels, TikTok. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2715,"sizeBytes":11751},{"name":"webinar-marketing.md","path":"docs/skills/marketing-skill/webinar-marketing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/webinar-marketing.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fwebinar-marketing.md -->","frontmatter":{"title":"Webinar & Virtual Event Marketing — Agent Skill for Marketing","description":"When the user wants to plan, promote, run, or improve a webinar or virtual event to generate and convert demand. Use when the user mentions. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2949,"sizeBytes":12837},{"name":"x-twitter-growth.md","path":"docs/skills/marketing-skill/x-twitter-growth.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/x-twitter-growth.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fx-twitter-growth.md -->","frontmatter":{"title":"X/Twitter Growth Engine — Agent Skill for Marketing","description":"X/Twitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X/Twitter, write. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2222,"sizeBytes":8852},{"name":"youtube-full.md","path":"docs/skills/marketing-skill/youtube-full.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing-skill/youtube-full.md","title":"Marketing-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing-skill%2Fyoutube-full.md -->","frontmatter":{"title":"youtube-full — YouTube Transcripts, Search, and Channel Data — Agent Skill for Marketing","description":"Use when the user needs YouTube transcripts, video search, channel browsing, playlist extraction, or content monitoring. Trigger phrases: 'get the. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1760,"sizeBytes":7376},{"name":"index.md","path":"docs/skills/marketing/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/index.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Findex.md -->","frontmatter":{"title":"Marketing (Top-Level) Skills — Agent Skills & Codex Plugins","description":"7 marketing (top-level) skills — landing-page generator agent skill and Claude Code plugin for single-file HTML output with 4 design styles. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":151,"sizeBytes":637},{"name":"landing.md","path":"docs/skills/marketing/landing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/landing.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flanding.md -->","frontmatter":{"title":"Landing — Premium HTML Landing Page Generator — Agent Skill for Landing Pages","description":"Generates a premium single-page HTML landing page with 3D CSS animations, GSAP scroll effects, and mouse-parallax depth. Forcing intake (product +."},"isInternal":false,"tokens":4159,"sizeBytes":15334},{"name":"linkedin-linkedin-analytics.md","path":"docs/skills/marketing/linkedin-linkedin-analytics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/linkedin-linkedin-analytics.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flinkedin-linkedin-analytics.md -->","frontmatter":{"title":"LinkedIn Analytics — describe honestly, then refuse to over-conclude — Agent Skill for Landing Pages","description":"Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1503,"sizeBytes":6272},{"name":"linkedin-linkedin-content.md","path":"docs/skills/marketing/linkedin-linkedin-content.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/linkedin-linkedin-content.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flinkedin-linkedin-content.md -->","frontmatter":{"title":"LinkedIn Content — format, draft, lint — Agent Skill for Landing Pages","description":"Use when someone wants to write, edit, or lint a LinkedIn post — a story, how-to, opinion piece, carousel script, video script, or poll — or wants an. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1577,"sizeBytes":6567},{"name":"linkedin-linkedin-engagement.md","path":"docs/skills/marketing/linkedin-linkedin-engagement.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/linkedin-linkedin-engagement.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flinkedin-linkedin-engagement.md -->","frontmatter":{"title":"LinkedIn Engagement — comments first, outreach second — Agent Skill for Landing Pages","description":"Use when someone wants to grow reach through comments, replies, groups, or outreach on LinkedIn — a commenting roster, a connection request note, a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1502,"sizeBytes":6283},{"name":"linkedin-linkedin-profile.md","path":"docs/skills/marketing/linkedin-linkedin-profile.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/linkedin-linkedin-profile.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flinkedin-linkedin-profile.md -->","frontmatter":{"title":"LinkedIn Profile — audit, then rewrite the parts that pay — Agent Skill for Landing Pages","description":"Use when someone wants their LinkedIn profile audited or rewritten — headline, About section, experience bullets, Featured, banner, recommendations . Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1443,"sizeBytes":6055},{"name":"linkedin-linkedin-skills.md","path":"docs/skills/marketing/linkedin-linkedin-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/linkedin-linkedin-skills.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flinkedin-linkedin-skills.md -->","frontmatter":{"title":"LinkedIn — Organic Presence Orchestrator — Agent Skill for Landing Pages","description":"Use when someone wants to grow an organic LinkedIn presence — a content strategy for a career change or consulting or thought leadership, a rewritten. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1429,"sizeBytes":5834},{"name":"linkedin-linkedin-strategy.md","path":"docs/skills/marketing/linkedin-linkedin-strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/marketing/linkedin-linkedin-strategy.md","title":"Marketing Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fmarketing%2Flinkedin-linkedin-strategy.md -->","frontmatter":{"title":"LinkedIn Strategy — brief, cadence, newsletter — Agent Skill for Landing Pages","description":"Use when someone needs a LinkedIn plan rather than a post — content pillars, positioning for a career change or consulting or thought leadership, a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1457,"sizeBytes":6082},{"name":"agile-product-owner.md","path":"docs/skills/product-team/agile-product-owner.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/agile-product-owner.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fagile-product-owner.md -->","frontmatter":{"title":"Agile Product Owner — Agent Skill for Product Teams","description":"Agile product ownership for backlog management and sprint execution. Covers user story writing, acceptance criteria, sprint planning, and velocity. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2999,"sizeBytes":12669},{"name":"apple-hig-expert.md","path":"docs/skills/product-team/apple-hig-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/apple-hig-expert.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fapple-hig-expert.md -->","frontmatter":{"title":"Apple HIG Expert — Agent Skill for Product Teams","description":"Audits and designs iOS/macOS/watchOS/visionOS interfaces against the Apple Human Interface Guidelines, including the Liquid Glass design language. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1446,"sizeBytes":5625},{"name":"code-to-prd.md","path":"docs/skills/product-team/code-to-prd.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/code-to-prd.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fcode-to-prd.md -->","frontmatter":{"title":"Code → PRD: Reverse-Engineer Any Codebase into Product Requirements — Agent Skill for Product Teams","description":"Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4547,"sizeBytes":19767},{"name":"competitive-teardown.md","path":"docs/skills/product-team/competitive-teardown.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/competitive-teardown.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fcompetitive-teardown.md -->","frontmatter":{"title":"Competitive Teardown — Agent Skill for Product Teams","description":"Analyzes competitor products and companies by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2031,"sizeBytes":8478},{"name":"experiment-designer.md","path":"docs/skills/product-team/experiment-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/experiment-designer.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fexperiment-designer.md -->","frontmatter":{"title":"Experiment Designer — Agent Skill for Product Teams","description":"Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":814,"sizeBytes":3708},{"name":"index.md","path":"docs/skills/product-team/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/index.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Findex.md -->","frontmatter":{"title":"Product Skills — Agent Skills & Codex Plugins","description":"17 product skills — product management agent skill and Claude Code plugin for PRDs, discovery, analytics, and roadmaps. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":595,"sizeBytes":2663},{"name":"landing-page-generator.md","path":"docs/skills/product-team/landing-page-generator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/landing-page-generator.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Flanding-page-generator.md -->","frontmatter":{"title":"Landing Page Generator — Agent Skill for Product Teams","description":"Generates high-converting landing pages as complete Next.js/React (TSX) components with Tailwind CSS. Creates hero sections, feature grids, pricing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2722,"sizeBytes":10745},{"name":"product-analytics.md","path":"docs/skills/product-team/product-analytics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/product-analytics.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fproduct-analytics.md -->","frontmatter":{"title":"Product Analytics — Agent Skill for Product Teams","description":"Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1386,"sizeBytes":6089},{"name":"product-discovery.md","path":"docs/skills/product-team/product-discovery.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/product-discovery.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fproduct-discovery.md -->","frontmatter":{"title":"Product Discovery — Agent Skill for Product Teams","description":"Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":824,"sizeBytes":3896},{"name":"product-manager-toolkit.md","path":"docs/skills/product-team/product-manager-toolkit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/product-manager-toolkit.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fproduct-manager-toolkit.md -->","frontmatter":{"title":"Product Manager Toolkit — Agent Skill for Product Teams","description":"Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2362,"sizeBytes":10554},{"name":"product-skills.md","path":"docs/skills/product-team/product-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/product-skills.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fproduct-skills.md -->","frontmatter":{"title":"Product Team — Domain Orchestrator & Discovery Loop — Agent Skill for Product Teams","description":"Use when coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2691,"sizeBytes":10750},{"name":"product-strategist.md","path":"docs/skills/product-team/product-strategist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/product-strategist.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fproduct-strategist.md -->","frontmatter":{"title":"Product Strategist — Agent Skill for Product Teams","description":"Strategic product leadership toolkit for Head of Product covering OKR cascade generation, quarterly planning, competitive landscape analysis, product. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1923,"sizeBytes":7585},{"name":"product-team.md","path":"docs/skills/product-team/product-team.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/product-team.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fproduct-team.md -->","frontmatter":{"title":"Product Team Skills — Agent Skill for Product Teams","description":"10 product agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. PM toolkit (RICE), agile PO, product strategist (OKR), UX."},"isInternal":false,"tokens":525,"sizeBytes":2124},{"name":"research-summarizer.md","path":"docs/skills/product-team/research-summarizer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/research-summarizer.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fresearch-summarizer.md -->","frontmatter":{"title":"Research Summarizer — Agent Skill for Product Teams","description":"Structured research summarization agent skill for non-dev users. Handles academic papers, web articles, reports, and documentation. Extracts key."},"isInternal":false,"tokens":2516,"sizeBytes":11069},{"name":"roadmap-communicator.md","path":"docs/skills/product-team/roadmap-communicator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/roadmap-communicator.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Froadmap-communicator.md -->","frontmatter":{"title":"Roadmap Communicator — Agent Skill for Product Teams","description":"Use when preparing roadmap narratives, release notes, changelogs, or stakeholder updates tailored for executives, engineering teams, and customers. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":691,"sizeBytes":3199},{"name":"saas-scaffolder.md","path":"docs/skills/product-team/saas-scaffolder.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/saas-scaffolder.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fsaas-scaffolder.md -->","frontmatter":{"title":"SaaS Scaffolder — Agent Skill for Product Teams","description":"Generates complete, production-ready SaaS project boilerplate including authentication, database schemas, billing integration, API routes, and a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2745,"sizeBytes":11070},{"name":"spec-to-repo.md","path":"docs/skills/product-team/spec-to-repo.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/spec-to-repo.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fspec-to-repo.md -->","frontmatter":{"title":"Spec to Repo — Agent Skill for Product Teams","description":"Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code'. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2805,"sizeBytes":11653},{"name":"ui-design-system.md","path":"docs/skills/product-team/ui-design-system.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/ui-design-system.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fui-design-system.md -->","frontmatter":{"title":"UI Design System — Agent Skill for Product Teams","description":"UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3007,"sizeBytes":11208},{"name":"ux-researcher-designer.md","path":"docs/skills/product-team/ux-researcher-designer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/product-team/ux-researcher-designer.md","title":"Product-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproduct-team%2Fux-researcher-designer.md -->","frontmatter":{"title":"UX Researcher & Designer — Agent Skill for Product Teams","description":"UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2999,"sizeBytes":12459},{"name":"andreessen.md","path":"docs/skills/productivity/andreessen.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/andreessen.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fandreessen.md -->","frontmatter":{"title":"Andreessen — Market-First Decision & Productivity Mode — Agent Skill for Personal Productivity","description":"Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3178,"sizeBytes":12820},{"name":"capture.md","path":"docs/skills/productivity/capture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/capture.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fcapture.md -->","frontmatter":{"title":"Capture — Brain-Dump Organizer — Agent Skill for Personal Productivity","description":"Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2475,"sizeBytes":10805},{"name":"deep-work.md","path":"docs/skills/productivity/deep-work.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/deep-work.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fdeep-work.md -->","frontmatter":{"title":"Deep Work — Time-Block the Day, Budget the Shallow — Agent Skill for Personal Productivity","description":"Use when someone wants to plan a deep work day, time-block their calendar or task list, budget or cut shallow work, protect focus hours, track. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1593,"sizeBytes":6508},{"name":"email-inbox-setup.md","path":"docs/skills/productivity/email-inbox-setup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/email-inbox-setup.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Femail-inbox-setup.md -->","frontmatter":{"title":"Inbox-Setup — Email Triage Onboarding — Agent Skill for Personal Productivity","description":"One-time setup skill that builds a personalized inbox triage knowledge base via interactive interview. Interviews the user about their email. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3734,"sizeBytes":15738},{"name":"email-inbox-triage.md","path":"docs/skills/productivity/email-inbox-triage.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/email-inbox-triage.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Femail-inbox-triage.md -->","frontmatter":{"title":"Inbox-Triage — Recurring Email Triage — Agent Skill for Personal Productivity","description":"Runs a full inbox triage using the knowledge base created by the 'inbox-setup' skill. Light-intake by design (most invocations skip questions and run. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3515,"sizeBytes":14625},{"name":"fable-goal.md","path":"docs/skills/productivity/fable-goal.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/fable-goal.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Ffable-goal.md -->","frontmatter":{"title":"Fable Goal Prompt Writer — Agent Skill for Personal Productivity","description":"Convert a rambling description of a desired outcome into one polished, autonomous /goal prompt ready to paste into a fresh session. Use when the user. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2262,"sizeBytes":9971},{"name":"handoff.md","path":"docs/skills/productivity/handoff.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/handoff.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fhandoff.md -->","frontmatter":{"title":"Handoff — Agent Skill for Personal Productivity","description":"Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2408,"sizeBytes":10168},{"name":"index.md","path":"docs/skills/productivity/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/index.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Findex.md -->","frontmatter":{"title":"Productivity Skills — Agent Skills & Codex Plugins","description":"12 productivity skills — personal productivity agent skill and Claude Code plugin for brain-dump capture, email triage, and reflection. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":186,"sizeBytes":825},{"name":"meetings.md","path":"docs/skills/productivity/meetings.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/meetings.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fmeetings.md -->","frontmatter":{"title":"Meetings — Cost Gate → Timeboxed Agenda → Owned Actions — Agent Skill for Personal Productivity","description":"Use when someone wants to decide whether a meeting is worth calling, price a meeting in dollars, build a timeboxed agenda with desired outcomes, or. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1551,"sizeBytes":6340},{"name":"reflect.md","path":"docs/skills/productivity/reflect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/reflect.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Freflect.md -->","frontmatter":{"title":"Reflect — Mid-Conversation Reassessment — Agent Skill for Personal Productivity","description":"Mid-conversation reflection skill that pauses execution and zooms out from detail-mode to honestly reassess direction, assumptions, and bias. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2268,"sizeBytes":10086},{"name":"roast.md","path":"docs/skills/productivity/roast.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/roast.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Froast.md -->","frontmatter":{"title":"Roast — 5-Angle Idea Panel → One Verdict — Agent Skill for Personal Productivity","description":"Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, 'convene the panel', get a brutal second. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2724,"sizeBytes":11027},{"name":"swedish-mentor.md","path":"docs/skills/productivity/swedish-mentor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/swedish-mentor.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fswedish-mentor.md -->","frontmatter":{"title":"Swedish YouTube & Podcast Mentor — Agent Skill for Personal Productivity","description":"Mentor Swedish language learners by selecting YouTube video clips and podcast episodes by CEFR level and skill (listening, reading, writing. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2627,"sizeBytes":11729},{"name":"weekly-review.md","path":"docs/skills/productivity/weekly-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/productivity/weekly-review.md","title":"Productivity Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproductivity%2Fweekly-review.md -->","frontmatter":{"title":"Weekly Review — GTD Loop → Trusted System — Agent Skill for Personal Productivity","description":"Use when someone wants to run a weekly review, close open loops, audit stalled projects and commitments, get their system back to trusted, restart a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1509,"sizeBytes":6283},{"name":"atlassian-admin.md","path":"docs/skills/project-management/atlassian-admin.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/atlassian-admin.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fatlassian-admin.md -->","frontmatter":{"title":"Atlassian Administrator Expert — Agent Skill for PM","description":"Atlassian Administrator for managing and organizing Atlassian products (Jira, Confluence, Bitbucket, Trello), users, permissions, security. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3017,"sizeBytes":13273},{"name":"atlassian-templates.md","path":"docs/skills/project-management/atlassian-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/atlassian-templates.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fatlassian-templates.md -->","frontmatter":{"title":"Atlassian Template & Files Creator Expert — Agent Skill for PM","description":"Atlassian Template and Files Creator/Modifier expert for creating, modifying, and managing Jira and Confluence templates, blueprints, custom layouts. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2924,"sizeBytes":12911},{"name":"confluence-expert.md","path":"docs/skills/project-management/confluence-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/confluence-expert.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fconfluence-expert.md -->","frontmatter":{"title":"Atlassian Confluence Expert — Agent Skill for PM","description":"Atlassian Confluence expert for creating and managing spaces, knowledge bases, and documentation. Configures space permissions and hierarchies. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3042,"sizeBytes":12675},{"name":"index.md","path":"docs/skills/project-management/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/index.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Findex.md -->","frontmatter":{"title":"Project Management Skills — Agent Skills & Codex Plugins","description":"9 project management skills — project management agent skill and Claude Code plugin for sprints, Jira, and Confluence. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":520,"sizeBytes":2296},{"name":"jira-expert.md","path":"docs/skills/project-management/jira-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/jira-expert.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fjira-expert.md -->","frontmatter":{"title":"Atlassian Jira Expert — Agent Skill for PM","description":"Atlassian Jira expert for creating and managing projects, planning, product discovery, JQL queries, workflows, custom fields, automation, reporting. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3180,"sizeBytes":13078},{"name":"meeting-analyzer.md","path":"docs/skills/project-management/meeting-analyzer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/meeting-analyzer.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fmeeting-analyzer.md -->","frontmatter":{"title":"Meeting Insights Analyzer — Agent Skill for PM","description":"Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2751,"sizeBytes":12348},{"name":"pm-skills.md","path":"docs/skills/project-management/pm-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/pm-skills.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fpm-skills.md -->","frontmatter":{"title":"Project Management — Domain Orchestrator & Delivery Loop — Agent Skill for PM","description":"Use when coordinating project-delivery work across the 8 project-management sub-skills — sprint/velocity analytics, portfolio health, Jira/JQL. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2562,"sizeBytes":10401},{"name":"project-management.md","path":"docs/skills/project-management/project-management.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/project-management.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fproject-management.md -->","frontmatter":{"title":"Project Management Skills — Agent Skill for PM","description":"6 project management agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Senior PM, scrum master, Jira expert (JQL)."},"isInternal":false,"tokens":473,"sizeBytes":1918},{"name":"scrum-master.md","path":"docs/skills/project-management/scrum-master.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/scrum-master.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fscrum-master.md -->","frontmatter":{"title":"Scrum Master Expert — Agent Skill for PM","description":"Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2085,"sizeBytes":9480},{"name":"senior-pm.md","path":"docs/skills/project-management/senior-pm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/senior-pm.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fsenior-pm.md -->","frontmatter":{"title":"Senior Project Management Expert — Agent Skill for PM","description":"Senior Project Manager for enterprise software, SaaS, and digital transformation projects. Specializes in portfolio management, quantitative risk. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3413,"sizeBytes":16610},{"name":"team-communications.md","path":"docs/skills/project-management/team-communications.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/project-management/team-communications.md","title":"Project-management Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fproject-management%2Fteam-communications.md -->","frontmatter":{"title":"Internal Comms — Agent Skill for PM","description":"Write internal company communications — 3P updates (Progress/Plans/Problems), company-wide newsletters, FAQ roundups, incident reports, leadership. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1012,"sizeBytes":4505},{"name":"agent-decision-receipts.md","path":"docs/skills/ra-qm-team/agent-decision-receipts.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/agent-decision-receipts.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fagent-decision-receipts.md -->","frontmatter":{"title":"Agent Decision Receipts — Agent Skill for Compliance","description":"Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2040,"sizeBytes":8248},{"name":"capa-officer.md","path":"docs/skills/ra-qm-team/capa-officer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/capa-officer.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fcapa-officer.md -->","frontmatter":{"title":"CAPA Officer — Agent Skill for Compliance","description":"CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3663,"sizeBytes":16218},{"name":"compliance-team-eu-ai-act-eu-ai-act-specialist.md","path":"docs/skills/ra-qm-team/compliance-team-eu-ai-act-eu-ai-act-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/compliance-team-eu-ai-act-eu-ai-act-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fcompliance-team-eu-ai-act-eu-ai-act-specialist.md -->","frontmatter":{"title":"EU AI Act Compliance Specialist — Agent Skill for Compliance","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3662,"sizeBytes":15298},{"name":"compliance-team-iso42001-iso42001-specialist.md","path":"docs/skills/ra-qm-team/compliance-team-iso42001-iso42001-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/compliance-team-iso42001-iso42001-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fcompliance-team-iso42001-iso42001-specialist.md -->","frontmatter":{"title":"ISO/IEC 42001 AI Management System Specialist — Agent Skill for Compliance","description":"ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3577,"sizeBytes":14273},{"name":"eu-ai-act-specialist.md","path":"docs/skills/ra-qm-team/eu-ai-act-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/eu-ai-act-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Feu-ai-act-specialist.md -->","frontmatter":{"title":"EU AI Act Compliance Specialist — Agent Skill for Compliance","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3617,"sizeBytes":15168},{"name":"fda-consultant-specialist.md","path":"docs/skills/ra-qm-team/fda-consultant-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/fda-consultant-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Ffda-consultant-specialist.md -->","frontmatter":{"title":"FDA Consultant Specialist — Agent Skill for Compliance","description":"FDA regulatory consultant for medical device companies. Provides 510(k)/PMA/De Novo pathway guidance, QMSR (21 CFR 820, which incorporates ISO. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3139,"sizeBytes":12844},{"name":"gdpr-dsgvo-expert.md","path":"docs/skills/ra-qm-team/gdpr-dsgvo-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/gdpr-dsgvo-expert.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fgdpr-dsgvo-expert.md -->","frontmatter":{"title":"GDPR/DSGVO Expert — Agent Skill for Compliance","description":"GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2070,"sizeBytes":8767},{"name":"index.md","path":"docs/skills/ra-qm-team/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/index.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Findex.md -->","frontmatter":{"title":"Regulatory & Quality Skills — Agent Skills & Codex Plugins","description":"19 regulatory & quality skills — regulatory and quality management agent skill for ISO 13485, MDR, FDA, and GDPR compliance. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":922,"sizeBytes":3935},{"name":"information-security-manager-iso27001.md","path":"docs/skills/ra-qm-team/information-security-manager-iso27001.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/information-security-manager-iso27001.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Finformation-security-manager-iso27001.md -->","frontmatter":{"title":"Information Security Manager - ISO 27001 — Agent Skill for Compliance","description":"ISO 27001 ISMS implementation and cybersecurity governance for HealthTech and MedTech companies. Use when designing an ISMS, running security risk. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2747,"sizeBytes":12107},{"name":"isms-audit-expert.md","path":"docs/skills/ra-qm-team/isms-audit-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/isms-audit-expert.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fisms-audit-expert.md -->","frontmatter":{"title":"ISMS Audit Expert — Agent Skill for Compliance","description":"Information Security Management System (ISMS) audit expert for ISO 27001 compliance verification, security control assessment, and certification. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1740,"sizeBytes":7982},{"name":"iso42001-specialist.md","path":"docs/skills/ra-qm-team/iso42001-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/iso42001-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fiso42001-specialist.md -->","frontmatter":{"title":"ISO/IEC 42001 AI Management System Specialist — Agent Skill for Compliance","description":"ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3542,"sizeBytes":14148},{"name":"mdr-745-specialist.md","path":"docs/skills/ra-qm-team/mdr-745-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/mdr-745-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fmdr-745-specialist.md -->","frontmatter":{"title":"MDR 2017/745 Specialist — Agent Skill for Compliance","description":"EU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2449,"sizeBytes":10433},{"name":"qms-audit-expert.md","path":"docs/skills/ra-qm-team/qms-audit-expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/qms-audit-expert.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fqms-audit-expert.md -->","frontmatter":{"title":"QMS Audit Expert — Agent Skill for Compliance","description":"ISO 13485 internal audit expertise for medical device QMS. Covers audit planning, execution, nonconformity classification, and CAPA verification. Use. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2238,"sizeBytes":9951},{"name":"quality-documentation-manager.md","path":"docs/skills/ra-qm-team/quality-documentation-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/quality-documentation-manager.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fquality-documentation-manager.md -->","frontmatter":{"title":"Quality Documentation Manager — Agent Skill for Compliance","description":"Document control system management for medical device QMS. Covers document numbering, version control, change management, and 21 CFR Part 11. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3471,"sizeBytes":15759},{"name":"quality-manager-qmr.md","path":"docs/skills/ra-qm-team/quality-manager-qmr.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/quality-manager-qmr.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fquality-manager-qmr.md -->","frontmatter":{"title":"Senior Quality Manager Responsible Person (QMR) — Agent Skill for Compliance","description":"Senior Quality Manager Responsible Person (QMR) for HealthTech and MedTech companies. Provides quality system governance, management review. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4310,"sizeBytes":19530},{"name":"quality-manager-qms-iso13485.md","path":"docs/skills/ra-qm-team/quality-manager-qms-iso13485.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/quality-manager-qms-iso13485.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fquality-manager-qms-iso13485.md -->","frontmatter":{"title":"Quality Manager - QMS ISO 13485 Specialist — Agent Skill for Compliance","description":"ISO 13485 Quality Management System implementation and maintenance for medical device organizations. Provides QMS design, documentation control. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4447,"sizeBytes":18841},{"name":"ra-qm-skills.md","path":"docs/skills/ra-qm-team/ra-qm-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/ra-qm-skills.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fra-qm-skills.md -->","frontmatter":{"title":"Regulatory Affairs & Quality Management Skills — Router — Agent Skill for Compliance","description":"Router/index for the 15 regulatory & quality-management skills bundled in this plugin (ISO 13485 QMS, EU MDR 2017/745, FDA submissions under QMSR. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":925,"sizeBytes":3474},{"name":"ra-qm-team.md","path":"docs/skills/ra-qm-team/ra-qm-team.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/ra-qm-team.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fra-qm-team.md -->","frontmatter":{"title":"Regulatory Affairs & Quality Management Skills — Agent Skill for Compliance","description":"12 regulatory & QM agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO."},"isInternal":false,"tokens":663,"sizeBytes":2483},{"name":"regulatory-affairs-head.md","path":"docs/skills/ra-qm-team/regulatory-affairs-head.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/regulatory-affairs-head.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fregulatory-affairs-head.md -->","frontmatter":{"title":"Head of Regulatory Affairs — Agent Skill for Compliance","description":"Senior Regulatory Affairs Manager for HealthTech and MedTech companies. Prepares FDA 510(k), De Novo, and PMA submission packages; analyzes. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":5015,"sizeBytes":21041},{"name":"risk-management-specialist.md","path":"docs/skills/ra-qm-team/risk-management-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/risk-management-specialist.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Frisk-management-specialist.md -->","frontmatter":{"title":"Risk Management Specialist — Agent Skill for Compliance","description":"Medical device risk management specialist implementing ISO 14971 throughout product lifecycle. Provides risk analysis, risk evaluation, risk control. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3977,"sizeBytes":17908},{"name":"soc2-compliance.md","path":"docs/skills/ra-qm-team/soc2-compliance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/ra-qm-team/soc2-compliance.md","title":"Ra-qm-team Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fra-qm-team%2Fsoc2-compliance.md -->","frontmatter":{"title":"SOC 2 Compliance — Agent Skill for Compliance","description":"Use when the user asks to prepare for SOC 2 audits, map Trust Service Criteria, build control matrices, collect audit evidence, perform gap analysis. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4298,"sizeBytes":19951},{"name":"clinical-research.md","path":"docs/skills/research-ops/clinical-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/clinical-research.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Fclinical-research.md -->","frontmatter":{"title":"clinical-research — Claude Code Plugin & Agent Skill","description":"Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2565,"sizeBytes":10811},{"name":"index.md","path":"docs/skills/research-ops/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/index.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Findex.md -->","frontmatter":{"title":"Research Operations Skills — Agent Skills & Codex Plugins","description":"6 research operations skills — enterprise research operations agent skill and Claude Code plugin for clinical study design, R&D finance, market sizing, and product research. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":397,"sizeBytes":1779},{"name":"interview-mapper.md","path":"docs/skills/research-ops/interview-mapper.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/interview-mapper.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Finterview-mapper.md -->","frontmatter":{"title":"Interview Mapper — Claude Code Plugin & Agent Skill","description":"Maps a single interview transcript into a verbatim-grounded, lens-coded structure and checks whether analytic conclusions hold across independent. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2044,"sizeBytes":8458},{"name":"market-research.md","path":"docs/skills/research-ops/market-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/market-research.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Fmarket-research.md -->","frontmatter":{"title":"market-research — Claude Code Plugin & Agent Skill","description":"Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2368,"sizeBytes":10104},{"name":"product-research.md","path":"docs/skills/research-ops/product-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/product-research.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Fproduct-research.md -->","frontmatter":{"title":"product-research — Claude Code Plugin & Agent Skill","description":"Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2528,"sizeBytes":11039},{"name":"research-finance.md","path":"docs/skills/research-ops/research-finance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/research-finance.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Fresearch-finance.md -->","frontmatter":{"title":"research-finance — Claude Code Plugin & Agent Skill","description":"Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2536,"sizeBytes":10556},{"name":"research-ops-skills.md","path":"docs/skills/research-ops/research-ops-skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research-ops/research-ops-skills.md","title":"Research-ops Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch-ops%2Fresearch-ops-skills.md -->","frontmatter":{"title":"Research Operations — Domain Orchestrator — Claude Code Plugin & Agent Skill","description":"Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":2620,"sizeBytes":10902},{"name":"deep-research.md","path":"docs/skills/research/deep-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/deep-research.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fdeep-research.md -->","frontmatter":{"title":"Deep Research — Disciplined Meta-Research — Agent Skill for Research Workflows","description":"Run a disciplined, multi-source research investigation for a high-stakes question or decision — fan-out web search across many channels, parallel. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1783,"sizeBytes":7905},{"name":"deepread.md","path":"docs/skills/research/deepread.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/deepread.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fdeepread.md -->","frontmatter":{"title":"DeepRead — Agent Skill for Research Workflows","description":"Use when the user asks to deeply read a book, article, PDF, or document set; extract claims and evidence; build a knowledge map; or learn through. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":1857,"sizeBytes":8672},{"name":"dossier.md","path":"docs/skills/research/dossier.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/dossier.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fdossier.md -->","frontmatter":{"title":"Dossier — Decision-Grade Entity Research — Agent Skill for Research Workflows","description":"Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4019,"sizeBytes":16944},{"name":"grants.md","path":"docs/skills/research/grants.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/grants.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fgrants.md -->","frontmatter":{"title":"Grants — NIH Funding Intelligence — Agent Skill for Research Workflows","description":"NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3779,"sizeBytes":14904},{"name":"index.md","path":"docs/skills/research/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/index.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Findex.md -->","frontmatter":{"title":"Research Skills — Agent Skills & Codex Plugins","description":"10 research skills — research orchestrator agent skill and Claude Code plugin for hybrid routing across pulse, litreview, grants, dossier, patent, syllabus, and notebooklm specialists. Works with Claude Code, Codex CLI, Gemini CLI, and OpenClaw."},"isInternal":false,"tokens":193,"sizeBytes":817},{"name":"litreview.md","path":"docs/skills/research/litreview.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/litreview.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Flitreview.md -->","frontmatter":{"title":"Litreview — Academic Literature Orientation — Agent Skill for Research Workflows","description":"Searches academic literature through free, keyless PubMed and OpenAlex APIs, optionally augments results with Consensus MCP when connected, builds a. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":4535,"sizeBytes":18638},{"name":"notebooklm.md","path":"docs/skills/research/notebooklm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/notebooklm.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fnotebooklm.md -->","frontmatter":{"title":"NotebookLM — Browser Automation — Agent Skill for Research Workflows","description":"Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."},"isInternal":false,"tokens":3941,"sizeBytes":16737},{"name":"patent.md","path":"docs/skills/research/patent.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/skills/research/patent.md","title":"Research Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fskills%2Fresearch%2Fpatent.md -->","frontmatter":{"title":"Patent — Prior-Art + Landscape Intelligence — Agent Skill for Research Workflows","description":"Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search. 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-->","isInternal":false,"tokens":1272,"sizeBytes":4964},{"name":"basic-search.md","path":"engineering-team/playwright-pro/skills/pw/templates/search/basic-search.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/search/basic-search.md","title":"Search Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Fpw%2Ftemplates%2Fsearch%2Fbasic-search.md -->","isInternal":false,"tokens":1121,"sizeBytes":4530},{"name":"empty-state.md","path":"engineering-team/playwright-pro/skills/pw/templates/search/empty-state.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/search/empty-state.md","title":"Search Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available 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-->","isInternal":false,"tokens":1244,"sizeBytes":5173},{"name":"pagination.md","path":"engineering-team/playwright-pro/skills/pw/templates/search/pagination.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/search/pagination.md","title":"Search Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Fpw%2Ftemplates%2Fsearch%2Fpagination.md -->","isInternal":false,"tokens":1135,"sizeBytes":4544},{"name":"sorting.md","path":"engineering-team/playwright-pro/skills/pw/templates/search/sorting.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/search/sorting.md","title":"Search Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Fpw%2Ftemplates%2Fsearch%2Fsorting.md -->","isInternal":false,"tokens":1291,"sizeBytes":5259},{"name":"account-delete.md","path":"engineering-team/playwright-pro/skills/pw/templates/settings/account-delete.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/settings/account-delete.md","title":"Settings Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Fpw%2Ftemplates%2Fsettings%2Faccount-delete.md -->","isInternal":false,"tokens":1363,"sizeBytes":5882},{"name":"notification-prefs.md","path":"engineering-team/playwright-pro/skills/pw/templates/settings/notification-prefs.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/settings/notification-prefs.md","title":"Settings Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Fpw%2Ftemplates%2Fsettings%2Fnotification-prefs.md -->","isInternal":false,"tokens":1203,"sizeBytes":5321},{"name":"password-change.md","path":"engineering-team/playwright-pro/skills/pw/templates/settings/password-change.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/pw/templates/settings/password-change.md","title":"Settings 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-->","isInternal":false,"tokens":1291,"sizeBytes":5342},{"name":"SKILL.md","path":"engineering-team/playwright-pro/skills/report/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/report/SKILL.md","title":"report","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Freport%2FSKILL.md -->","frontmatter":{"name":"report","description":"Generate test report. Use when user says \"test report\", \"results summary\", \"test status\", \"show results\", \"test dashboard\", or \"how did tests go\"."},"isInternal":false,"tokens":787,"sizeBytes":2931},{"name":"SKILL.md","path":"engineering-team/playwright-pro/skills/testrail/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/skills/testrail/SKILL.md","title":"testrail","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2Fskills%2Ftestrail%2FSKILL.md -->","frontmatter":{"name":"testrail","description":"Sync tests with TestRail. 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-->","frontmatter":{"name":"code-reviewer","description":"Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. 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Use when the user mentions embedded, IoT, microcontroller, ESP32, STM32, Arduino, Raspberry Pi Pico, firmware, PCB, KiCad, EasyEDA, PlatformIO, MQTT, Home Assistant, ESPHome, Grafana, an IoT dashboard, seeing sensor data on a phone, or asks for hardware tool recommendations, project planning, or cost/time estimates for an electronics project."},"isInternal":false,"tokens":2426,"sizeBytes":10447},{"name":"SKILL.md","path":"engineering-team/skills/engineering-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/engineering-skills/SKILL.md","title":"engineering-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fengineering-skills%2FSKILL.md -->","frontmatter":{"name":"engineering-skills","description":"Index of the engineering-team skills bundle for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. 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Use when browsing or choosing among engineering-team role skills — load only the one specialist SKILL.md you need, never bulk-load the bundle.","license":"MIT","metadata":{"version":"2.9.0","author":"Alireza Rezvani","tags":["engineering","frontend","backend","devops","security","ai-ml","data-engineering"],"agents":["claude-code","codex-cli","openclaw"]}},"isInternal":false,"tokens":909,"sizeBytes":3589},{"name":"accessibility.md","path":"engineering-team/skills/epic-design/references/accessibility.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/epic-design/references/accessibility.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fepic-design%2Freferences%2Faccessibility.md 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/api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fepic-design%2Freferences%2Fperformance.md -->","isInternal":false,"tokens":1733,"sizeBytes":7332},{"name":"text-animations.md","path":"engineering-team/skills/epic-design/references/text-animations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/epic-design/references/text-animations.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fepic-design%2Freferences%2Ftext-animations.md 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Use when asked to design Google Cloud infrastructure, deploy to GKE or Cloud Run, configure BigQuery pipelines, optimize GCP costs, or migrate to GCP. 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Team size 1-20, customer-facing or ML-adjacent SaaS, type-safe Python ecosystem. Strong async story, fastest path when ML/data team already in Python.","version":"1.0.0","constraints":{"team_size_min":1,"team_size_max":20,"tenancy":"shared-multi-tenant","data_sensitivity_tier_max":"pii","pattern":"modular-monolith-or-domain-bounded"},"stack":{"runtime":"python-3.11-or-3.12","framework":"fastapi-0.110+","orm":"sqlalchemy-2-async-mode","migrations":"alembic","database":"postgresql-16+","cache":"redis-only-if-justified","queue_options":["arq-on-redis","celery-only-if-team-knows-it","pg-tasks-for-simple-cases"],"auth_options":["fastapi-users","authlib","clerk-paid"],"validation":"pydantic-v2","testing":"pytest + pytest-asyncio + httpx-async-test-client + testcontainers","tracing":"opentelemetry-with-honeycomb-or-tempo","background_jobs":"arq-or-pg-boss-equivalent","package_manager":"uv-or-poetry"},"anti_recommendations":{"flask-for-new-projects":"kill — FastAPI is the modern default; Flask has no async story","django-rest-framework-for-greenfield":"warn — DRF is fine for full-Django shops; FastAPI wins for API-first","sync-only-database-driver":"kill — async path matters for FastAPI throughput","no-pydantic-validation":"kill — every request body validated","celery-without-experience":"kill — operational complexity not worth it under 200 QPS background load","microservices":"kill at this team size — modular monolith"},"success_thresholds":{"p50_api_latency_ms":60,"p95_api_latency_ms":200,"p99_api_latency_ms":500,"uptime_target":0.995,"test_coverage_min":0.75,"security_scan_severity_max":"medium","rpo_minutes_max":60,"rto_minutes_max":240},"named_approver_chain":{"schema_change_production":"tech-lead + on-call","new-external-service":"tech-lead + cfo","auth-or-authz-change":"tech-lead + security-owner"},"canon_references":["Sebastián Ramírez, FastAPI docs (2018-2024)","SQLAlchemy 2.0 docs — async migration path","Tiangolo's Pydantic v2 migration notes (2023)","Martin Kleppmann, DDIA (2017)","OWASP API Security Top 10 (2023)"]},"isInternal":false,"tokens":737,"sizeBytes":2515},{"name":"go-or-rust-microservice.json","path":"engineering-team/skills/senior-backend/profiles/go-or-rust-microservice.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-backend/profiles/go-or-rust-microservice.json","title":"Profiles Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-backend%2Fprofiles%2Fgo-or-rust-microservice.json -->","frontmatter":{"$schema":"https://json-schema.org/draft-07/schema#","profile_name":"go-or-rust-microservice","description":"Single high-throughput service in Go (Gin/Echo/Chi) or Rust (Axum/Actix). Extracted from a modular monolith because (a) team owns it, (b) bounded context is provably-independent, (c) throughput / latency target requires it. NOT a default — earn your way in.","version":"1.0.0","constraints":{"team_size_min":30,"tenancy":"shared-multi-tenant-or-isolated","data_sensitivity_tier_max":"phi","pattern":"extracted-service-not-greenfield-microservices","qps_p99_min":1000,"platform_team_exists":true},"stack_go":{"runtime":"go-1.22+","framework_options":["chi","gin","echo","stdlib-net-http"],"orm_options":["sqlc-preferred","pgx-direct"],"database":"postgresql-or-spanner-or-cockroachdb","cache":"redis-or-internal-cache-tier","tracing":"opentelemetry-go-sdk","testing":"stdlib-testing + testify + testcontainers"},"stack_rust":{"runtime":"rust-stable-1.78+","framework_options":["axum","actix-web"],"orm_options":["sqlx-preferred","diesel-only-if-team-knows-it"],"database":"postgresql-or-spanner-or-cockroachdb","tracing":"opentelemetry-rust-sdk","testing":"cargo-test + insta-snapshots"},"anti_recommendations":{"rewrite-from-monolith-without-bounded-context":"kill — extract a service only when the second team needs to own it","rust-because-its-safer":"warn — Rust learning curve is 6-12 months; do not pick without an on-team senior","go-without-context-everywhere":"kill — context.Context on every handler + DB call mandatory","no-circuit-breakers":"kill — extracted services need hystrix/gobreaker or equivalent","no-bulkhead-isolation":"kill — connection pool isolation per dependency","shared-database-across-services":"kill — defeats the point of the extraction"},"success_thresholds":{"p50_api_latency_ms":20,"p95_api_latency_ms":80,"p99_api_latency_ms":200,"uptime_target":0.999,"test_coverage_min":0.8,"security_scan_severity_max":"low","rpo_minutes_max":5,"rto_minutes_max":30,"throughput_rps_min":1000},"named_approver_chain":{"service_extraction_decision":"principal-engineer + platform-team-lead + product-owner","schema_change_production":"service-owner + DBA + on-call + change-advisory-board","new-external-service":"principal-engineer + security-review + finance"},"canon_references":["Sam Newman, Building Microservices 2e (2021), ch. 3 'Splitting the Monolith'","Susan Fowler, Production-Ready Microservices (2017) — eight pillars","Niall Murphy + Betsy Beyer, SRE (2016) — circuit breakers + bulkheads","Tigran Bregadze, Production Rust at scale (talks, 2023-2024)","Pat Helland, Life beyond Distributed Transactions (2007)"]},"isInternal":false,"tokens":847,"sizeBytes":2995},{"name":"node-express.json","path":"engineering-team/skills/senior-backend/profiles/node-express.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-backend/profiles/node-express.json","title":"Profiles Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-backend%2Fprofiles%2Fnode-express.json -->","frontmatter":{"$schema":"https://json-schema.org/draft-07/schema#","profile_name":"node-express","description":"Node.js + Express (or Fastify) + Postgres. 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Use when the user asks to \"design REST APIs\", \"optimize database queries\", \"implement authentication\", \"build microservices\", \"review backend code\", \"set up GraphQL\", \"handle database migrations\", or \"load test APIs\". 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Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. 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Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues."},"isInternal":false,"tokens":1348,"sizeBytes":5802},{"name":"experiment_design_frameworks.md","path":"engineering-team/skills/senior-data-scientist/references/experiment_design_frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-data-scientist/references/experiment_design_frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-data-scientist%2Freferences%2Fexperiment_design_frameworks.md -->","isInternal":false,"tokens":297,"sizeBytes":1435},{"name":"feature_engineering_patterns.md","path":"engineering-team/skills/senior-data-scientist/references/feature_engineering_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-data-scientist/references/feature_engineering_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-data-scientist%2Freferences%2Ffeature_engineering_patterns.md -->","isInternal":false,"tokens":296,"sizeBytes":1435},{"name":"statistical_methods_advanced.md","path":"engineering-team/skills/senior-data-scientist/references/statistical_methods_advanced.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-data-scientist/references/statistical_methods_advanced.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-data-scientist%2Freferences%2Fstatistical_methods_advanced.md -->","isInternal":false,"tokens":296,"sizeBytes":1435},{"name":"SKILL.md","path":"engineering-team/skills/senior-data-scientist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-data-scientist/SKILL.md","title":"senior-data-scientist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-data-scientist%2FSKILL.md -->","frontmatter":{"name":"senior-data-scientist","description":"World-class senior data scientist skill specialising in statistical modeling, experiment design, causal inference, and predictive analytics. Covers A/B testing (sample sizing, two-proportion z-tests, Bonferroni correction), difference-in-differences, feature engineering pipelines (Scikit-learn, XGBoost), cross-validated model evaluation (AUC-ROC, AUC-PR, SHAP), and MLflow experiment tracking — using Python (NumPy, Pandas, Scikit-learn), R, and SQL. Use when designing or analysing controlled experiments, building and evaluating classification or regression models, performing causal analysis on observational data, engineering features for structured tabular datasets, or translating statistical findings into data-driven business decisions."},"isInternal":false,"tokens":2354,"sizeBytes":9404},{"name":"cicd_pipeline_guide.md","path":"engineering-team/skills/senior-devops/references/cicd_pipeline_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-devops/references/cicd_pipeline_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-devops%2Freferences%2Fcicd_pipeline_guide.md -->","isInternal":false,"tokens":367,"sizeBytes":1610},{"name":"deployment_strategies.md","path":"engineering-team/skills/senior-devops/references/deployment_strategies.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-devops/references/deployment_strategies.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-devops%2Freferences%2Fdeployment_strategies.md -->","isInternal":false,"tokens":365,"sizeBytes":1612},{"name":"infrastructure_as_code.md","path":"engineering-team/skills/senior-devops/references/infrastructure_as_code.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-devops/references/infrastructure_as_code.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-devops%2Freferences%2Finfrastructure_as_code.md -->","isInternal":false,"tokens":366,"sizeBytes":1613},{"name":"SKILL.md","path":"engineering-team/skills/senior-devops/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-devops/SKILL.md","title":"senior-devops","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-devops%2FSKILL.md -->","frontmatter":{"name":"senior-devops","description":"Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). 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-->","isInternal":false,"tokens":1960,"sizeBytes":8068},{"name":"tech_stack_guide.md","path":"engineering-team/skills/senior-fullstack/references/tech_stack_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-fullstack/references/tech_stack_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-fullstack%2Freferences%2Ftech_stack_guide.md -->","isInternal":false,"tokens":3378,"sizeBytes":14100},{"name":"SKILL.md","path":"engineering-team/skills/senior-fullstack/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-fullstack/SKILL.md","title":"senior-fullstack","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-fullstack%2FSKILL.md -->","frontmatter":{"name":"senior-fullstack","description":"Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and complexity scoring, and stack selection guidance. Use when the user asks to \"scaffold a new project\", \"create a Next.js app\", \"set up FastAPI with React\", \"analyze code quality\", \"audit my codebase\", \"what stack should I use\", \"generate project boilerplate\", or mentions fullstack development, project setup, or tech stack comparison."},"isInternal":false,"tokens":3419,"sizeBytes":14646},{"name":"llm_integration_guide.md","path":"engineering-team/skills/senior-ml-engineer/references/llm_integration_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-ml-engineer/references/llm_integration_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-ml-engineer%2Freferences%2Fllm_integration_guide.md -->","isInternal":false,"tokens":2028,"sizeBytes":8900},{"name":"mlops_production_patterns.md","path":"engineering-team/skills/senior-ml-engineer/references/mlops_production_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-ml-engineer/references/mlops_production_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-ml-engineer%2Freferences%2Fmlops_production_patterns.md -->","isInternal":false,"tokens":1730,"sizeBytes":7307},{"name":"rag_system_architecture.md","path":"engineering-team/skills/senior-ml-engineer/references/rag_system_architecture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-ml-engineer/references/rag_system_architecture.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-ml-engineer%2Freferences%2Frag_system_architecture.md -->","isInternal":false,"tokens":2398,"sizeBytes":10286},{"name":"SKILL.md","path":"engineering-team/skills/senior-ml-engineer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-ml-engineer/SKILL.md","title":"senior-ml-engineer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-ml-engineer%2FSKILL.md -->","frontmatter":{"name":"senior-ml-engineer","description":"ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization. Use when the user asks about deploying ML models to production, setting up MLOps infrastructure (MLflow, Kubeflow, Kubernetes, Docker), monitoring model performance or drift, building RAG pipelines, or integrating LLM APIs with retry logic and cost controls. Focused on production and operational concerns rather than model research or initial training.","metadata":{"triggers":["MLOps pipeline","model deployment","feature store","model monitoring","drift detection","RAG system","LLM integration","model serving","A/B testing ML","automated retraining"]}},"isInternal":false,"tokens":2274,"sizeBytes":9796},{"name":"agentic_system_design.md","path":"engineering-team/skills/senior-prompt-engineer/references/agentic_system_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-prompt-engineer/references/agentic_system_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-prompt-engineer%2Freferences%2Fagentic_system_design.md -->","isInternal":false,"tokens":4118,"sizeBytes":21700},{"name":"llm_evaluation_frameworks.md","path":"engineering-team/skills/senior-prompt-engineer/references/llm_evaluation_frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-prompt-engineer/references/llm_evaluation_frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-prompt-engineer%2Freferences%2Fllm_evaluation_frameworks.md -->","isInternal":false,"tokens":3542,"sizeBytes":13303},{"name":"prompt_engineering_patterns.md","path":"engineering-team/skills/senior-prompt-engineer/references/prompt_engineering_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-prompt-engineer/references/prompt_engineering_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-prompt-engineer%2Freferences%2Fprompt_engineering_patterns.md -->","isInternal":false,"tokens":3321,"sizeBytes":13675},{"name":"SKILL.md","path":"engineering-team/skills/senior-prompt-engineer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-prompt-engineer/SKILL.md","title":"senior-prompt-engineer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-prompt-engineer%2FSKILL.md -->","frontmatter":{"name":"senior-prompt-engineer","description":"Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools."},"isInternal":false,"tokens":2235,"sizeBytes":9954},{"name":"README.md","path":"engineering-team/skills/senior-qa/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-qa/README.md","title":"Senior-qa Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-qa%2FREADME.md -->","isInternal":false,"tokens":1392,"sizeBytes":5705},{"name":"qa_best_practices.md","path":"engineering-team/skills/senior-qa/references/qa_best_practices.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-qa/references/qa_best_practices.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-qa%2Freferences%2Fqa_best_practices.md -->","isInternal":false,"tokens":5764,"sizeBytes":23792},{"name":"test_automation_patterns.md","path":"engineering-team/skills/senior-qa/references/test_automation_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-qa/references/test_automation_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-qa%2Freferences%2Ftest_automation_patterns.md -->","isInternal":false,"tokens":5764,"sizeBytes":24981},{"name":"testing_strategies.md","path":"engineering-team/skills/senior-qa/references/testing_strategies.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-qa/references/testing_strategies.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-qa%2Freferences%2Ftesting_strategies.md -->","isInternal":false,"tokens":4253,"sizeBytes":17198},{"name":"SKILL.md","path":"engineering-team/skills/senior-qa/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-qa/SKILL.md","title":"senior-qa","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-qa%2FSKILL.md -->","frontmatter":{"name":"senior-qa","description":"Generates unit tests, integration tests, and E2E tests for React/Next.js applications. Scans components to create Jest + React Testing Library test stubs, analyzes Istanbul/LCOV coverage reports to surface gaps, scaffolds Playwright test files from Next.js routes, mocks API calls with MSW, creates test fixtures, and configures test runners. Use when the user asks to \"generate tests\", \"write unit tests\", \"analyze test coverage\", \"scaffold E2E tests\", \"set up Playwright\", \"configure Jest\", \"implement testing patterns\", or \"improve test quality\"."},"isInternal":false,"tokens":2017,"sizeBytes":8588},{"name":"compliance_requirements.md","path":"engineering-team/skills/senior-secops/references/compliance_requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-secops/references/compliance_requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-secops%2Freferences%2Fcompliance_requirements.md -->","isInternal":false,"tokens":5138,"sizeBytes":23807},{"name":"security_standards.md","path":"engineering-team/skills/senior-secops/references/security_standards.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-secops/references/security_standards.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-secops%2Freferences%2Fsecurity_standards.md -->","isInternal":false,"tokens":4431,"sizeBytes":19246},{"name":"vulnerability_management_guide.md","path":"engineering-team/skills/senior-secops/references/vulnerability_management_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-secops/references/vulnerability_management_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-secops%2Freferences%2Fvulnerability_management_guide.md -->","isInternal":false,"tokens":3461,"sizeBytes":14297},{"name":"SKILL.md","path":"engineering-team/skills/senior-secops/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-secops/SKILL.md","title":"senior-secops","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-secops%2FSKILL.md -->","frontmatter":{"name":"senior-secops","description":"Senior SecOps engineer skill for application security, vulnerability management, compliance verification, and secure development practices. Runs SAST/DAST scans, generates CVE remediation plans, checks dependency vulnerabilities, creates security policies, enforces secure coding patterns, and automates compliance checks against SOC2, PCI-DSS, HIPAA, and GDPR. Use when conducting a security review or audit, responding to a CVE or security incident, hardening infrastructure, implementing authentication or secrets management, running penetration test prep, checking OWASP Top 10 exposure, or enforcing security controls in CI/CD pipelines."},"isInternal":false,"tokens":3907,"sizeBytes":16062},{"name":"cryptography-implementation.md","path":"engineering-team/skills/senior-security/references/cryptography-implementation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-security/references/cryptography-implementation.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-security%2Freferences%2Fcryptography-implementation.md -->","isInternal":false,"tokens":5166,"sizeBytes":21912},{"name":"security-architecture-patterns.md","path":"engineering-team/skills/senior-security/references/security-architecture-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-security/references/security-architecture-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-security%2Freferences%2Fsecurity-architecture-patterns.md -->","isInternal":false,"tokens":4455,"sizeBytes":22198},{"name":"threat-modeling-guide.md","path":"engineering-team/skills/senior-security/references/threat-modeling-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-security/references/threat-modeling-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-security%2Freferences%2Fthreat-modeling-guide.md -->","isInternal":false,"tokens":4443,"sizeBytes":22659},{"name":"SKILL.md","path":"engineering-team/skills/senior-security/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/senior-security/SKILL.md","title":"senior-security","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fsenior-security%2FSKILL.md -->","frontmatter":{"name":"senior-security","description":"Use when the user asks for STRIDE threat modeling, DREAD risk scoring, data-flow-diagram threat analysis, or a quick secret scan — or when a security request needs routing to the right specialist skill (pen-testing, incident response, cloud posture, red team, AI security, threat hunting, secure code review). This skill owns threat modeling; everything else routes to a sibling."},"isInternal":false,"tokens":1244,"sizeBytes":5188},{"name":"SKILL.md","path":"engineering-team/skills/stripe-integration-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/stripe-integration-expert/SKILL.md","title":"stripe-integration-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Fstripe-integration-expert%2FSKILL.md -->","frontmatter":{"name":"stripe-integration-expert","description":"Production-grade Stripe integrations: subscriptions with trials and proration, one-time payments, usage-based billing, checkout sessions, idempotent webhook handlers, customer portal, and invoicing. Covers Next.js, Express, and Django patterns. Use when integrating Stripe for the first time, debugging webhook reliability issues, migrating from a different payment provider, or adding usage-based billing to an existing subscription product."},"isInternal":false,"tokens":3308,"sizeBytes":14948},{"name":"expected_output.json","path":"engineering-team/skills/tdd-guide/assets/expected_output.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/tdd-guide/assets/expected_output.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Ftdd-guide%2Fassets%2Fexpected_output.json -->","frontmatter":{"test_generation":{"generated_tests":[{"name":"should_validate_password_length_successfully","type":"happy_path","priority":"P0","framework":"jest","code":"it('should validate password with sufficient length', () => {\n  const validator = new PasswordValidator();\n  const result = validator.validate('Test@123');\n  expect(result).toBe(true);\n});"},{"name":"should_handle_too_short_password","type":"error_case","priority":"P0","framework":"jest","code":"it('should reject password shorter than 8 characters', () => {\n  const validator = new PasswordValidator();\n  const result = validator.validate('Test@1');\n  expect(result).toBe(false);\n});"}],"test_file":"password-validator.test.ts","total_tests_generated":8},"coverage_analysis":{"summary":{"line_coverage":100,"branch_coverage":100,"function_coverage":100,"total_lines":20,"covered_lines":20,"total_branches":12,"covered_branches":12},"gaps":[],"assessment":"Excellent coverage - all paths tested"},"metrics":{"complexity":{"cyclomatic_complexity":6,"cognitive_complexity":8,"testability_score":85,"assessment":"Medium complexity - moderately testable"},"test_quality":{"total_tests":8,"total_assertions":16,"avg_assertions_per_test":2,"isolation_score":95,"naming_quality":87.5,"quality_score":88,"test_smells":[]}},"recommendations":[{"priority":"P1","type":"edge_case_coverage","message":"Consider adding boundary value tests","action":"Add tests for exact boundary conditions (7 vs 8 characters)","impact":"medium"},{"priority":"P2","type":"test_organization","message":"Group related tests using describe blocks","action":"Organize tests by feature (length validation, complexity validation)","impact":"low"}],"tdd_workflow":{"current_phase":"GREEN","status":"Tests passing, ready for refactoring","next_steps":["Review code for duplication","Consider extracting validation rules","Commit changes"]}},"isInternal":false,"tokens":630,"sizeBytes":2404},{"name":"sample_input_python.json","path":"engineering-team/skills/tdd-guide/assets/sample_input_python.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/tdd-guide/assets/sample_input_python.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fskills%2Ftdd-guide%2Fassets%2Fsample_input_python.json -->","frontmatter":{"language":"python","framework":"pytest","source_code":"def calculate_discount(price: float, discount_percent: float) -> float:\n    \"\"\"Calculate discounted price.\"\"\"\n    if price < 0:\n        raise ValueError(\"Price cannot be negative\")\n    if discount_percent < 0 or discount_percent > 100:\n        raise ValueError(\"Discount must be between 0 and 100\")\n    \n    discount_amount = price * (discount_percent / 100)\n    return round(price - discount_amount, 2)","requirements":{"user_stories":[{"description":"Calculate discounted price for valid inputs","action":"calculate_discount","given":["Price is 100","Discount is 20%"],"when":"Discount is calculated","then":"Return 80.00","error_conditions":[{"condition":"negative_price","description":"Price is negative","error_type":"ValueError"},{"condition":"invalid_discount","description":"Discount is out of range","error_type":"ValueError"}],"edge_cases":[{"scenario":"zero_discount","description":"Discount is 0%"},{"scenario":"full_discount","description":"Discount is 100%"}]}]},"coverage_threshold":90},"isInternal":false,"tokens":334,"sizeBytes":1443},{"name":"sample_input_typescript.json","path":"engineering-team/skills/tdd-guide/assets/sample_input_typescript.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/skills/tdd-guide/assets/sample_input_typescript.json","title":"Assets 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Use when analyzing sales pipeline coverage, forecasting revenue, evaluating go-to-market performance, reviewing sales metrics, assessing pipeline analysis, tracking forecast accuracy with MAPE, calculating GTM efficiency, or measuring sales efficiency and unit economics for SaaS teams.","tools":[{"script":"business-growth/skills/revenue-operations/scripts/forecast_accuracy_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 business-growth/skills/revenue-operations/scripts/forecast_accuracy_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"business-growth/skills/revenue-operations/scripts/gtm_efficiency_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 business-growth/skills/revenue-operations/scripts/gtm_efficiency_calculator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"business-growth/skills/revenue-operations/scripts/pipeline_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-growth/skills/revenue-operations/scripts/pipeline_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-growth/skills/revenue-operations/scripts/pipeline_analyzer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["gtm-efficiency-benchmarks.md","pipeline-management-framework.md","revops-metrics-guide.md"]},{"name":"sales-engineer","path":"business-growth/skills/sales-engineer","description":"Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'.","tools":[{"script":"business-growth/skills/sales-engineer/scripts/competitive_matrix_builder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 business-growth/skills/sales-engineer/scripts/competitive_matrix_builder.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"business-growth/skills/sales-engineer/scripts/poc_planner.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 business-growth/skills/sales-engineer/scripts/poc_planner.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"business-growth/skills/sales-engineer/scripts/rfp_response_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 business-growth/skills/sales-engineer/scripts/rfp_response_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["competitive-positioning-framework.md","poc-best-practices.md","rfp-response-guide.md"]}]},"isInternal":false,"tokens":2062,"sizeBytes":9356},{"name":"business-operations.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/business-operations.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/business-operations.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fbusiness-operations.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"business-operations","skill_count":7,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"business-operations-skills","path":"business-operations/skills/business-operations-skills","description":"Use when running, diagnosing, or designing internal business operations — process documentation, vendor SLAs, capacity planning, internal comms, SOP/runbook authoring, procurement spend. Triggers on \"BizOps review\", \"where's the bottleneck\", \"vendor health\", \"internal SOP\", \"all-hands deck\", \"spend categorization\", \"capacity for Q3\", \"process mapping\". Forks context to route to one of six BizOps sub-skills (process-mapper, vendor-management, capacity-planner, internal-comms, knowledge-ops, procurement-optimizer) and returns a digest. Distinct from business-growth (external sales motion) and …","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":true},"references":[]},{"name":"capacity-planner","path":"business-operations/skills/capacity-planner","description":"Use when an ops leader (Director of CX, Head of Support, VP Ops, Head of BizOps, Head of IT ops, Head of Finance ops) is sizing ops capacity, building a headcount plan, modeling utilization risk, planning Q3 capacity or annual support capacity, or designing CS coverage — and needs Erlang-C queueing math, P90 demand sizing, shrinkage-adjusted FTE, manager-trigger thresholds, and a quarterly hiring sequence with ramp + attrition. Apply when sustained team utilization is above 80% or when the team is growing >50% in 12 months. Run before committing the headcount budget. This is NOT engineering …","tools":[{"script":"business-operations/skills/capacity-planner/scripts/capacity_modeler.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/capacity-planner/scripts/capacity_modeler.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/capacity-planner/scripts/capacity_modeler.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/capacity-planner/scripts/hiring_sequencer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/capacity-planner/scripts/hiring_sequencer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/capacity-planner/scripts/hiring_sequencer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/capacity-planner/scripts/utilization_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/capacity-planner/scripts/utilization_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/capacity-planner/scripts/utilization_analyzer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["capacity_anti_patterns.md","ops_workforce_planning_canon.md","queueing_theory_canon.md"]},{"name":"internal-comms","path":"business-operations/skills/internal-comms","description":"Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management communication — a re-org announcement, a tool rollout, a policy change, a leadership transition, a layoff, an acquisition close, or an internal product launch — and the audience is employees (not customers). Pairs Prosci ADKAR and Kotter's 8-step change model with deterministic stdlib-only Python tools to produce a sequenced touchpoint calendar, a Kotter-compliant primary announcement, an audience-segmented FAQ, and manager cascade talking points …","tools":[{"script":"business-operations/skills/internal-comms/scripts/change_announcement_builder.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/internal-comms/scripts/change_announcement_builder.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/internal-comms/scripts/change_announcement_builder.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/internal-comms/scripts/comms_calendar_builder.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/internal-comms/scripts/comms_calendar_builder.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/internal-comms/scripts/comms_calendar_builder.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/internal-comms/scripts/comms_template_filler.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/internal-comms/scripts/comms_template_filler.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/internal-comms/scripts/comms_template_filler.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["announcement_anti_patterns.md","change_management_canon.md","internal_comms_canon.md"]},{"name":"knowledge-ops","path":"business-operations/skills/knowledge-ops","description":"Use when a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Ishikawa's 5W2H method, Gawande's *The …","tools":[{"script":"business-operations/skills/knowledge-ops/scripts/kb_ingester.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/knowledge-ops/scripts/kb_ingester.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/knowledge-ops/scripts/kb_ingester.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/knowledge-ops/scripts/runbook_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/knowledge-ops/scripts/runbook_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/knowledge-ops/scripts/runbook_validator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/knowledge-ops/scripts/sop_generator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/knowledge-ops/scripts/sop_generator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/knowledge-ops/scripts/sop_generator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":true},"references":["5w2h_sop_canon.md","kb_hygiene_anti_patterns.md","runbook_canon.md"]},{"name":"process-mapper","path":"business-operations/skills/process-mapper","description":"Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time. Pairs Lean / Six Sigma / Theory-of-Constraints canon with deterministic stdlib-only Python tools to produce a process map, a ranked bottleneck list (with severity + root-cause hypothesis), and a …","tools":[{"script":"business-operations/skills/process-mapper/scripts/bottleneck_detector.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/process-mapper/scripts/bottleneck_detector.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/process-mapper/scripts/bottleneck_detector.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/process-mapper/scripts/cycle_time_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/process-mapper/scripts/cycle_time_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/process-mapper/scripts/cycle_time_analyzer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/process-mapper/scripts/process_documenter.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/process-mapper/scripts/process_documenter.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/process-mapper/scripts/process_documenter.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["bottleneck_anti_patterns.md","bpmn_essentials.md","lean_six_sigma_canon.md"]},{"name":"procurement-optimizer","path":"business-operations/skills/procurement-optimizer","description":"Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs a spend audit, spend categorization (UNSPSC-aligned with Pareto breakdown and industry profiles), purchasing-cycle analysis (bottleneck categories per Goldratt's Theory of Constraints), or risk-balanced supplier consolidation that refuses single-source recommendations for tier-1 categories without a documented break-glass plan. Triggers on \"spend audit\", \"SaaS audit\", \"spend categorization\", \"supplier rationalization\", \"supplier consolidation\", \"category …","tools":[{"script":"business-operations/skills/procurement-optimizer/scripts/purchasing_cycle_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/procurement-optimizer/scripts/purchasing_cycle_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/procurement-optimizer/scripts/purchasing_cycle_analyzer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/procurement-optimizer/scripts/spend_categorizer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/procurement-optimizer/scripts/spend_categorizer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/procurement-optimizer/scripts/spend_categorizer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/procurement-optimizer/scripts/supplier_consolidation.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/procurement-optimizer/scripts/supplier_consolidation.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/procurement-optimizer/scripts/supplier_consolidation.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["procurement_anti_patterns.md","saas_management_canon.md","spend_management_canon.md"]},{"name":"vendor-management","path":"business-operations/skills/vendor-management","description":"Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA compliance with credit-claim flags, classifying third-party risk across 4 risk vectors, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Triggers on \"vendor SLA\", \"vendor scorecard\", \"third-party risk\", \"TPRM\", \"vendor review\", \"supplier performance\", \"vendor health check\", \"renewal review\".","tools":[{"script":"business-operations/skills/vendor-management/scripts/sla_compliance_tracker.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/vendor-management/scripts/sla_compliance_tracker.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/vendor-management/scripts/sla_compliance_tracker.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/vendor-management/scripts/vendor_risk_classifier.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/vendor-management/scripts/vendor_risk_classifier.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/vendor-management/scripts/vendor_risk_classifier.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"business-operations/skills/vendor-management/scripts/vendor_scorer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 business-operations/skills/vendor-management/scripts/vendor_scorer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 business-operations/skills/vendor-management/scripts/vendor_scorer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["sla_design_patterns.md","vendor_management_canon.md","vendor_risk_anti_patterns.md"]}]},"isInternal":false,"tokens":4298,"sizeBytes":19208},{"name":"c-level-advisor.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/c-level-advisor.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/c-level-advisor.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fc-level-advisor.json -->","isInternal":false,"tokens":11856,"sizeBytes":50030},{"name":"commercial.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/commercial.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/commercial.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fcommercial.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"commercial","skill_count":8,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"channel-economics","path":"commercial/skills/channel-economics","description":"Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts …","tools":[{"script":"commercial/skills/channel-economics/scripts/channel_mix_optimizer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/channel-economics/scripts/channel_mix_optimizer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/channel-economics/scripts/channel_mix_optimizer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/channel-economics/scripts/channel_roi_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/channel-economics/scripts/channel_roi_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/channel-economics/scripts/channel_roi_analyzer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/channel-economics/scripts/cost_to_serve_calculator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/channel-economics/scripts/cost_to_serve_calculator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/channel-economics/scripts/cost_to_serve_calculator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["channel_anti_patterns.md","channel_economics_canon.md","cost_to_serve_canon.md"]},{"name":"commercial-forecaster","path":"commercial/skills/commercial-forecaster","description":"Use when building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board number — especially when the CRO needs to walk the board through funnel math + cohort ARR + per-stage conversion assumptions without the theatre of a single undefended number. Decomposes pipeline into commit, best-case, and pipe-only tiers; projects cohort-level NRR/GRR to surface leaky cohorts before they show up in the consolidated number; scores per-stage funnel confidence so soft-floor stages get treated differently from high-confidence ones. Every …","tools":[{"script":"commercial/skills/commercial-forecaster/scripts/bookings_forecaster.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/commercial-forecaster/scripts/bookings_forecaster.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/commercial-forecaster/scripts/bookings_forecaster.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/commercial-forecaster/scripts/cohort_arr_projector.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/commercial-forecaster/scripts/cohort_arr_projector.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/commercial-forecaster/scripts/cohort_arr_projector.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/commercial-forecaster/scripts/funnel_confidence_scorer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/commercial-forecaster/scripts/funnel_confidence_scorer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/commercial-forecaster/scripts/funnel_confidence_scorer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["cohort_analysis_canon.md","forecast_anti_patterns.md","saas_forecasting_canon.md"]},{"name":"commercial-policy","path":"commercial/skills/commercial-policy","description":"Use when designing or revising a company's commercial policy — the rules of engagement governing discounts off list price, approver thresholds, exception flows, and the deal framework that Deal Desk and AEs operate under. Covers discount matrix design (ARR band x term length x payment terms x strategic value), commercial policy design, exception policy, discount governance, approval thresholds, deal framework structure, and policy linting (contradictions, gaps, cliff edges, gaming surfaces). For Head of Commercial, Head of Deal Desk, VP Sales, or RevOps at the policy-design moment — NOT …","tools":[{"script":"commercial/skills/commercial-policy/scripts/discount_matrix_builder.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/commercial-policy/scripts/discount_matrix_builder.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/commercial-policy/scripts/discount_matrix_builder.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/commercial-policy/scripts/exception_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/commercial-policy/scripts/exception_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/commercial-policy/scripts/exception_router.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/commercial-policy/scripts/policy_linter.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/commercial-policy/scripts/policy_linter.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/commercial-policy/scripts/policy_linter.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["discount_governance_canon.md","policy_anti_patterns.md","policy_design_canon.md"]},{"name":"commercial-skills","path":"commercial/skills/commercial-skills","description":"Use when reviewing, approving, or designing commercial motion — pricing models, deal review, discount approval, partnership economics, channel mix, commercial policy, RFP/RFI response, bookings forecast. Triggers on \"review this deal\", \"should we discount\", \"pricing model\", \"partner economics\", \"RFP response\", \"bookings forecast\", \"channel mix\". Forks context to route to one of seven Commercial sub-skills (pricing-strategist, deal-desk, partnerships-architect, channel-economics, commercial-policy, rfp-responder, commercial-forecaster) and returns a digest. Distinct from business-growth …","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":[]},{"name":"deal-desk","path":"commercial/skills/deal-desk","description":"Use when reviewing a specific inbound deal before close — when sales has asked for a discount that exceeds AE authority, when the customer has redlined the MSA, when per-deal economics (margin after discount, multi-year payment shape, indemnity exposure) need to be quantified, or when discount approval needs to be routed to a named human approver (Sales Director, VP Sales, CFO, CRO, General Counsel). Covers deal review, discount approval routing, per-deal margin scoring, deal exception handling, MSA redline triage, contract landmine detection (uncapped indemnity, MFN, perpetual …","tools":[{"script":"commercial/skills/deal-desk/scripts/deal_scorer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/deal-desk/scripts/deal_scorer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/deal-desk/scripts/deal_scorer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/deal-desk/scripts/discount_approval_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/deal-desk/scripts/discount_approval_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/deal-desk/scripts/discount_approval_router.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/deal-desk/scripts/terms_redliner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/deal-desk/scripts/terms_redliner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/deal-desk/scripts/terms_redliner.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["contract_landmines.md","deal_desk_canon.md","discount_economics.md"]},{"name":"partnerships-architect","path":"commercial/skills/partnerships-architect","description":"Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic …","tools":[{"script":"commercial/skills/partnerships-architect/scripts/joint_gtm_planner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/partnerships-architect/scripts/joint_gtm_planner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/partnerships-architect/scripts/joint_gtm_planner.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/partnerships-architect/scripts/partner_tier_classifier.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/partnerships-architect/scripts/partner_tier_classifier.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/partnerships-architect/scripts/partner_tier_classifier.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/partnerships-architect/scripts/revshare_modeler.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/partnerships-architect/scripts/revshare_modeler.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/partnerships-architect/scripts/revshare_modeler.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["channel_partner_canon.md","joint_gtm_canon.md","partnership_anti_patterns.md"]},{"name":"pricing-strategist","path":"commercial/skills/pricing-strategist","description":"Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.","tools":[{"script":"commercial/skills/pricing-strategist/scripts/packaging_designer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/pricing-strategist/scripts/packaging_designer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/pricing-strategist/scripts/packaging_designer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/pricing-strategist/scripts/pricing_model_picker.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/pricing-strategist/scripts/pricing_model_picker.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/pricing-strategist/scripts/pricing_model_picker.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/pricing-strategist/scripts/wtp_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/pricing-strategist/scripts/wtp_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/pricing-strategist/scripts/wtp_analyzer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["packaging_anti_patterns.md","saas_pricing_canon.md","van_westendorp_methodology.md"]},{"name":"rfp-responder","path":"commercial/skills/rfp-responder","description":"Use when an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the …","tools":[{"script":"commercial/skills/rfp-responder/scripts/response_drafter.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/rfp-responder/scripts/response_drafter.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/rfp-responder/scripts/response_drafter.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/rfp-responder/scripts/rfp_parser.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/rfp-responder/scripts/rfp_parser.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/rfp-responder/scripts/rfp_parser.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"commercial/skills/rfp-responder/scripts/winrate_predictor.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 commercial/skills/rfp-responder/scripts/winrate_predictor.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 commercial/skills/rfp-responder/scripts/winrate_predictor.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["rfp_anti_patterns.md","rfp_strategy_canon.md","shipley_method_canon.md"]}]},"isInternal":false,"tokens":4796,"sizeBytes":21401},{"name":"compliance-os.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/compliance-os.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/compliance-os.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fcompliance-os.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"compliance-os","skill_count":9,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"ai-act-readiness","path":"compliance-os/skills/ai-act-readiness","description":"/compliance-os:ai-act-readiness <system> — EU AI Act 6-question forcing interrogation. Use during AI-system intake, before EU deployment, or during annual compliance refresh as Article 113 obligations phase in (2025-02-02 / 2025-08-02 / 2026-08-02 / 2027-08-02).","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":[]},{"name":"aims-audit","path":"compliance-os/skills/aims-audit","description":"/compliance-os:aims-audit <scope> — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. Use before certification stage 1, before annual internal audit cycles, or when onboarding a new AI system into an existing AIMS.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":[]},{"name":"compliance-os","path":"compliance-os/skills/compliance-os","description":"Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE internal audits, and CONSOLIDATE evidence across multiple frameworks. Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario …","tools":[{"script":"compliance-os/skills/compliance-os/scripts/audit_simulator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 compliance-os/skills/compliance-os/scripts/audit_simulator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"compliance-os/skills/compliance-os/scripts/cross_framework_mapper.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 compliance-os/skills/compliance-os/scripts/cross_framework_mapper.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"compliance-os/skills/compliance-os/scripts/evidence_pool_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 compliance-os/skills/compliance-os/scripts/evidence_pool_generator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"compliance-os/skills/compliance-os/scripts/framework_selector.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 compliance-os/skills/compliance-os/scripts/framework_selector.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["audit_simulation_methodology.md","compliance_os_pattern.md","cross_framework_overlap.md","evidence_artifact_reuse_index.md","evidence_management.md","multi_framework_audit_playbook.md"]},{"name":"compliance-readiness","path":"compliance-os/skills/compliance-readiness","description":"/compliance-os:compliance-readiness <program> — Multi-framework compliance officer 6-question forcing interrogation of any compliance program. Use before starting a new framework, planning the annual audit calendar, or preparing for certification stage 1.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":[]},{"name":"fda-qsr-audit-prep","path":"compliance-os/skills/fda-qsr-audit-prep","description":"/compliance-os:fda-qsr-audit-prep <scope> — FDA 21 CFR 820 (QSR / QMSR) audit 6-question forcing interrogation. Post-Feb 2026 substantially harmonized with ISO 13485. Use before annual internal QSR audit, pre-FDA-inspection readiness, or Form 483 response.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":[]},{"name":"gdpr-audit-prep","path":"compliance-os/skills/gdpr-audit-prep","description":"/compliance-os:gdpr-audit-prep <scope> — GDPR audit 6-question Article-cited forcing interrogation. Use before annual internal GDPR review, post-breach internal audit, DPA investigation readiness, or acquisition due diligence.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":[]},{"name":"iso13485-audit-prep","path":"compliance-os/skills/iso13485-audit-prep","description":"/compliance-os:iso13485-audit-prep <scope> — ISO 13485 QMS audit 6-question forcing interrogation. Design controls + CAPA + post-market focused. Use before Clause 8.2.4 internal audit, MDR / FDA QSR alignment review, or product-launch DHF closure audit.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":[]},{"name":"iso27001-audit-prep","path":"compliance-os/skills/iso27001-audit-prep","description":"/compliance-os:iso27001-audit-prep <scope> — ISO 27001 ISMS audit readiness 6-question forcing interrogation. Use before annual Clause 9.2 internal audit, surveillance audit prep, or stage 1 certification readiness.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":[]},{"name":"soc2-audit-prep","path":"compliance-os/skills/soc2-audit-prep","description":"/compliance-os:soc2-audit-prep <scope> — SOC 2 Type II readiness 6-question forcing interrogation. Observation-period focused. Use before Type II observation begins, mid-period checkpoint, or pre-field-test month-10 readiness.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":[]}]},"isInternal":false,"tokens":2003,"sizeBytes":8029},{"name":"engineering-team.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/engineering-team.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/engineering-team.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fengineering-team.json -->","isInternal":false,"tokens":11142,"sizeBytes":50030},{"name":"engineering.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/engineering.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/engineering.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fengineering.json -->","isInternal":false,"tokens":11436,"sizeBytes":50030},{"name":"finance.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/finance.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/finance.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Ffinance.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"finance","skill_count":4,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"business-investment-advisor","path":"finance/business-investment-advisor/skills/business-investment-advisor","description":"Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring, technology, or any capital expenditure. Also use for ROI calculations, IRR, NPV, payback period, build vs buy decisions, lease vs buy analysis, vendor evaluation, or deciding where to allocate limited budget for maximum return.","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":false},"references":[]},{"name":"finance-skills","path":"finance/skills/finance-skills","description":"Router/index for the 2 finance skills bundled in this plugin: financial-analyst (ratio analysis, DCF valuation, budget variance, rolling forecasts) and saas-metrics-coach (ARR/MRR, churn, CAC/LTV, NRR, quick ratio). Use when a finance request doesn't obviously match one skill and you need to pick the right one (e.g., 'analyze these financials', 'how healthy are my SaaS metrics').","tools":[],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":false},"references":[]},{"name":"financial-analyst","path":"finance/skills/financial-analyst","description":"Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.","tools":[{"script":"finance/skills/financial-analyst/scripts/budget_variance_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/financial-analyst/scripts/budget_variance_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"finance/skills/financial-analyst/scripts/dcf_valuation.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/financial-analyst/scripts/dcf_valuation.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"finance/skills/financial-analyst/scripts/forecast_builder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/financial-analyst/scripts/forecast_builder.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"finance/skills/financial-analyst/scripts/ratio_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/financial-analyst/scripts/ratio_calculator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":false},"references":["financial-ratios-guide.md","forecasting-best-practices.md","industry-adaptations.md","valuation-methodology.md"]},{"name":"saas-metrics-coach","path":"finance/skills/saas-metrics-coach","description":"SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how their SaaS business is doing.","tools":[{"script":"finance/skills/saas-metrics-coach/scripts/metrics_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/saas-metrics-coach/scripts/metrics_calculator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"finance/skills/saas-metrics-coach/scripts/quick_ratio_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/saas-metrics-coach/scripts/quick_ratio_calculator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"finance/skills/saas-metrics-coach/scripts/unit_economics_simulator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 finance/skills/saas-metrics-coach/scripts/unit_economics_simulator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":false},"references":["benchmarks.md","formulas.md"]}]},"isInternal":false,"tokens":1439,"sizeBytes":6210},{"name":"loop-library.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/loop-library.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/loop-library.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Floop-library.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"loop-library","skill_count":1,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"loop-library","path":"loop-library","description":"Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring agent workflow or automation cadence, turn an outcome into a bounded copy-ready loop, or review an existing loop for weak checks, unsafe authority, unbounded repetition, stale state, or unclear …","tools":[],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["audit.md","discover.md"]}]},"isInternal":false,"tokens":321,"sizeBytes":1334},{"name":"markdown-html.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/markdown-html.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/markdown-html.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fmarkdown-html.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"markdown-html","skill_count":5,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"design-system","path":"markdown-html/skills/design-system","description":"Captures the user's brand identity once via a 10-question onboarding wizard (primary/accent HEX + heading + body Google Fonts + design style editorial/technical/minimal/playful + default output directory + syntax theme + TOC behavior + optional logo/company), validates body-text and link contrast against WCAG 2.2 AA, derives 12 CSS custom properties in HSL space, and stores the result for every markdown-html converter to consume. Use before any markdown-html conversion. Triggers on first-run onboarding (\"set up the brand\", \"configure markdown-html\", \"run onboarding\"), on explicit reset …","tools":[{"script":"markdown-html/skills/design-system/scripts/brand_palette_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 markdown-html/skills/design-system/scripts/brand_palette_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 markdown-html/skills/design-system/scripts/brand_palette_validator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"markdown-html/skills/design-system/scripts/config_loader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 markdown-html/skills/design-system/scripts/config_loader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 markdown-html/skills/design-system/scripts/config_loader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"markdown-html/skills/design-system/scripts/onboard.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 markdown-html/skills/design-system/scripts/onboard.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":false,"close_out":false},"references":["design_token_canon.md","typography_pairing.md","wcag_accessibility.md"]},{"name":"markdown-html-orchestrator","path":"markdown-html/skills/markdown-html-orchestrator","description":"Use when a user wants to convert any markdown file in their Claude project into a single-file, lightly-interactive HTML — long-form documents (specs, plans, RFCs, reports, explainers), code reviews with diffs and severity-tagged annotations, or slide decks. Triggers on \"convert this markdown to HTML\", \"make this an HTML file\", \"turn this into an interactive document\", \"render this report as HTML\", \"PR writeup as HTML\", \"slides from this markdown\". 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Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs-md-review. Refuses without explicit --reviewer (a code review must name a human), refuses if no diff hunks present (route to md-document instead), and refuses …","tools":[{"script":"markdown-html/skills/md-review/scripts/annotation_extractor.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 markdown-html/skills/md-review/scripts/annotation_extractor.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 markdown-html/skills/md-review/scripts/annotation_extractor.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"markdown-html/skills/md-review/scripts/diff_parser.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 markdown-html/skills/md-review/scripts/diff_parser.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 markdown-html/skills/md-review/scripts/diff_parser.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"markdown-html/skills/md-review/scripts/review_html_renderer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 markdown-html/skills/md-review/scripts/review_html_renderer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 markdown-html/skills/md-review/scripts/review_html_renderer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["diff_rendering_canon.md","pr_annotation_ux.md","severity_coding.md"]},{"name":"md-slides","path":"markdown-html/skills/md-slides","description":"Converts a markdown deck (slides separated by `---` HR boundaries or by `# ` H1 headings, with optional `<!-- notes: ... -->` presenter notes blocks) into a single-file HTML presentation with arrow-key / space / PgDn / PgUp / Home / End / P / Esc keyboard navigation, presenter mode (split view with current slide + speaker notes + clock + next-slide preview), URL-hash deep linking, and `@media print` page-per-slide for PDF export. 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Covers user story writing, acceptance criteria, sprint planning, and velocity tracking. Use when writing user stories, creating acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing the backlog.","tools":[{"script":"product-team/agile-product-owner/skills/agile-product-owner/scripts/user_story_generator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 product-team/agile-product-owner/skills/agile-product-owner/scripts/user_story_generator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 product-team/agile-product-owner/skills/agile-product-owner/scripts/user_story_generator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["sprint-planning-guide.md","user-story-templates.md"]},{"name":"apple-hig-expert","path":"product-team/apple-hig-expert/skills/apple-hig-expert","description":"Audits and designs iOS/macOS/watchOS/visionOS interfaces against the Apple Human Interface Guidelines, including the Liquid Glass design language (announced WWDC25, shipped with iOS 26/macOS Tahoe, Sept 2025). Use when reviewing an Apple-platform mockup or app for HIG compliance, checking contrast or tap-target sizes, or designing native-feeling Apple UI (e.g., 'audit my iOS app against the HIG', 'is this text readable on Liquid Glass?').","tools":[{"script":"product-team/apple-hig-expert/skills/apple-hig-expert/scripts/hig_checker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/apple-hig-expert/skills/apple-hig-expert/scripts/hig_checker.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["accessibility.md","platform-specifics.md","visual-design.md"]},{"name":"code-to-prd","path":"product-team/code-to-prd/skills/code-to-prd","description":"Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Use when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document …","tools":[{"script":"product-team/code-to-prd/skills/code-to-prd/scripts/codebase_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/code-to-prd/skills/code-to-prd/scripts/codebase_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"product-team/code-to-prd/skills/code-to-prd/scripts/prd_scaffolder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/code-to-prd/skills/code-to-prd/scripts/prd_scaffolder.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["framework-patterns.md","prd-quality-checklist.md"]},{"name":"research-summarizer","path":"product-team/research-summarizer/skills/research-summarizer","description":"Structured research summarization agent skill for non-dev users. Handles academic papers, web articles, reports, and documentation. Extracts key findings, generates comparative analyses, and produces properly formatted citations. Use when: user wants to summarize a research paper, compare multiple sources, extract citations from documents, or create structured research briefs. Plugin for Claude Code, Codex, Gemini CLI, and OpenClaw.","tools":[{"script":"product-team/research-summarizer/skills/research-summarizer/scripts/extract_citations.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/research-summarizer/skills/research-summarizer/scripts/extract_citations.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"product-team/research-summarizer/skills/research-summarizer/scripts/format_summary.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/research-summarizer/skills/research-summarizer/scripts/format_summary.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["citation-formats.md","summary-templates.md"]},{"name":"competitive-teardown","path":"product-team/skills/competitive-teardown","description":"Analyzes competitor products and companies by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices scored across 12 dimensions, SWOT analyses, positioning maps, UX audits, pricing model breakdowns, action item roadmaps, and stakeholder presentation templates. Use when conducting competitor analysis, comparing products against competitors, researching the competitive landscape, building battle cards for sales, preparing for a product strategy or roadmap session …","tools":[{"script":"product-team/skills/competitive-teardown/scripts/competitive_matrix_builder.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/competitive-teardown/scripts/competitive_matrix_builder.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["analysis-templates.md","competitive-analysis-frameworks.md","data-collection-guide.md","scoring-rubric.md"]},{"name":"experiment-designer","path":"product-team/skills/experiment-designer","description":"Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.","tools":[{"script":"product-team/skills/experiment-designer/scripts/sample_size_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/experiment-designer/scripts/sample_size_calculator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["experiment-playbook.md","statistics-reference.md"]},{"name":"landing-page-generator","path":"product-team/skills/landing-page-generator","description":"Generates high-converting landing pages as complete Next.js/React (TSX) components with Tailwind CSS. Creates hero sections, feature grids, pricing tables, FAQ accordions, testimonial blocks, and CTA sections using proven copy frameworks (PAS, AIDA, BAB). Outputs SEO meta tags, structured data, and performance-optimised code targeting Core Web Vitals (LCP < 1s, CLS < 0.1). Use when the user asks to create a landing page, marketing page, homepage, single-page site, lead capture page, campaign page, promo page, or conversion-optimised web page — or when they want to A/B test landing page …","tools":[{"script":"product-team/skills/landing-page-generator/scripts/landing_page_scaffolder.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/landing-page-generator/scripts/landing_page_scaffolder.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["conversion-patterns.md","copy-frameworks.md","landing-page-patterns.md","seo-checklist.md"]},{"name":"product-analytics","path":"product-team/skills/product-analytics","description":"Use when defining product KPIs, building metric dashboards, running cohort or retention analysis, or interpreting feature adoption trends across product stages.","tools":[{"script":"product-team/skills/product-analytics/scripts/metrics_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/product-analytics/scripts/metrics_calculator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":["dashboard-templates.md","metrics-frameworks.md"]},{"name":"product-discovery","path":"product-team/skills/product-discovery","description":"Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources.","tools":[{"script":"product-team/skills/product-discovery/scripts/assumption_mapper.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/product-discovery/scripts/assumption_mapper.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":["discovery-frameworks.md"]},{"name":"product-manager-toolkit","path":"product-team/skills/product-manager-toolkit","description":"Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use when prioritizing features, synthesizing user research, writing requirement documentation, or developing product strategy.","tools":[{"script":"product-team/skills/product-manager-toolkit/scripts/customer_interview_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/product-manager-toolkit/scripts/customer_interview_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":false},"references":["frameworks.md","input-output-examples.md","prd_templates.md"]},{"name":"product-skills","path":"product-team/skills/product-skills","description":"Use when coordinating product work across the 12 bundled product sub-skills (RICE, OKRs, UX research, design tokens, competitive teardown, analytics, experiments, discovery, roadmaps, spec-to-repo, landing pages, SaaS scaffolding) or the 4 standalone product-team plugins (user stories, Apple HIG, code-to-PRD, research summarizer). Triggers on 'help me prioritize', 'plan a product experiment', 'we ship features nobody uses', 'run the discovery loop', 'is our OST sound'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a …","tools":[{"script":"product-team/skills/product-skills/scripts/discovery_cadence_tracker.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 product-team/skills/product-skills/scripts/discovery_cadence_tracker.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 product-team/skills/product-skills/scripts/discovery_cadence_tracker.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"product-team/skills/product-skills/scripts/ost_linter.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 product-team/skills/product-skills/scripts/ost_linter.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 product-team/skills/product-skills/scripts/ost_linter.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"product-team/skills/product-skills/scripts/product_goal_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 product-team/skills/product-skills/scripts/product_goal_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 product-team/skills/product-skills/scripts/product_goal_router.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":true},"references":["ai_product_evals.md","continuous_discovery_canon.md","product_operating_model.md"]},{"name":"product-strategist","path":"product-team/skills/product-strategist","description":"Strategic product leadership toolkit for Head of Product covering OKR cascade generation, quarterly planning, competitive landscape analysis, product vision documents, and team scaling proposals. Use when creating quarterly OKR documents, defining product goals or KPIs, building product roadmaps, running competitive analysis, drafting team structure or hiring plans, aligning product strategy across engineering and design, or generating cascaded goal hierarchies from company to team level.","tools":[{"script":"product-team/skills/product-strategist/scripts/okr_cascade_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/product-strategist/scripts/okr_cascade_generator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":["examples","okr_framework.md","strategy_types.md"]},{"name":"roadmap-communicator","path":"product-team/skills/roadmap-communicator","description":"Use when preparing roadmap narratives, release notes, changelogs, or stakeholder updates tailored for executives, engineering teams, and customers.","tools":[{"script":"product-team/skills/roadmap-communicator/scripts/changelog_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/roadmap-communicator/scripts/changelog_generator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["communication-templates.md","roadmap-templates.md"]},{"name":"saas-scaffolder","path":"product-team/skills/saas-scaffolder","description":"Generates complete, production-ready SaaS project boilerplate including authentication, database schemas, billing integration, API routes, and a working dashboard using Next.js 14+ App Router, TypeScript, Tailwind CSS, shadcn/ui, Drizzle ORM, and Stripe. Use when the user wants to create a new SaaS app, start a subscription-based web project, scaffold a Next.js application, or mentions terms like starter template, boilerplate, new project, or wiring up auth and payments.","tools":[{"script":"product-team/skills/saas-scaffolder/scripts/project_bootstrapper.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/saas-scaffolder/scripts/project_bootstrapper.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["architecture-patterns.md","auth-billing-guide.md","saas-architecture-patterns.md","tech-stack-comparison.md"]},{"name":"spec-to-repo","path":"product-team/skills/spec-to-repo","description":"Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and need a codebase', or provides a natural-language project specification and expects a complete, runnable repository. Stack-agnostic: Next.js, FastAPI, Rails, Go, Rust, Flutter, and more.","tools":[{"script":"product-team/skills/spec-to-repo/scripts/validate_project.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/spec-to-repo/scripts/validate_project.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["spec-parsing-guide.md","stack-templates.md"]},{"name":"ui-design-system","path":"product-team/skills/ui-design-system","description":"UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use when creating design systems, generating design tokens, maintaining visual consistency, or facilitating design-dev collaboration and developer handoff.","tools":[{"script":"product-team/skills/ui-design-system/scripts/design_token_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 product-team/skills/ui-design-system/scripts/design_token_generator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["component-architecture.md","developer-handoff.md","responsive-calculations.md","token-generation.md"]},{"name":"ux-researcher-designer","path":"product-team/skills/ux-researcher-designer","description":"UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs.","tools":[{"script":"product-team/skills/ux-researcher-designer/scripts/persona_generator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 product-team/skills/ux-researcher-designer/scripts/persona_generator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 product-team/skills/ux-researcher-designer/scripts/persona_generator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["example-personas.md","journey-mapping-guide.md","persona-methodology.md","usability-testing-frameworks.md"]}]},"isInternal":false,"tokens":5568,"sizeBytes":25095},{"name":"productivity.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/productivity.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/productivity.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fproductivity.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"productivity","skill_count":11,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"andreessen","path":"productivity/andreessen/skills/andreessen","description":"Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit; bias to build over deliberate. Use when the user says 'andreessen', 'pmarca mode', 'should I build this', 'is there a market', 'are we at product/market fit', 'pmf check', 'pressure-test this idea', 'be brutal about this venture', 'market-first take', or wants a no-disclaimers, no-hedging, confidence-leveled verdict …","tools":[{"script":"productivity/andreessen/skills/andreessen/scripts/anti_todo_card.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/andreessen/skills/andreessen/scripts/anti_todo_card.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/andreessen/skills/andreessen/scripts/anti_todo_card.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/andreessen/skills/andreessen/scripts/market_first_evaluator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/andreessen/skills/andreessen/scripts/market_first_evaluator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/andreessen/skills/andreessen/scripts/market_first_evaluator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/andreessen/skills/andreessen/scripts/pmf_signal_scorer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/andreessen/skills/andreessen/scripts/pmf_signal_scorer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/andreessen/skills/andreessen/scripts/pmf_signal_scorer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["market_first_canon.md","operating_prompt.md","personal_productivity_system.md","pmf_and_build_canon.md"]},{"name":"capture","path":"productivity/capture/skills/capture","description":"Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed …","tools":[{"script":"productivity/capture/skills/capture/scripts/complexity_estimator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/capture/skills/capture/scripts/complexity_estimator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/capture/skills/capture/scripts/complexity_estimator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/capture/skills/capture/scripts/dump_classifier.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/capture/skills/capture/scripts/dump_classifier.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/capture/skills/capture/scripts/dump_classifier.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/capture/skills/capture/scripts/workspace_inventory.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/capture/skills/capture/scripts/workspace_inventory.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/capture/skills/capture/scripts/workspace_inventory.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["complexity_matching.md","voice_preservation.md","workspace_detection.md"]},{"name":"deep-work","path":"productivity/deep-work/skills/deep-work","description":"Use when someone wants to plan a deep work day, time-block their calendar or task list, budget or cut shallow work, protect focus hours, track deep-work sessions and streaks, run an end-of-day shutdown ritual, or says \"/deep-work\" or \"/time-block\". Classifies tasks deep vs shallow, builds an energy-first time-blocked schedule that refuses deep demand past the 4-hour ceiling, batches shallow work into at most two windows, and logs focus sessions against a weekly target.","tools":[{"script":"productivity/deep-work/skills/deep-work/scripts/focus_session_logger.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/deep-work/skills/deep-work/scripts/focus_session_logger.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/deep-work/skills/deep-work/scripts/focus_session_logger.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/deep-work/skills/deep-work/scripts/shallow_work_auditor.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/deep-work/skills/deep-work/scripts/shallow_work_auditor.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/deep-work/skills/deep-work/scripts/shallow_work_auditor.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/deep-work/skills/deep-work/scripts/time_block_planner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/deep-work/skills/deep-work/scripts/time_block_planner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/deep-work/skills/deep-work/scripts/time_block_planner.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["deep_work_canon.md","shallow_work_budget.md","time_blocking_method.md"]},{"name":"inbox-setup","path":"productivity/email/skills/inbox-setup","description":"One-time setup skill that builds a personalized inbox triage knowledge base via interactive interview. Interviews the user about their email patterns, business context, reply style, and priorities using grill-me discipline (one question at a time, forcing format where possible, dependency-ordered, each question explains why I'm asking), then generates the knowledge base files that power the companion 'inbox-triage' skill. Run this once before using inbox-triage for the first time. Re-run when business, pricing, or priorities change significantly. Triggers: 'set up my inbox', 'configure …","tools":[{"script":"productivity/email/skills/inbox-setup/scripts/kb_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/email/skills/inbox-setup/scripts/kb_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/email/skills/inbox-setup/scripts/kb_validator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/email/skills/inbox-setup/scripts/section_progress_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 productivity/email/skills/inbox-setup/scripts/section_progress_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"productivity/email/skills/inbox-setup/scripts/voice_sample_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/email/skills/inbox-setup/scripts/voice_sample_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/email/skills/inbox-setup/scripts/voice_sample_analyzer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":true},"references":["grill_me_section_walk.md","kb_file_contract.md","voice_calibration.md"]},{"name":"inbox-triage","path":"productivity/email/skills/inbox-triage","description":"Runs a full inbox triage using the knowledge base created by the 'inbox-setup' skill. Light-intake by design (most invocations skip questions and run with KB-default preferences); asks at most 2 grill-me override questions when invocation is outside normal cadence or includes category-skip intent. Searches recent emails, classifies them via the user's taxonomy, researches new senders, generates recommendations, drafts replies (NEVER sends), delivers a report in the user's preferred format, and updates the knowledge base with learnings. Designed to run on a recurring schedule (1-3x daily) or …","tools":[{"script":"productivity/email/skills/inbox-triage/scripts/draft_safety_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/email/skills/inbox-triage/scripts/draft_safety_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/email/skills/inbox-triage/scripts/draft_safety_validator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/email/skills/inbox-triage/scripts/kb_reader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/email/skills/inbox-triage/scripts/kb_reader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/email/skills/inbox-triage/scripts/kb_reader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/email/skills/inbox-triage/scripts/search_window_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 productivity/email/skills/inbox-triage/scripts/search_window_calculator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["drafts_only_safety.md","kb_file_contract.md","triage_decision_framework.md"]},{"name":"fable-goal","path":"productivity/fable-goal/skills/fable-goal","description":"Convert a rambling description of a desired outcome into one polished, autonomous /goal prompt ready to paste into a fresh session. Use when the user says \"/fable-goal\", \"turn this into a goal prompt\", \"write me a fable prompt\", \"write the prompt that builds X\", or rambles about something they want made and asks for the prompt that makes it happen. The output is a single copy-paste prompt, never the build itself. Do NOT use when the user wants the thing built right now in this session — only when they want the PROMPT that will make it happen in a fresh session.","tools":[{"script":"productivity/fable-goal/skills/fable-goal/scripts/goal_prompt_self_check.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/fable-goal/skills/fable-goal/scripts/goal_prompt_self_check.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/fable-goal/skills/fable-goal/scripts/goal_prompt_self_check.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["goal_prompt_patterns.md"]},{"name":"handoff","path":"productivity/handoff/skills/session-handoff","description":"Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'm ending this session', 'pick this up later', or any variation signaling intent to pass work to a …","tools":[{"script":"productivity/handoff/skills/session-handoff/scripts/cleanup.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/cleanup.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/cleanup.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/handoff/skills/session-handoff/scripts/config_loader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/config_loader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/config_loader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/handoff/skills/session-handoff/scripts/handoff_self_check.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/handoff_self_check.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/handoff_self_check.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/handoff/skills/session-handoff/scripts/handoff_template_generator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/handoff_template_generator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/handoff_template_generator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/handoff/skills/session-handoff/scripts/redaction_linter.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/redaction_linter.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/redaction_linter.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/handoff/skills/session-handoff/scripts/setup.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/setup.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/setup.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/handoff/skills/session-handoff/scripts/skill_recommender.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/skill_recommender.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/handoff/skills/session-handoff/scripts/skill_recommender.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":true,"verification":true,"loop_discipline":false,"close_out":true},"references":["configuration.md","deduplication_discipline.md","handoff_prompt.md","handoff_structure.md","redaction_checklist.md"]},{"name":"meetings","path":"productivity/meetings/skills/meetings","description":"Use when someone wants to decide whether a meeting is worth calling, price a meeting in dollars, build a timeboxed agenda with desired outcomes, or turn messy meeting notes into owned action items — or says \"should this be a meeting\", \"/cs-meeting-prep\", or \"/cs-meeting-actions\". Runs a cost gate (ASYNC / NOT-READY / MEET), builds a decision-first agenda, and extracts an owner + due-date checklist that flags every orphan.","tools":[{"script":"productivity/meetings/skills/meetings/scripts/action_item_extractor.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/meetings/skills/meetings/scripts/action_item_extractor.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/meetings/skills/meetings/scripts/action_item_extractor.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/meetings/skills/meetings/scripts/agenda_builder.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/meetings/skills/meetings/scripts/agenda_builder.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/meetings/skills/meetings/scripts/agenda_builder.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/meetings/skills/meetings/scripts/meeting_cost_calculator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/meetings/skills/meetings/scripts/meeting_cost_calculator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/meetings/skills/meetings/scripts/meeting_cost_calculator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":true},"references":["action_item_discipline.md","agenda_discipline.md","meeting_cost_canon.md"]},{"name":"reflect","path":"productivity/reflect/skills/reflect","description":"Mid-conversation reflection skill that pauses execution and zooms out from detail-mode to honestly reassess direction, assumptions, and bias. Use when the user says 'reflect', 'take a step back', 'step back', 'zoom out', 'are we missing something', 'bigger picture', 'sanity check this', 'are we on track', 'are we overthinking this', 'forest for the trees', or any variation signaling intent to break out of detail-mode and reassess. Also trigger when the conversation has gone deep on implementation details without strategic check-in, or when the user shows signs of being stuck — that's often …","tools":[{"script":"productivity/reflect/skills/reflect/scripts/bias_pattern_detector.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/reflect/skills/reflect/scripts/bias_pattern_detector.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/reflect/skills/reflect/scripts/bias_pattern_detector.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/reflect/skills/reflect/scripts/conversation_depth_analyzer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/reflect/skills/reflect/scripts/conversation_depth_analyzer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/reflect/skills/reflect/scripts/conversation_depth_analyzer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/reflect/skills/reflect/scripts/directional_recommendation_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/reflect/skills/reflect/scripts/directional_recommendation_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/reflect/skills/reflect/scripts/directional_recommendation_validator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["cognitive_bias_canon.md","conversation_reflection_practice.md","honest_output_discipline.md"]},{"name":"roast","path":"productivity/roast/skills/roast","description":"Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, \"convene the panel\", get a brutal second opinion before building something, or says \"/roast\". Spins up a 5-angle panel (Critic, Champion, Analyst, Investigator, Customer) that attacks the idea from every angle, then a Judge returns one GO / RESHAPE / KILL verdict with the cheapest test to de-risk it.","tools":[{"script":"productivity/roast/skills/roast/scripts/brief_builder.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/roast/skills/roast/scripts/brief_builder.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/roast/skills/roast/scripts/brief_builder.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/roast/skills/roast/scripts/cheapest_test_designer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/roast/skills/roast/scripts/cheapest_test_designer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/roast/skills/roast/scripts/cheapest_test_designer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/roast/skills/roast/scripts/verdict_synthesizer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/roast/skills/roast/scripts/verdict_synthesizer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/roast/skills/roast/scripts/verdict_synthesizer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":false},"references":["adversarial_panel_canon.md","cheapest_test_canon.md","verdict_synthesis_method.md"]},{"name":"weekly-review","path":"productivity/weekly-review/skills/weekly-review","description":"Use when someone wants to run a weekly review, close open loops, audit stalled projects and commitments, get their system back to trusted, restart a lapsed review habit, or says \"/cs-weekly-review\". Walks David Allen's three-phase loop — GET CLEAR, GET CURRENT, GET CREATIVE — with deterministic scripts that inventory open loops, gate the checklist with named gaps, and score commitment health 0-100.","tools":[{"script":"productivity/weekly-review/skills/weekly-review/scripts/commitment_auditor.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/weekly-review/skills/weekly-review/scripts/commitment_auditor.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/weekly-review/skills/weekly-review/scripts/commitment_auditor.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/weekly-review/skills/weekly-review/scripts/open_loop_scanner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/weekly-review/skills/weekly-review/scripts/open_loop_scanner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/weekly-review/skills/weekly-review/scripts/open_loop_scanner.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"productivity/weekly-review/skills/weekly-review/scripts/weekly_review_gate.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 productivity/weekly-review/skills/weekly-review/scripts/weekly_review_gate.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 productivity/weekly-review/skills/weekly-review/scripts/weekly_review_gate.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":true},"references":["gtd_weekly_review_canon.md","open_loop_psychology.md","review_cadence_design.md"]}]},"isInternal":false,"tokens":7344,"sizeBytes":32656},{"name":"project-management.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/project-management.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/project-management.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fproject-management.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"project-management","skill_count":9,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"atlassian-admin","path":"project-management/skills/atlassian-admin","description":"Atlassian Administrator for managing and organizing Atlassian products (Jira, Confluence, Bitbucket, Trello), users, permissions, security, integrations, system configuration, and org-wide governance. Use when asked to add users to Jira, change Confluence permissions, configure access control, update admin settings, manage Atlassian groups, set up SSO, install marketplace apps, review security policies, or handle any org-wide Atlassian administration task.","tools":[{"script":"project-management/skills/atlassian-admin/scripts/permission_audit_tool.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/atlassian-admin/scripts/permission_audit_tool.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["security-hardening-guide.md","user-provisioning-checklist.md"]},{"name":"atlassian-templates","path":"project-management/skills/atlassian-templates","description":"Atlassian Template and Files Creator/Modifier expert for creating, modifying, and managing Jira and Confluence templates, blueprints, custom layouts, reusable components, and standardized content structures. Use when building org-wide templates, custom blueprints, page layouts, and automated content generation.","tools":[{"script":"project-management/skills/atlassian-templates/scripts/template_scaffolder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/atlassian-templates/scripts/template_scaffolder.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["governance-framework.md","template-design-patterns.md"]},{"name":"confluence-expert","path":"project-management/skills/confluence-expert","description":"Atlassian Confluence expert for creating and managing spaces, knowledge bases, and documentation. Configures space permissions and hierarchies, creates page templates with macros, sets up documentation taxonomies, designs page layouts, and manages content governance. Use when users need to build or restructure a Confluence space, design page hierarchies with permission structures, author or standardise documentation templates, embed Jira reports in pages, run knowledge base audits, or establish documentation standards and collaborative workflows.","tools":[{"script":"project-management/skills/confluence-expert/scripts/content_audit_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/confluence-expert/scripts/content_audit_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"project-management/skills/confluence-expert/scripts/space_structure_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/confluence-expert/scripts/space_structure_generator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["macro-cheat-sheet.md","space-architecture-patterns.md","templates.md"]},{"name":"jira-expert","path":"project-management/skills/jira-expert","description":"Atlassian Jira expert for creating and managing projects, planning, product discovery, JQL queries, workflows, custom fields, automation, reporting, and all Jira features. Use when setting up or configuring Jira projects, writing JQL and advanced searches, creating dashboards, designing workflows, or performing technical Jira operations.","tools":[{"script":"project-management/skills/jira-expert/scripts/jql_query_builder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/jira-expert/scripts/jql_query_builder.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"project-management/skills/jira-expert/scripts/workflow_validator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/jira-expert/scripts/workflow_validator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["AUTOMATION.md","WORKFLOWS.md","automation-examples.md","jql-examples.md"]},{"name":"meeting-analyzer","path":"project-management/skills/meeting-analyzer","description":"Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this skill whenever the user uploads or points to meeting transcripts (.txt, .md, .vtt, .srt, .docx), asks about their communication habits, wants feedback on how they run meetings, requests speaking ratio analysis, mentions filler words or conflict avoidance, or wants to compare their communication across time periods. Also trigger when users mention tools like Granola, Otter, Fireflies, or Zoom transcripts. Even if the user just says \"look at my …","tools":[],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":[]},{"name":"pm-skills","path":"project-management/skills/pm-skills","description":"Use when coordinating project-delivery work across the 8 project-management sub-skills — sprint/velocity analytics, portfolio health, Jira/JQL, Confluence, Atlassian admin, templates, meeting analysis, team comms. Triggers on 'our sprints feel off', 'project health report', 'audit our Jira permissions', 'when will it be done', 'run the delivery loop'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a full goal→plan→execute→verify→close delivery loop through the repo-wide agent-harness with Jira MCP data bridged into the domain's …","tools":[{"script":"project-management/skills/pm-skills/scripts/delivery_loop_gate.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 project-management/skills/pm-skills/scripts/delivery_loop_gate.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 project-management/skills/pm-skills/scripts/delivery_loop_gate.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"project-management/skills/pm-skills/scripts/jira_snapshot_bridge.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 project-management/skills/pm-skills/scripts/jira_snapshot_bridge.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 project-management/skills/pm-skills/scripts/jira_snapshot_bridge.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"project-management/skills/pm-skills/scripts/pm_goal_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 project-management/skills/pm-skills/scripts/pm_goal_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 project-management/skills/pm-skills/scripts/pm_goal_router.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":true},"references":["agentic_delivery_governance.md","flow_forecasting_canon.md","pm_loop_playbook.md"]},{"name":"scrum-master","path":"project-management/skills/scrum-master","description":"Advanced Scrum Master skill for data-driven agile team analysis and coaching. Use when the user asks about sprint planning, velocity tracking, retrospectives, standup facilitation, backlog grooming, story points, burndown charts, blocker resolution, or agile team health. Runs Python scripts to analyse sprint JSON exports from Jira or similar tools: velocity_analyzer.py for Monte Carlo sprint forecasting, sprint_health_scorer.py for multi-dimension health scoring, and retrospective_analyzer.py for action-item and theme tracking. Produces confidence-interval forecasts, health grade reports …","tools":[{"script":"project-management/skills/scrum-master/scripts/retrospective_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/scrum-master/scripts/retrospective_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"project-management/skills/scrum-master/scripts/sprint_health_scorer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/scrum-master/scripts/sprint_health_scorer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"project-management/skills/scrum-master/scripts/velocity_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/scrum-master/scripts/velocity_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":true},"references":["retro-formats.md","team-dynamics-framework.md","velocity-forecasting-guide.md"]},{"name":"senior-pm","path":"project-management/skills/senior-pm","description":"Senior Project Manager for enterprise software, SaaS, and digital transformation projects. Specializes in portfolio management, quantitative risk analysis, resource optimization, stakeholder alignment, and executive reporting. Uses advanced methodologies including EMV analysis, Monte Carlo simulation, WSJF prioritization, and multi-dimensional health scoring. Use when a user needs help with project plans, project status reports, risk assessments, resource allocation, project roadmaps, milestone tracking, team capacity planning, portfolio health reviews, program management, or …","tools":[{"script":"project-management/skills/senior-pm/scripts/project_health_dashboard.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/senior-pm/scripts/project_health_dashboard.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"project-management/skills/senior-pm/scripts/resource_capacity_planner.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/senior-pm/scripts/resource_capacity_planner.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"project-management/skills/senior-pm/scripts/risk_matrix_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 project-management/skills/senior-pm/scripts/risk_matrix_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":true},"references":["portfolio-kpis.md","portfolio-prioritization-models.md","risk-management-framework.md"]},{"name":"team-communications","path":"project-management/skills/team-communications","description":"Write internal company communications — 3P updates (Progress/Plans/Problems), company-wide newsletters, FAQ roundups, incident reports, leadership updates, status reports, project updates, and general internal comms. Use this skill any time the user asks to draft, edit, or format something meant for internal audiences. Trigger on keywords like \"3P\", \"weekly update\", \"newsletter\", \"FAQ\", \"internal comms\", \"status report\", \"company update\", \"team update\", \"incident report\", or any request to summarize work for leadership, teammates, or the broader company. Even casual requests like \"write my …","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":false,"close_out":false},"references":["3p-updates.md","company-newsletter.md","faq-answers.md","general-comms.md"]}]},"isInternal":false,"tokens":3515,"sizeBytes":16027},{"name":"ra-qm-team.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/ra-qm-team.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/ra-qm-team.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fra-qm-team.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"ra-qm-team","skill_count":19,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"eu-ai-act-specialist","path":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and …","tools":[{"script":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/scripts/ai_act_obligation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/scripts/ai_act_obligation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/scripts/ai_system_risk_classifier.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/scripts/ai_system_risk_classifier.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/scripts/conformity_assessment_planner.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/scripts/conformity_assessment_planner.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["cross_framework_mapping_ai_act.md","eu_ai_act_titles.md","gpai_obligations.md","high_risk_systems_annex_iii.md"]},{"name":"iso42001-specialist","path":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist","description":"ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see …","tools":[{"script":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/scripts/ai_risk_register_builder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/scripts/ai_risk_register_builder.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/scripts/aims_audit_scheduler.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/scripts/aims_audit_scheduler.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/scripts/aims_gap_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/scripts/aims_gap_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["aims_controls_annex_a.md","aims_implementation_guide.md","cross_framework_mapping_ai.md","iso42001_clauses.md"]},{"name":"agent-decision-receipts","path":"ra-qm-team/skills/agent-decision-receipts","description":"Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion.","tools":[{"script":"ra-qm-team/skills/agent-decision-receipts/scripts/build_action_manifest.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/agent-decision-receipts/scripts/build_action_manifest.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":true,"verification":true,"loop_discipline":false,"close_out":false},"references":["receipt-fields.md"]},{"name":"capa-officer","path":"ra-qm-team/skills/capa-officer","description":"CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use when running CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.","tools":[{"script":"ra-qm-team/skills/capa-officer/scripts/capa_tracker.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 ra-qm-team/skills/capa-officer/scripts/capa_tracker.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 ra-qm-team/skills/capa-officer/scripts/capa_tracker.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"ra-qm-team/skills/capa-officer/scripts/root_cause_analyzer.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/capa-officer/scripts/root_cause_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["effectiveness-verification-guide.md","rca-methodologies.md"]},{"name":"eu-ai-act-specialist","path":"ra-qm-team/skills/eu-ai-act-specialist","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and …","tools":[{"script":"ra-qm-team/skills/eu-ai-act-specialist/scripts/ai_act_obligation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/eu-ai-act-specialist/scripts/ai_act_obligation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/eu-ai-act-specialist/scripts/ai_system_risk_classifier.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/eu-ai-act-specialist/scripts/ai_system_risk_classifier.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/eu-ai-act-specialist/scripts/conformity_assessment_planner.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/eu-ai-act-specialist/scripts/conformity_assessment_planner.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["cross_framework_mapping_ai_act.md","eu_ai_act_titles.md","gpai_obligations.md","high_risk_systems_annex_iii.md"]},{"name":"fda-consultant-specialist","path":"ra-qm-team/skills/fda-consultant-specialist","description":"FDA regulatory consultant for medical device companies. Provides 510(k)/PMA/De Novo pathway guidance, QMSR (21 CFR 820, which incorporates ISO 13485:2016 by reference since 2026-02-02; formerly QSR) compliance, HIPAA assessments, and device cybersecurity. Use when user mentions FDA submission, 510(k), PMA, De Novo, QMSR, QSR, ISO 13485 for FDA, premarket, predicate device, substantial equivalence, HIPAA medical device, or FDA cybersecurity.","tools":[{"script":"ra-qm-team/skills/fda-consultant-specialist/scripts/fda_submission_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/fda-consultant-specialist/scripts/fda_submission_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/fda-consultant-specialist/scripts/hipaa_risk_assessment.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/fda-consultant-specialist/scripts/hipaa_risk_assessment.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/fda-consultant-specialist/scripts/qsr_compliance_checker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/fda-consultant-specialist/scripts/qsr_compliance_checker.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["device_cybersecurity_guidance.md","fda_capa_requirements.md","fda_submission_guide.md","hipaa_compliance_framework.md","qsr_compliance_requirements.md"]},{"name":"gdpr-dsgvo-expert","path":"ra-qm-team/skills/gdpr-dsgvo-expert","description":"GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests with Art. 12(3) one-month deadlines. Use when running GDPR compliance assessments, privacy audits, data protection planning, DPIA generation, or data subject rights (DSAR) management (e.g., 'check this service for GDPR risks', 'track an access request deadline'). Final compliance determinations route to the DPO or legal counsel.","tools":[{"script":"ra-qm-team/skills/gdpr-dsgvo-expert/scripts/data_subject_rights_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/gdpr-dsgvo-expert/scripts/data_subject_rights_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/gdpr-dsgvo-expert/scripts/dpia_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/gdpr-dsgvo-expert/scripts/dpia_generator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/gdpr-dsgvo-expert/scripts/gdpr_compliance_checker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/gdpr-dsgvo-expert/scripts/gdpr_compliance_checker.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["dpia_methodology.md","gdpr_audit_playbook.md","gdpr_compliance_guide.md","german_bdsg_requirements.md"]},{"name":"information-security-manager-iso27001","path":"ra-qm-team/skills/information-security-manager-iso27001","description":"ISO 27001 ISMS implementation and cybersecurity governance for HealthTech and MedTech companies. Use when designing an ISMS, running security risk assessments, implementing controls, pursuing ISO 27001 certification, preparing security audits, responding to security incidents, or verifying compliance. Covers ISO 27001, ISO 27002, healthcare security, and medical device cybersecurity.","tools":[{"script":"ra-qm-team/skills/information-security-manager-iso27001/scripts/compliance_checker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/information-security-manager-iso27001/scripts/compliance_checker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/information-security-manager-iso27001/scripts/risk_assessment.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/information-security-manager-iso27001/scripts/risk_assessment.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["incident-response.md","iso27001-controls.md","risk-assessment-guide.md"]},{"name":"isms-audit-expert","path":"ra-qm-team/skills/isms-audit-expert","description":"Information Security Management System (ISMS) audit expert for ISO 27001 compliance verification, security control assessment, and certification support. Use when the user mentions ISO 27001, ISMS audit, Annex A controls, Statement of Applicability (SOA), gap analysis, nonconformity management, internal audit, surveillance audit, or security certification preparation. Helps review control implementation evidence, document audit findings, classify nonconformities, generate risk-based audit plans, map controls to Annex A requirements, prepare Stage 1 and Stage 2 audit documentation, and …","tools":[{"script":"ra-qm-team/skills/isms-audit-expert/scripts/isms_audit_scheduler.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/isms-audit-expert/scripts/isms_audit_scheduler.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["cloud-security-audit.md","iso27001-audit-methodology.md","iso27001_audit_playbook.md","security-control-testing.md"]},{"name":"iso42001-specialist","path":"ra-qm-team/skills/iso42001-specialist","description":"ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see …","tools":[{"script":"ra-qm-team/skills/iso42001-specialist/scripts/ai_risk_register_builder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/iso42001-specialist/scripts/ai_risk_register_builder.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/iso42001-specialist/scripts/aims_audit_scheduler.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/iso42001-specialist/scripts/aims_audit_scheduler.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/iso42001-specialist/scripts/aims_gap_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/iso42001-specialist/scripts/aims_gap_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["aims_controls_annex_a.md","aims_implementation_guide.md","cross_framework_mapping_ai.md","iso42001_clauses.md"]},{"name":"mdr-745-specialist","path":"ra-qm-team/skills/mdr-745-specialist","description":"EU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Covers Annex VIII classification rules, Annex II/III technical files, Annex XIV clinical evaluation, Art. 86 PSUR schedules, and EUDAMED integration. Use when classifying a medical device under MDR, building or gap-checking a technical file, planning clinical evaluation or PMS/PSUR cadence, or preparing for notified body review (e.g., 'what class is my device under MDR', 'review my PSUR schedule').","tools":[{"script":"ra-qm-team/skills/mdr-745-specialist/scripts/mdr_gap_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/mdr-745-specialist/scripts/mdr_gap_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["clinical-evidence-requirements.md","mdr-classification-guide.md","technical-documentation-templates.md"]},{"name":"qms-audit-expert","path":"ra-qm-team/skills/qms-audit-expert","description":"ISO 13485 internal audit expertise for medical device QMS. Covers audit planning, execution, nonconformity classification, and CAPA verification. Use when planning internal audits, executing audits, classifying findings, preparing for external audits, or managing an audit program.","tools":[{"script":"ra-qm-team/skills/qms-audit-expert/scripts/audit_schedule_optimizer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/qms-audit-expert/scripts/audit_schedule_optimizer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["iso13485-audit-guide.md","iso13485_audit_playbook.md","nonconformity-classification.md"]},{"name":"quality-documentation-manager","path":"ra-qm-team/skills/quality-documentation-manager","description":"Document control system management for medical device QMS. Covers document numbering, version control, change management, and 21 CFR Part 11 compliance. Use when working on document control procedures, change control workflows, document numbering, version management, electronic signature compliance, or regulatory documentation review.","tools":[{"script":"ra-qm-team/skills/quality-documentation-manager/scripts/document_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 ra-qm-team/skills/quality-documentation-manager/scripts/document_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 ra-qm-team/skills/quality-documentation-manager/scripts/document_validator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"ra-qm-team/skills/quality-documentation-manager/scripts/document_version_control.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/quality-documentation-manager/scripts/document_version_control.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["21cfr11-compliance-guide.md","document-control-procedures.md"]},{"name":"quality-manager-qmr","path":"ra-qm-team/skills/quality-manager-qmr","description":"Senior Quality Manager Responsible Person (QMR) for HealthTech and MedTech companies. Provides quality system governance, management review leadership, regulatory compliance oversight, and quality performance monitoring per ISO 13485 Clause 5.5.2. Use when leading management reviews, setting quality policy and objectives, monitoring quality KPIs and cost of quality, or exercising QMR governance and regulatory oversight responsibilities.","tools":[{"script":"ra-qm-team/skills/quality-manager-qmr/scripts/management_review_tracker.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 ra-qm-team/skills/quality-manager-qmr/scripts/management_review_tracker.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 ra-qm-team/skills/quality-manager-qmr/scripts/management_review_tracker.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"ra-qm-team/skills/quality-manager-qmr/scripts/quality_effectiveness_monitor.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/quality-manager-qmr/scripts/quality_effectiveness_monitor.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["management-review-guide.md","quality-kpi-framework.md"]},{"name":"quality-manager-qms-iso13485","path":"ra-qm-team/skills/quality-manager-qms-iso13485","description":"ISO 13485 Quality Management System implementation and maintenance for medical device organizations. Provides QMS design, documentation control, internal auditing, CAPA management, and certification support. Use when working with medical device quality systems, preparing for ISO 13485 audits, managing regulatory compliance documentation, setting up corrective actions, or building audit preparation programs. Useful for quality management, audit preparation, regulatory compliance, medical device documentation, and corrective action workflows.","tools":[{"script":"ra-qm-team/skills/quality-manager-qms-iso13485/scripts/qms_audit_checklist.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/quality-manager-qms-iso13485/scripts/qms_audit_checklist.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["iso13485-clause-requirements.md","qms-process-templates.md"]},{"name":"ra-qm-skills","path":"ra-qm-team/skills/ra-qm-skills","description":"Router/index for the 15 regulatory & quality-management skills bundled in this plugin (ISO 13485 QMS, EU MDR 2017/745, FDA submissions under QMSR, ISO 14971 risk, CAPA, document control, ISO 27001/ISMS, ISO 42001 AIMS, EU AI Act, GDPR/DSGVO, SOC 2, auditing). Use when a compliance request doesn't obviously match one skill and you need to pick the right one (e.g., 'prepare us for an ISO 13485 audit', 'is my AI system high-risk under the AI Act').","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":[]},{"name":"regulatory-affairs-head","path":"ra-qm-team/skills/regulatory-affairs-head","description":"Senior Regulatory Affairs Manager for HealthTech and MedTech companies. Prepares FDA 510(k), De Novo, and PMA submission packages; analyzes regulatory pathways for new medical devices; drafts responses to FDA deficiency letters and Notified Body queries; develops CE marking technical documentation under EU MDR 2017/745; coordinates multi-market approval strategies across FDA, EU, Health Canada, PMDA, and NMPA; and maintains regulatory intelligence on evolving standards. Use when users need to plan or execute FDA submissions, navigate 510(k) or PMA approval processes, achieve CE marking …","tools":[{"script":"ra-qm-team/skills/regulatory-affairs-head/scripts/regulatory_pathway_analyzer.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/regulatory-affairs-head/scripts/regulatory_pathway_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/regulatory-affairs-head/scripts/regulatory_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/regulatory-affairs-head/scripts/regulatory_tracker.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":true},"references":["eu-mdr-submission-guide.md","fda-submission-guide.md","global-regulatory-pathways.md","iso-regulatory-requirements.md"]},{"name":"risk-management-specialist","path":"ra-qm-team/skills/risk-management-specialist","description":"Medical device risk management specialist implementing ISO 14971 throughout product lifecycle. Provides risk analysis, risk evaluation, risk control, and post-production information analysis. Use when user mentions risk management, ISO 14971, risk analysis, FMEA, fault tree analysis, hazard identification, risk control, risk matrix, benefit-risk analysis, residual risk, risk acceptability, or post-market risk.","tools":[{"script":"ra-qm-team/skills/risk-management-specialist/scripts/fmea_analyzer.py","wired":false,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/risk-management-specialist/scripts/fmea_analyzer.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/risk-management-specialist/scripts/risk_matrix_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/risk-management-specialist/scripts/risk_matrix_calculator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["iso14971-implementation-guide.md","risk-analysis-methods.md","risk-assessment-templates.md"]},{"name":"soc2-compliance","path":"ra-qm-team/skills/soc2-compliance","description":"Use when the user asks to prepare for SOC 2 audits, map Trust Service Criteria, build control matrices, collect audit evidence, perform gap analysis, or assess SOC 2 Type I vs Type II readiness.","tools":[{"script":"ra-qm-team/skills/soc2-compliance/scripts/control_matrix_builder.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/soc2-compliance/scripts/control_matrix_builder.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/soc2-compliance/scripts/evidence_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/soc2-compliance/scripts/evidence_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"ra-qm-team/skills/soc2-compliance/scripts/gap_analyzer.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 ra-qm-team/skills/soc2-compliance/scripts/gap_analyzer.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":true},"references":["evidence_collection_guide.md","soc2_audit_playbook.md","trust_service_criteria.md","type1_vs_type2.md"]}]},"isInternal":false,"tokens":8460,"sizeBytes":35588},{"name":"research-ops.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/research-ops.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/research-ops.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fresearch-ops.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"research-ops","skill_count":5,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"clinical-research","path":"research-ops/skills/clinical-research","description":"Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission …","tools":[{"script":"research-ops/skills/clinical-research/scripts/ar_evaluator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/clinical-research/scripts/ar_evaluator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/clinical-research/scripts/ar_evaluator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/clinical-research/scripts/config_loader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/clinical-research/scripts/config_loader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/clinical-research/scripts/config_loader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/clinical-research/scripts/endpoint_selector.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/clinical-research/scripts/endpoint_selector.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/clinical-research/scripts/endpoint_selector.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/clinical-research/scripts/onboard.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research-ops/skills/clinical-research/scripts/onboard.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research-ops/skills/clinical-research/scripts/phase_gate_scorer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/clinical-research/scripts/phase_gate_scorer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/clinical-research/scripts/phase_gate_scorer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/clinical-research/scripts/sample_size_estimator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/clinical-research/scripts/sample_size_estimator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/clinical-research/scripts/sample_size_estimator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["endpoint_and_power.md","study_design_canon.md","trial_operations.md"]},{"name":"market-research","path":"research-ops/skills/market-research","description":"Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number), planning a survey sample size with finite-population correction and per-segment minimums, or scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria. Outputs always show the method and the assumptions. For market-research analysts and product-marketing at the sizing/survey/segmentation moment. Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — …","tools":[{"script":"research-ops/skills/market-research/scripts/ar_evaluator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/market-research/scripts/ar_evaluator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/market-research/scripts/ar_evaluator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/market-research/scripts/config_loader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/market-research/scripts/config_loader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/market-research/scripts/config_loader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/market-research/scripts/market_sizer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/market-research/scripts/market_sizer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/market-research/scripts/market_sizer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/market-research/scripts/onboard.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research-ops/skills/market-research/scripts/onboard.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research-ops/skills/market-research/scripts/sample_size_planner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/market-research/scripts/sample_size_planner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/market-research/scripts/sample_size_planner.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/market-research/scripts/segmentation_scorer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/market-research/scripts/segmentation_scorer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/market-research/scripts/segmentation_scorer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["market_sizing_canon.md","segmentation_and_ci.md","survey_methodology.md"]},{"name":"product-research","path":"research-ops/skills/product-research","description":"Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint …","tools":[{"script":"research-ops/skills/product-research/scripts/ar_evaluator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/product-research/scripts/ar_evaluator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/product-research/scripts/ar_evaluator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/product-research/scripts/config_loader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/product-research/scripts/config_loader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/product-research/scripts/config_loader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/product-research/scripts/insight_synthesizer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/product-research/scripts/insight_synthesizer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/product-research/scripts/insight_synthesizer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/product-research/scripts/onboard.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research-ops/skills/product-research/scripts/onboard.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research-ops/skills/product-research/scripts/saturation_planner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/product-research/scripts/saturation_planner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/product-research/scripts/saturation_planner.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/product-research/scripts/study_designer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/product-research/scripts/study_designer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/product-research/scripts/study_designer.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["repository_and_synthesis.md","research_methods_canon.md","sampling_and_saturation.md"]},{"name":"research-finance","path":"research-ops/skills/research-finance","description":"Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this …","tools":[{"script":"research-ops/skills/research-finance/scripts/ar_evaluator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/research-finance/scripts/ar_evaluator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/research-finance/scripts/ar_evaluator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/research-finance/scripts/burn_runway_tracker.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/research-finance/scripts/burn_runway_tracker.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/research-finance/scripts/burn_runway_tracker.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/research-finance/scripts/capex_vs_opex_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/research-finance/scripts/capex_vs_opex_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/research-finance/scripts/capex_vs_opex_router.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/research-finance/scripts/config_loader.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/research-finance/scripts/config_loader.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/research-finance/scripts/config_loader.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research-ops/skills/research-finance/scripts/onboard.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research-ops/skills/research-finance/scripts/onboard.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research-ops/skills/research-finance/scripts/program_budget_planner.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research-ops/skills/research-finance/scripts/program_budget_planner.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research-ops/skills/research-finance/scripts/program_budget_planner.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":true,"loop_discipline":true,"close_out":false},"references":["burn_and_portfolio.md","indirect_rate_modeling.md","rd_program_finance_canon.md"]},{"name":"research-ops-skills","path":"research-ops/skills/research-ops-skills","description":"Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on \"design this clinical study\", \"what sample size\", \"R&D budget\", \"burn rate\", \"capitalize or expense\", \"TAM SAM SOM\", \"market sizing\", \"survey design\", \"segment the market\", \"plan user interviews\", \"usability test\", \"synthesize research insights\". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and …","tools":[],"agentic_signals":{"goal_intake":true,"refusal_gate":false,"verification":false,"loop_discipline":true,"close_out":true},"references":[]}]},"isInternal":false,"tokens":4336,"sizeBytes":19227},{"name":"research.json","path":"engineering/agent-harness/skills/agent-harness/assets/harnesses/research.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/assets/harnesses/research.json","title":"Harnesses Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Fassets%2Fharnesses%2Fresearch.json -->","frontmatter":{"schema":"agent-harness/manifest.v1","domain":"research","skill_count":9,"loop_defaults":{"max_attempts_per_task":3,"max_loop_iterations":12,"escalate_on":["attempts_exhausted","no_verification_available","destructive_or_irreversible_action","goal_drift_detected"]},"skills":[{"name":"deep-research","path":"research/deep-research/skills/deep-research","description":"Run a disciplined, multi-source research investigation for a high-stakes question or decision — fan-out web search across many channels, parallel sub-agents, source triangulation (each claim backed by ≥3 independent sources), an adversarial review pass, and every source saved to its own file with verbatim quotes for reuse. Use when a low-quality answer is expensive: strategy work, comparing N products/methods/markets, validating a hypothesis with external data, or mapping how a field works. NOT for quick fact-checks (answer directly), structured 12-dimension competitor scoring (use …","tools":[],"agentic_signals":{"goal_intake":false,"refusal_gate":false,"verification":true,"loop_discipline":false,"close_out":false},"references":["full-catalog.md"]},{"name":"dossier","path":"research/dossier/skills/dossier","description":"Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch …","tools":[{"script":"research/dossier/skills/dossier/scripts/citation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/dossier/skills/dossier/scripts/citation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/dossier/skills/dossier/scripts/disconfirming_evidence_balance.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/dossier/skills/dossier/scripts/disconfirming_evidence_balance.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/dossier/skills/dossier/scripts/disconfirming_evidence_balance.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/dossier/skills/dossier/scripts/source_tier_classifier.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/dossier/skills/dossier/scripts/source_tier_classifier.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/dossier/skills/dossier/scripts/source_tier_classifier.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["conversation_hook_quality.md","hypothesis_testing_discipline.md","subject_type_source_matrix.md"]},{"name":"grants","path":"research/grants/skills/grants","description":"NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer …","tools":[{"script":"research/grants/skills/grants/scripts/citation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/grants/skills/grants/scripts/citation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/grants/skills/grants/scripts/fiscal_year_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/grants/skills/grants/scripts/fiscal_year_calculator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/grants/skills/grants/scripts/mechanism_matcher.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/grants/skills/grants/scripts/mechanism_matcher.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/grants/skills/grants/scripts/mechanism_matcher.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["docx_9_sections.md","nih_mechanism_matching.md","reporter_post_patterns.md"]},{"name":"litreview","path":"research/litreview/skills/litreview","description":"Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. …","tools":[{"script":"research/litreview/skills/litreview/scripts/citation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/litreview/skills/litreview/scripts/citation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/litreview/skills/litreview/scripts/cross_search_aggregator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/litreview/skills/litreview/scripts/cross_search_aggregator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/litreview/skills/litreview/scripts/cross_search_aggregator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/litreview/skills/litreview/scripts/framework_recommender.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/litreview/skills/litreview/scripts/framework_recommender.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/litreview/skills/litreview/scripts/framework_recommender.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/litreview/skills/litreview/scripts/free_search.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/litreview/skills/litreview/scripts/free_search.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["docx_8_sections.md","framework_selection.md","search_budget_allocation.md"]},{"name":"notebooklm","path":"research/notebooklm/skills/notebooklm","description":"Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live …","tools":[{"script":"research/notebooklm/skills/notebooklm/scripts/action_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/notebooklm/skills/notebooklm/scripts/action_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/notebooklm/skills/notebooklm/scripts/action_router.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/notebooklm/skills/notebooklm/scripts/async_action_classifier.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/notebooklm/skills/notebooklm/scripts/async_action_classifier.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/notebooklm/skills/notebooklm/scripts/async_action_classifier.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/notebooklm/skills/notebooklm/scripts/custom_prompt_template_generator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/notebooklm/skills/notebooklm/scripts/custom_prompt_template_generator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/notebooklm/skills/notebooklm/scripts/custom_prompt_template_generator.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":true},"references":["async_action_discipline.md","browser_automation_canon.md","studio_output_custom_prompts.md"]},{"name":"patent","path":"research/patent/skills/patent","description":"Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full …","tools":[{"script":"research/patent/skills/patent/scripts/citation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/patent/skills/patent/scripts/citation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/patent/skills/patent/scripts/family_resolver.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/patent/skills/patent/scripts/family_resolver.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/patent/skills/patent/scripts/family_resolver.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/patent/skills/patent/scripts/sub_use_case_router.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/patent/skills/patent/scripts/sub_use_case_router.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/patent/skills/patent/scripts/sub_use_case_router.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":true,"loop_discipline":true,"close_out":false},"references":["cpc_classification_canon.md","legal_disclaimer_discipline.md","sub_use_case_routing.md"]},{"name":"pulse","path":"research/pulse/skills/pulse","description":"Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people …","tools":[{"script":"research/pulse/skills/pulse/scripts/citation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/pulse/skills/pulse/scripts/citation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/pulse/skills/pulse/scripts/time_window_calculator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/pulse/skills/pulse/scripts/time_window_calculator.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/pulse/skills/pulse/scripts/topic_slug_generator.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/pulse/skills/pulse/scripts/topic_slug_generator.py --help","expect_exit":0,"kind":"smoke"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["cross_platform_synthesis.md","parallel_execution_discipline.md","research_pack_conventions.md"]},{"name":"research","path":"research/research/skills/research","description":"Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Use when the user makes any research request that doesn't obviously match a …","tools":[{"script":"research/research/skills/research/scripts/classifier.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/research/skills/research/scripts/classifier.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/research/skills/research/scripts/classifier.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/research/skills/research/scripts/fallback_decomposer.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/research/skills/research/scripts/fallback_decomposer.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/research/skills/research/scripts/fallback_decomposer.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/research/skills/research/scripts/routing_transparency_logger.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/research/skills/research/scripts/routing_transparency_logger.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/research/skills/research/scripts/routing_transparency_logger.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":true},"references":["deterministic_classification_canon.md","fallback_workflow_canon.md","hybrid_router_architecture.md"]},{"name":"syllabus","path":"research/syllabus/skills/syllabus","description":"Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order …","tools":[{"script":"research/syllabus/skills/syllabus/scripts/citation_tracker.py","wired":true,"supports_sample":false,"verification":[{"cmd":"python3 research/syllabus/skills/syllabus/scripts/citation_tracker.py --help","expect_exit":0,"kind":"smoke"}]},{"script":"research/syllabus/skills/syllabus/scripts/discussion_question_validator.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/syllabus/skills/syllabus/scripts/discussion_question_validator.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/syllabus/skills/syllabus/scripts/discussion_question_validator.py --sample","expect_exit":0,"kind":"sample"}]},{"script":"research/syllabus/skills/syllabus/scripts/topic_grouper.py","wired":true,"supports_sample":true,"verification":[{"cmd":"python3 research/syllabus/skills/syllabus/scripts/topic_grouper.py --help","expect_exit":0,"kind":"smoke"},{"cmd":"python3 research/syllabus/skills/syllabus/scripts/topic_grouper.py --sample","expect_exit":0,"kind":"sample"}]}],"agentic_signals":{"goal_intake":true,"refusal_gate":true,"verification":false,"loop_discipline":true,"close_out":false},"references":["applied_domain_weaving.md","audience_calibration.md","bundled_script_pattern.md"]}]},"isInternal":false,"tokens":5135,"sizeBytes":22981},{"name":"agentic_loop_canon.md","path":"engineering/agent-harness/skills/agent-harness/references/agentic_loop_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/references/agentic_loop_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Freferences%2Fagentic_loop_canon.md -->","isInternal":false,"tokens":1392,"sizeBytes":6206},{"name":"domain_harness_design.md","path":"engineering/agent-harness/skills/agent-harness/references/domain_harness_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/references/domain_harness_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Freferences%2Fdomain_harness_design.md -->","isInternal":false,"tokens":1577,"sizeBytes":6606},{"name":"verification_discipline.md","path":"engineering/agent-harness/skills/agent-harness/references/verification_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/references/verification_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2Freferences%2Fverification_discipline.md -->","isInternal":false,"tokens":1491,"sizeBytes":6321},{"name":"SKILL.md","path":"engineering/agent-harness/skills/agent-harness/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/skills/agent-harness/SKILL.md","title":"agent-harness","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2Fskills%2Fagent-harness%2FSKILL.md -->","frontmatter":{"name":"agent-harness","description":"Turn any domain folder of skills into a bounded agentic loop: compile a goal into a verifiable task plan, execute tasks with the domain's own tools, verify every task with machine-run checks, retry with caps, escalate to a human when budgets exhaust, and refuse to close until everything is verified or explicitly waived. Use when you want an agent or subagent to pick up a goal and drive it to a verified close across one of this repo's 18 domains ('run this goal through the engineering harness', 'set up an agentic loop for marketing work', 'make the finance domain self-verifying'). NOT for authoring Claude Code Workflow-tool .js scripts (workflow-builder), N-agent tournaments on one task (agenthub), single-file metric optimization (autoresearch-agent), or discovering published loop recipes (loop-library)."},"isInternal":false,"tokens":1897,"sizeBytes":8045},{"name":"memory_schema.json","path":"engineering/agent-memory/skills/agent-memory/assets/memory_schema.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-memory/skills/agent-memory/assets/memory_schema.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-memory%2Fskills%2Fagent-memory%2Fassets%2Fmemory_schema.json -->","frontmatter":{"$schema":"https://json-schema.org/draft/2020-12/schema","$id":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/main/engineering/agent-memory/skills/agent-memory/assets/memory_schema.json","$comment":"$id decision, settled — do not re-litigate. (a) raw.githubusercontent, NOT the github.com/blob/ form used by the repo's one other schema: blob URLs serve HTML, so anything that dereferences $id for $ref breaks. That other file is a pre-existing inconsistency, not a convention to propagate. (b) Pinned to main, not dev, because $id is a stable identifier for the published artifact; under this repo's dev -> main promotion flow it is a dead link until the promotion PR lands, which is accepted deliberately — a URL that is correct-eventually beats one that is correct-now and wrong-after-promotion. Nothing in this repo dereferences $id today.","title":"agent-memory atom (L1) — v1","description":"One atomic memory claim extracted from an L0 transcript. Every atom MUST carry a live back-pointer into the transcript that produced it; an atom without provenance is discarded, never stored. Promotion to L2/L3 is decided by recurrence across distinct sessions, not by importance. See ../DESIGN.md sections 3 and 4.","type":"object","additionalProperties":false,"required":["id","claim","scope","kind","first_seen","last_seen","observations","sessions","source","first_source","confidence","tier","redacted"],"properties":{"id":{"type":"string","pattern":"^atm_[0-9a-f]{8}$","description":"Stable id, PROJECT-SCOPED: hash(normalized_claim + '\\u0000' + project) when scope is 'project', hash(normalized_claim) when scope is 'global'. The project component is mandatory and is what stops two unrelated claims that normalize alike in different repos (e.g. 'tests must pass before merge') from colliding and merging their 'sessions' arrays across projects — which would manufacture false durability, since the L1 to L2 gate requires the sessions be from the SAME project. Merging on this id is how a claim re-observed in a later session accumulates durability instead of duplicating."},"claim":{"type":"string","minLength":3,"maxLength":280,"description":"A single assertion, stated positively and in the present tense. One claim per atom — a sentence containing 'and' is usually two atoms."},"scope":{"type":"string","enum":["project","global"],"description":"DETERMINED BY TIER, not chosen freely: L1 and L2 are always 'project'; 'global' arises ONLY from the L2->L3 merge. Extraction must therefore always emit scope='project'. Permitting a scope='global' atom at extraction would create an unreachable state — the L1 to L2 gate requires 'same project' and a global atom has no 'project' field, while L2 to L3 is a merge over two or more L2 atoms, so such an atom could never promote and would sit at L1 until it expired. Enforced by the tier/scope conditional below. See DESIGN.md section 4.1.2."},"project":{"type":"string","description":"Repo or working-directory slug. REQUIRED when scope is 'project'; MUST be absent when scope is 'global'."},"kind":{"type":"string","enum":["constraint","preference","fact","decision","failure"],"description":"constraint = a rule that must hold (PR base is dev). preference = a stated liking (stdlib only). fact = an environmental truth (backend URL). decision = a choice made with rationale. failure = a command or approach that did not work, retained so it is not retried."},"first_seen":{"type":"string","format":"date-time","description":"UTC timestamp of the earliest observation. Never updated after creation."},"last_seen":{"type":"string","format":"date-time","description":"UTC timestamp of the most recent observation. Drives the 90-day L1 expiry and recency scoring at recall."},"observations":{"type":"integer","minimum":1,"description":"Total times observed. Informational — the promotion gate counts distinct entries in 'sessions', NOT this field, so restating a claim repeatedly within one session cannot manufacture durability."},"sessions":{"type":"array","items":{"type":"string"},"minItems":1,"uniqueItems":true,"description":"Set of distinct Claude Code session ids in which this claim was observed. This is the durability counter that gates promotion (L1 to L2 needs >= 3 distinct sessions across >= 2 distinct days)."},"source":{"type":"string","description":"Back-pointer into L0 for the MOST RECENT observation. Overwritten on every merge — read 'first_source' for the evidence that originally justified the claim. Required at every tier; an unprovenanced claim can never be promoted (the anti-fabrication rule). FORMAT IS TIER-DEPENDENT: at L1 (gitignored) it is the full local path '~/.claude/projects/<cwd-slug>/<session>.jsonl#L<line>'; at L2/L3 (committed) promotion MUST strip the prefix to '<session>.jsonl#L<line>', because <cwd-slug> is the slugified absolute working directory and therefore embeds the OS username — committing it would violate the de-identification rule in DESIGN.md section 6. The prefix is derivable at read time by globbing ~/.claude/projects/*/<session>.jsonl, so nothing is lost. See DESIGN.md section 3.1.1."},"first_source":{"type":"string","description":"Back-pointer into L0 for the FIRST observation, written once at creation and never overwritten (except by the tier-dependent prefix strip described under 'source', which rewrites the format, never the target). 'source' alone is insufficient for an anti-fabrication field: after N merges it points only at the latest sighting, so the evidence that originally justified the claim would be unrecoverable exactly when an auditor needs it. Both are retained deliberately."},"promoted_from_projects":{"type":"array","items":{"type":"string"},"uniqueItems":true,"description":"Projects in which this claim independently held at L2 before being promoted to L3. REQUIRED once tier is L3. Exists because 'scope' flips to 'global' on promotion and the conditional below then forbids the single 'project' field — without this array the >= 2-distinct-projects criterion from DESIGN.md section 4.1 would be unauditable the moment it was satisfied, discarding the evidence precisely when it turns from an eligibility test into an audit trail."},"confidence":{"type":"string","enum":["observed","stated","verified"],"description":"observed = the agent inferred it (3 sessions to promote). stated = the user said it directly (2 sessions). verified = a script or check confirmed it (promotes on 1 observation; it is not hearsay)."},"tier":{"type":"string","enum":["L1","L2","L3"],"description":"Current tier. L0 is never represented as an atom — it is the raw transcript this atom points back to."},"contested":{"type":"boolean","default":false,"description":"Set when a newer atom contradicts this one. A contested L2/L3 claim is STILL injected, tagged with the conflict — silently withholding it would be worse than surfacing it. Resolution is always a human decision at adopt time."},"contested_by":{"type":"array","items":{"type":"string","pattern":"^atm_[0-9a-f]{8}$"},"description":"Ids of atoms contradicting this claim."},"promoted_at":{"type":"string","format":"date-time","description":"When this atom last changed tier. Starts the 30-day clock for L2 to L3 eligibility (section 4.1.1) and anchors demotion (section 4.3). REQUIRED at L2/L3 via the conditional below — an atom that reached a committed tier without recording when could never satisfy the age gate and would sit un-promotable forever. NOT required at L1, and explicitly not forbidden there: a demoted atom (section 4.3) sits at L1 while legitimately retaining the promoted_at from its earlier life."},"redacted":{"type":"boolean","default":false,"description":"True when the redaction pass altered the claim text before storage. REQUIRED, not optional: DESIGN.md section 6 rule 1 makes redaction non-negotiable before ANY write, so every atom that exists on disk has already been through the pass and knows its answer. Leaving the field optional would let an atom that skipped redaction entirely be schema-valid — precisely the state the rule forbids. Requiring it turns 'redaction ran' into something memory_promote.py can machine-check rather than trust. A redacted atom is still usable, but is never promoted to a committed tier without human review."}},"allOf":[{"if":{"properties":{"scope":{"const":"project"}},"required":["scope"]},"then":{"required":["project"]},"else":{"not":{"required":["project"]}}},{"$comment":"Two-sided, mirroring the scope<->project conditional. promoted_from_projects is not merely unnecessary outside L3 — it is meaningless there: it records which L2 atoms merged to produce a global claim (section 4.1.1), so an L1/L2 atom carrying it is asserting a promotion that has not happened. Section 3.1 already says an extractor must not emit it unconditionally; the else branch makes that enforceable instead of advisory.","if":{"properties":{"tier":{"const":"L3"}},"required":["tier"]},"then":{"required":["promoted_from_projects"],"properties":{"promoted_from_projects":{"minItems":2}}},"else":{"not":{"required":["promoted_from_projects"]}}},{"$comment":"promoted_at is REQUIRED at L2/L3 because sections 4.1.1 and 4.3 both key off it — the L2->L3 gate needs age >= 30 days, and demotion needs to know when the atom last moved. An L2 atom missing it could never satisfy the age test and would sit un-promotable forever, silently: the same silent-skip failure mode that made `redacted` required. Deliberately NOT forbidden at L1, because section 4.3 demotes an expired L2 claim BACK to L1 and that atom legitimately retains its promotion history; forbidding it there would make a demoted atom invalid.","if":{"properties":{"tier":{"enum":["L2","L3"]}},"required":["tier"]},"then":{"required":["promoted_at"]}},{"$comment":"tier determines scope, closing an unreachable state: a tier=L1/scope=global atom could never promote (L1->L2 needs 'same project', which it lacks; L2->L3 merges L2 atoms) and would sit at L1 until expiry. L1 and L2 are project-scoped; global exists only as the product of the L2->L3 merge. See DESIGN.md section 4.1.2.","if":{"properties":{"tier":{"enum":["L1","L2"]}},"required":["tier"]},"then":{"properties":{"scope":{"const":"project"}}},"else":{"properties":{"scope":{"const":"global"}}}},{"$comment":"Enforces the tier-dependent back-pointer format from DESIGN.md section 3.1.1. This is the one promotion rule with PII consequences — an unstripped L2/L3 back-pointer commits the contributor's OS username to a shared CLAUDE.md — so it is machine-checked here rather than left to prose, exactly like the scope and tier conditionals above. memory_promote.py must fail loudly on a bad promotion, never leak silently.","if":{"properties":{"tier":{"const":"L1"}},"required":["tier"]},"then":{"properties":{"source":{"pattern":"^~/\\.claude/projects/[^/]+/[A-Za-z0-9._-]+\\.jsonl#L[0-9]+$"},"first_source":{"pattern":"^~/\\.claude/projects/[^/]+/[A-Za-z0-9._-]+\\.jsonl#L[0-9]+$"}}},"else":{"properties":{"source":{"pattern":"^[A-Za-z0-9._-]+\\.jsonl#L[0-9]+$"},"first_source":{"pattern":"^[A-Za-z0-9._-]+\\.jsonl#L[0-9]+$"}}}}],"examples":[{"id":"atm_14a05266","claim":"mkdocs build fails when nav lists a page with no matching file","scope":"project","project":"claude-skills","kind":"failure","first_seen":"2026-08-01T14:22:09Z","last_seen":"2026-08-01T14:22:09Z","observations":1,"sessions":["01SESSIONBBBB11112222333"],"source":"~/.claude/projects/-home-user-claude-skills/01SESSIONBBBB11112222333.jsonl#L1043","first_source":"~/.claude/projects/-home-user-claude-skills/01SESSIONBBBB11112222333.jsonl#L1043","confidence":"observed","tier":"L1","redacted":false},{"id":"atm_961f033d","claim":"PR base branch is dev, never main","scope":"project","project":"claude-skills","kind":"constraint","first_seen":"2026-07-02T09:11:04Z","last_seen":"2026-08-09T10:14:22Z","observations":6,"sessions":["01SESSIONAAAA11112222333","01SESSIONBBBB11112222333","01SESSIONCCCC11112222333"],"source":"01SESSIONCCCC11112222333.jsonl#L412","first_source":"01SESSIONAAAA11112222333.jsonl#L77","confidence":"stated","tier":"L2","promoted_at":"2026-07-19T14:02:00Z","redacted":false},{"id":"atm_12cc1dc2","claim":"Python tooling stays stdlib-only; no third-party runtime deps","scope":"global","kind":"preference","first_seen":"2026-05-14T08:20:11Z","last_seen":"2026-08-08T17:45:03Z","observations":23,"sessions":["01SESSIONDDDD11112222333","01SESSIONEEEE11112222333","01SESSIONFFFF11112222333","01SESSIONGGGG11112222333"],"source":"01SESSIONGGGG11112222333.jsonl#L88","first_source":"01SESSIONDDDD11112222333.jsonl#L204","confidence":"verified","tier":"L3","promoted_from_projects":["claude-skills","other-project"],"promoted_at":"2026-06-21T11:30:00Z","redacted":false}]},"isInternal":false,"tokens":3951,"sizeBytes":15600},{"name":"hook_capture_discipline.md","path":"engineering/agent-memory/skills/agent-memory/references/hook_capture_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-memory/skills/agent-memory/references/hook_capture_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-memory%2Fskills%2Fagent-memory%2Freferences%2Fhook_capture_discipline.md -->","isInternal":false,"tokens":1688,"sizeBytes":6977},{"name":"promotion_gate_design.md","path":"engineering/agent-memory/skills/agent-memory/references/promotion_gate_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-memory/skills/agent-memory/references/promotion_gate_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-memory%2Fskills%2Fagent-memory%2Freferences%2Fpromotion_gate_design.md -->","isInternal":false,"tokens":1837,"sizeBytes":7529},{"name":"tiered_memory_canon.md","path":"engineering/agent-memory/skills/agent-memory/references/tiered_memory_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-memory/skills/agent-memory/references/tiered_memory_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-memory%2Fskills%2Fagent-memory%2Freferences%2Ftiered_memory_canon.md -->","isInternal":false,"tokens":1633,"sizeBytes":6800},{"name":"SKILL.md","path":"engineering/agent-memory/skills/agent-memory/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-memory/skills/agent-memory/SKILL.md","title":"agent-memory","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-memory%2Fskills%2Fagent-memory%2FSKILL.md -->","frontmatter":{"name":"agent-memory","description":"Use when a project's CLAUDE.md has grown past what anyone reads and you want the agent to learn durable facts from its own sessions instead — or when asking why the agent keeps re-learning the same correction, why a remembered rule is wrong, or where a memory line came from. Implements a four-tier store (L0 transcripts / L1 candidates / L2 project context / L3 stable persona) where promotion is earned by recurrence across sessions and days, never by one confident statement, and nothing reaches a committed file without a human adopting it.","argument-hint":"[optional: status | why \"<claim>\" | a tier name]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Tencent TencentDB-Agent-Memory's tiering concept rebuilt natively on Claude Code hooks; deterministic recurrence gates, no LLM, no database","distinct_from":"llm-wiki (a vault you write on purpose; this writes itself from sessions); skillopt-sleep (replays tasks to improve a skill; this extracts facts to remember); memory-engineering (audits and prices any memory system; this IS one, and is a legitimate subject of that audit)"}},"isInternal":false,"tokens":1231,"sizeBytes":5222},{"name":"eval_case_spec.example.json","path":"engineering/agent-regression-evals/skills/agent-regression-evals/assets/eval_case_spec.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-regression-evals/skills/agent-regression-evals/assets/eval_case_spec.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-regression-evals%2Fskills%2Fagent-regression-evals%2Fassets%2Feval_case_spec.example.json -->","frontmatter":{"refund-lookup":{"expected":[{"tool":"get_order","args":{"order_id":"A-1001"}},{"tool":"get_refund_policy","args":{}},{"tool":"issue_refund","args":{"order_id":"A-1001"}}],"match":"strict","args_match":"subset","forbidden":["delete_order"],"max_calls":6},"faq-shipping":{"expected":[{"tool":"search_kb","args":{}}],"match":"superset","args_match":"ignore","forbidden":["issue_refund"]}},"isInternal":false,"tokens":197,"sizeBytes":669},{"name":"eval_statistics.md","path":"engineering/agent-regression-evals/skills/agent-regression-evals/references/eval_statistics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-regression-evals/skills/agent-regression-evals/references/eval_statistics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-regression-evals%2Fskills%2Fagent-regression-evals%2Freferences%2Feval_statistics.md -->","isInternal":false,"tokens":1455,"sizeBytes":4964},{"name":"flaky_cases_and_quarantine.md","path":"engineering/agent-regression-evals/skills/agent-regression-evals/references/flaky_cases_and_quarantine.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-regression-evals/skills/agent-regression-evals/references/flaky_cases_and_quarantine.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-regression-evals%2Fskills%2Fagent-regression-evals%2Freferences%2Fflaky_cases_and_quarantine.md -->","isInternal":false,"tokens":1334,"sizeBytes":4935},{"name":"trajectory_grading.md","path":"engineering/agent-regression-evals/skills/agent-regression-evals/references/trajectory_grading.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-regression-evals/skills/agent-regression-evals/references/trajectory_grading.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-regression-evals%2Fskills%2Fagent-regression-evals%2Freferences%2Ftrajectory_grading.md -->","isInternal":false,"tokens":1083,"sizeBytes":4249},{"name":"SKILL.md","path":"engineering/agent-regression-evals/skills/agent-regression-evals/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-regression-evals/skills/agent-regression-evals/SKILL.md","title":"agent-regression-evals","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-regression-evals%2Fskills%2Fagent-regression-evals%2FSKILL.md -->","frontmatter":{"name":"agent-regression-evals","description":"Use when an agent, prompt, model or tool change needs proof it did not make the agent worse — setting up a regression eval suite, deciding whether a pass-rate drop is real or noise, grading tool-call trajectories, finding flaky eval cases, or wiring an eval gate into CI that blocks the merge. Runs repeated trials, reports pass@k and pass^k, compares candidate to baseline with paired statistics, and refuses to pass a dropped case, a critical-case regression, or a forbidden tool call.","argument-hint":"[baseline.jsonl candidate.jsonl | results.jsonl | a question about agent evals]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Statistics-first eval gate: 3 deterministic stdlib scripts (trajectory grading, flake detection, paired regression gate) with blocking exit codes","distinct_from":"prompt-governance (versions and registers prompts; this gates a change with statistics); self-eval (grades one session's work); agenthub eval (ranks parallel agents in one session)"}},"isInternal":false,"tokens":1393,"sizeBytes":5649},{"name":"agent-templates.md","path":"engineering/agenthub/skills/agenthub/references/agent-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/agenthub/references/agent-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fagenthub%2Freferences%2Fagent-templates.md -->","isInternal":false,"tokens":1729,"sizeBytes":7795},{"name":"coordination-strategies.md","path":"engineering/agenthub/skills/agenthub/references/coordination-strategies.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/agenthub/references/coordination-strategies.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fagenthub%2Freferences%2Fcoordination-strategies.md -->","isInternal":false,"tokens":1467,"sizeBytes":5958},{"name":"dag-patterns.md","path":"engineering/agenthub/skills/agenthub/references/dag-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/agenthub/references/dag-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fagenthub%2Freferences%2Fdag-patterns.md -->","isInternal":false,"tokens":1046,"sizeBytes":4091},{"name":"SKILL.md","path":"engineering/agenthub/skills/agenthub/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/agenthub/SKILL.md","title":"agenthub","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fagenthub%2FSKILL.md -->","frontmatter":{"name":"agenthub","description":"Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.","license":"MIT","metadata":{"version":"2.1.2","author":"Alireza Rezvani","category":"engineering","updated":"2026-03-17"}},"isInternal":false,"tokens":1932,"sizeBytes":7922},{"name":"SKILL.md","path":"engineering/agenthub/skills/board/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/board/SKILL.md","title":"board","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fboard%2FSKILL.md -->","frontmatter":{"name":"board","description":"Read, write, and browse the AgentHub message board for agent coordination. Use when the user runs /hub:board or asks to post, read, or inspect coordination messages between competing AgentHub agents.","metadata":{"command":"/hub:board"}},"isInternal":false,"tokens":592,"sizeBytes":2461},{"name":"SKILL.md","path":"engineering/agenthub/skills/eval/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/eval/SKILL.md","title":"eval","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Feval%2FSKILL.md -->","frontmatter":{"name":"eval","description":"Evaluate and rank agent results by metric or LLM judge for an AgentHub session. Use when the user runs /hub:eval or asks to score, compare, or pick a winner among completed AgentHub agents.","metadata":{"command":"/hub:eval"}},"isInternal":false,"tokens":642,"sizeBytes":2491},{"name":"SKILL.md","path":"engineering/agenthub/skills/hub-init/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/hub-init/SKILL.md","title":"hub-init","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fhub-init%2FSKILL.md -->","frontmatter":{"name":"hub-init","description":"Create a new AgentHub collaboration session with task, agent count, and evaluation criteria. Use when the user runs /hub:hub-init or asks to start a multi-agent competition on a task.","metadata":{"command":"/hub:hub-init"}},"isInternal":false,"tokens":719,"sizeBytes":2850},{"name":"SKILL.md","path":"engineering/agenthub/skills/hub-run/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/hub-run/SKILL.md","title":"hub-run","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fhub-run%2FSKILL.md -->","frontmatter":{"name":"hub-run","description":"One-shot lifecycle command that chains init → baseline → spawn → eval → merge in a single invocation. Use when the user runs /hub:hub-run or asks to execute a full AgentHub competition end-to-end.","metadata":{"command":"/hub:hub-run"}},"isInternal":false,"tokens":973,"sizeBytes":3838},{"name":"SKILL.md","path":"engineering/agenthub/skills/hub-status/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/hub-status/SKILL.md","title":"hub-status","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fhub-status%2FSKILL.md -->","frontmatter":{"name":"hub-status","description":"Show DAG state, agent progress, and branch status for an AgentHub session. Use when the user runs /hub:hub-status or asks how the AgentHub agents are doing.","metadata":{"command":"/hub:hub-status"}},"isInternal":false,"tokens":714,"sizeBytes":2510},{"name":"SKILL.md","path":"engineering/agenthub/skills/merge/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/merge/SKILL.md","title":"merge","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fmerge%2FSKILL.md -->","frontmatter":{"name":"merge","description":"Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning AgentHub result and tidy the session.","metadata":{"command":"/hub:merge"}},"isInternal":false,"tokens":611,"sizeBytes":2368},{"name":"SKILL.md","path":"engineering/agenthub/skills/spawn/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/skills/spawn/SKILL.md","title":"spawn","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2Fskills%2Fspawn%2FSKILL.md -->","frontmatter":{"name":"spawn","description":"Launch N parallel subagents in isolated git worktrees to compete on the session task. Use when the user runs /hub:spawn or asks to start the competing agents for an initialized AgentHub session.","metadata":{"command":"/hub:spawn"}},"isInternal":false,"tokens":763,"sizeBytes":3361},{"name":"SKILL.md","path":"engineering/autoresearch-agent/skills/ar-resume/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/ar-resume/SKILL.md","title":"ar-resume","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Far-resume%2FSKILL.md -->","frontmatter":{"name":"ar-resume","description":"Resume a paused experiment. Checkout the experiment branch, read results history, continue iterating. Use when the user runs /ar:ar-resume or asks to pick up a previously started autoresearch experiment.","metadata":{"command":"/ar:ar-resume"}},"isInternal":false,"tokens":553,"sizeBytes":2144},{"name":"SKILL.md","path":"engineering/autoresearch-agent/skills/ar-run/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/ar-run/SKILL.md","title":"ar-run","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Far-run%2FSKILL.md -->","frontmatter":{"name":"ar-run","description":"Run a single experiment iteration. Edit the target file, evaluate, keep or discard. Use when the user runs /ar:ar-run or asks for one manual autoresearch iteration.","metadata":{"command":"/ar:ar-run"}},"isInternal":false,"tokens":609,"sizeBytes":2543},{"name":"SKILL.md","path":"engineering/autoresearch-agent/skills/ar-status/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/ar-status/SKILL.md","title":"ar-status","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Far-status%2FSKILL.md -->","frontmatter":{"name":"ar-status","description":"Show experiment dashboard with results, active loops, and progress. Use when the user runs /ar:ar-status or asks how an autoresearch experiment is going.","metadata":{"command":"/ar:ar-status"}},"isInternal":false,"tokens":487,"sizeBytes":1957},{"name":"experiment-domains.md","path":"engineering/autoresearch-agent/skills/autoresearch-agent/references/experiment-domains.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/autoresearch-agent/references/experiment-domains.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Fautoresearch-agent%2Freferences%2Fexperiment-domains.md -->","isInternal":false,"tokens":1639,"sizeBytes":6672},{"name":"program-template.md","path":"engineering/autoresearch-agent/skills/autoresearch-agent/references/program-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/autoresearch-agent/references/program-template.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Fautoresearch-agent%2Freferences%2Fprogram-template.md -->","isInternal":false,"tokens":1154,"sizeBytes":4819},{"name":"SKILL.md","path":"engineering/autoresearch-agent/skills/autoresearch-agent/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/autoresearch-agent/SKILL.md","title":"autoresearch-agent","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Fautoresearch-agent%2FSKILL.md -->","frontmatter":{"name":"autoresearch-agent","description":"Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.","license":"MIT","metadata":{"version":"2.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-03-13"}},"isInternal":false,"tokens":2939,"sizeBytes":12324},{"name":"SKILL.md","path":"engineering/autoresearch-agent/skills/loop/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/loop/SKILL.md","title":"loop","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Floop%2FSKILL.md -->","frontmatter":{"name":"loop","description":"Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling. Use when the user runs /ar:loop or asks to run an autoresearch experiment continuously on a schedule.","metadata":{"command":"/ar:loop"}},"isInternal":false,"tokens":1086,"sizeBytes":4234},{"name":"SKILL.md","path":"engineering/autoresearch-agent/skills/setup/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/skills/setup/SKILL.md","title":"setup","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2Fskills%2Fsetup%2FSKILL.md -->","frontmatter":{"name":"setup","description":"Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator. Use when the user runs /ar:setup or asks to start optimizing a file with the autoresearch loop.","metadata":{"command":"/ar:setup"}},"isInternal":false,"tokens":758,"sizeBytes":2978},{"name":"api-integration.md","path":"engineering/behuman/skills/behuman/references/api-integration.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/behuman/skills/behuman/references/api-integration.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbehuman%2Fskills%2Fbehuman%2Freferences%2Fapi-integration.md -->","isInternal":false,"tokens":729,"sizeBytes":3171},{"name":"SKILL.md","path":"engineering/behuman/skills/behuman/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/behuman/skills/behuman/SKILL.md","title":"behuman","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbehuman%2Fskills%2Fbehuman%2FSKILL.md -->","frontmatter":{"name":"behuman","description":"Use when the user wants more human-like AI responses — less robotic, less listy, more authentic. Triggers: 'behuman', 'be real', 'like a human', 'more human', 'less AI', 'talk like a person', 'mirror mode', 'stop being so AI', or when conversations are emotionally charged (grief, job loss, relationship advice, fear). NOT for technical questions, code generation, or factual lookups."},"isInternal":false,"tokens":1839,"sizeBytes":8115},{"name":"chapter_template.md","path":"engineering/book-to-skill/skills/book-to-skill/assets/chapter_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/assets/chapter_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Fassets%2Fchapter_template.md -->","isInternal":false,"tokens":687,"sizeBytes":2879},{"name":"cheatsheet_template.md","path":"engineering/book-to-skill/skills/book-to-skill/assets/cheatsheet_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/assets/cheatsheet_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Fassets%2Fcheatsheet_template.md -->","isInternal":false,"tokens":621,"sizeBytes":2541},{"name":"master_skill_template.md","path":"engineering/book-to-skill/skills/book-to-skill/assets/master_skill_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/assets/master_skill_template.md","title":"<slug>","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Fassets%2Fmaster_skill_template.md -->","frontmatter":{"name":"<slug>","description":"Knowledge base from \"<Full Title>\" by <Author(s)>. Use when applying <author>'s frameworks for <3–6 key topics>, studying the book, or referencing its concepts."},"isInternal":false,"tokens":765,"sizeBytes":3178},{"name":"conversion_workflow.md","path":"engineering/book-to-skill/skills/book-to-skill/references/conversion_workflow.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/references/conversion_workflow.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Freferences%2Fconversion_workflow.md -->","isInternal":false,"tokens":4404,"sizeBytes":17053},{"name":"document_extraction_pipeline.md","path":"engineering/book-to-skill/skills/book-to-skill/references/document_extraction_pipeline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/references/document_extraction_pipeline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Freferences%2Fdocument_extraction_pipeline.md -->","isInternal":false,"tokens":2416,"sizeBytes":9675},{"name":"knowledge_extraction_canon.md","path":"engineering/book-to-skill/skills/book-to-skill/references/knowledge_extraction_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/references/knowledge_extraction_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Freferences%2Fknowledge_extraction_canon.md -->","isInternal":false,"tokens":1838,"sizeBytes":7609},{"name":"progressive_disclosure_budgets.md","path":"engineering/book-to-skill/skills/book-to-skill/references/progressive_disclosure_budgets.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/references/progressive_disclosure_budgets.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Freferences%2Fprogressive_disclosure_budgets.md -->","isInternal":false,"tokens":1965,"sizeBytes":8461},{"name":"rights_and_provenance.md","path":"engineering/book-to-skill/skills/book-to-skill/references/rights_and_provenance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/references/rights_and_provenance.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2Freferences%2Frights_and_provenance.md -->","isInternal":false,"tokens":1945,"sizeBytes":8252},{"name":"SKILL.md","path":"engineering/book-to-skill/skills/book-to-skill/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/skills/book-to-skill/SKILL.md","title":"book-to-skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2Fskills%2Fbook-to-skill%2FSKILL.md -->","frontmatter":{"name":"book-to-skill","description":"Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills — extracting named frameworks, principles, techniques, and anti-patterns into a master SKILL.md plus on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Use when the user wants to study a document with an agent, apply an author's frameworks while working, turn internal docs or standards into a reusable knowledge base, or package a compiled book skill as a claude-skills plugin.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-08-05"}},"isInternal":false,"tokens":2858,"sizeBytes":11784},{"name":"SKILL.md","path":"engineering/boost-asio-pro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/boost-asio-pro/SKILL.md","title":"boost-asio-pro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fboost-asio-pro%2FSKILL.md -->","frontmatter":{"name":"boost-asio-pro","description":"Use when writing or reviewing asynchronous C++ networking code with Boost.Asio or standalone Asio — TCP/UDP servers and clients, SSL/TLS, timers, strands, io_context, co_spawn, awaitable, async_read/async_write, asio::spawn, yield_context, or pre-C++20 completion-handler callbacks."},"isInternal":false,"tokens":2755,"sizeBytes":10550},{"name":"companion_tooling.md","path":"engineering/caveman/skills/caveman/references/companion_tooling.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/caveman/skills/caveman/references/companion_tooling.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcaveman%2Fskills%2Fcaveman%2Freferences%2Fcompanion_tooling.md -->","isInternal":false,"tokens":863,"sizeBytes":3528},{"name":"compression_principles.md","path":"engineering/caveman/skills/caveman/references/compression_principles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/caveman/skills/caveman/references/compression_principles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcaveman%2Fskills%2Fcaveman%2Freferences%2Fcompression_principles.md -->","isInternal":false,"tokens":1534,"sizeBytes":6169},{"name":"when_caveman_backfires.md","path":"engineering/caveman/skills/caveman/references/when_caveman_backfires.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/caveman/skills/caveman/references/when_caveman_backfires.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcaveman%2Fskills%2Fcaveman%2Freferences%2Fwhen_caveman_backfires.md -->","isInternal":false,"tokens":1468,"sizeBytes":6294},{"name":"SKILL.md","path":"engineering/caveman/skills/caveman/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/caveman/skills/caveman/SKILL.md","title":"caveman","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcaveman%2Fskills%2Fcaveman%2FSKILL.md -->","frontmatter":{"name":"caveman","description":"Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use when user says \"caveman mode\", \"talk like caveman\", \"use caveman\", \"less tokens\", \"be brief\", or invokes /caveman.\n","license":"MIT","metadata":{"derived_from":"https://github.com/mattpocock/skills/tree/main/skills/productivity/caveman","original_author":"Matt Pocock (@mattpocock)","original_license":"MIT","voice":"Matt Pocock — terse, fragment-OK, no filler","version":"1.0.0"}},"isInternal":false,"tokens":684,"sizeBytes":2731},{"name":"experiment_template.md","path":"engineering/chaos-engineering/skills/chaos-engineering/assets/experiment_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/assets/experiment_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2Fassets%2Fexperiment_template.md -->","isInternal":false,"tokens":676,"sizeBytes":2410},{"name":"postmortem_template.md","path":"engineering/chaos-engineering/skills/chaos-engineering/assets/postmortem_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/assets/postmortem_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2Fassets%2Fpostmortem_template.md -->","isInternal":false,"tokens":403,"sizeBytes":1534},{"name":"attack_taxonomy.md","path":"engineering/chaos-engineering/skills/chaos-engineering/references/attack_taxonomy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/references/attack_taxonomy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2Freferences%2Fattack_taxonomy.md -->","isInternal":false,"tokens":1469,"sizeBytes":5881},{"name":"chaos_principles.md","path":"engineering/chaos-engineering/skills/chaos-engineering/references/chaos_principles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/references/chaos_principles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2Freferences%2Fchaos_principles.md -->","isInternal":false,"tokens":1286,"sizeBytes":5456},{"name":"experiment_design.md","path":"engineering/chaos-engineering/skills/chaos-engineering/references/experiment_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/references/experiment_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2Freferences%2Fexperiment_design.md -->","isInternal":false,"tokens":1427,"sizeBytes":5741},{"name":"tooling_landscape.md","path":"engineering/chaos-engineering/skills/chaos-engineering/references/tooling_landscape.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/references/tooling_landscape.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2Freferences%2Ftooling_landscape.md -->","isInternal":false,"tokens":1617,"sizeBytes":6269},{"name":"SKILL.md","path":"engineering/chaos-engineering/skills/chaos-engineering/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/skills/chaos-engineering/SKILL.md","title":"chaos-engineering","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2Fskills%2Fchaos-engineering%2FSKILL.md -->","frontmatter":{"name":"chaos-engineering","description":"Use when planning, running, or learning from chaos engineering experiments. Triggers on \"chaos experiment\", \"fault injection\", \"gameday\", \"resilience test\", \"blast radius\", \"steady state\", \"abort criteria\", \"Chaos Toolkit\", \"Chaos Mesh\", \"Litmus\", \"Gremlin\", \"AWS FIS\", or any deliberate failure-injection question. Ships experiment designer, blast-radius calculator, and postmortem generator (all stdlib Python), 4 references on chaos principles + experiment design + attack taxonomy + tooling landscape, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (common chaos targets).","context":"fork","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["chaos-engineering","resilience","fault-injection","gameday","sre","reliability","chaos-toolkit","chaos-mesh","litmus","gremlin","aws-fis"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2530,"sizeBytes":10708},{"name":"README.md","path":"engineering/claude-coach/skills/claude-coach/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/claude-coach/skills/claude-coach/README.md","title":"Claude-coach Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fclaude-coach%2Fskills%2Fclaude-coach%2FREADME.md -->","isInternal":false,"tokens":170,"sizeBytes":654},{"name":"cheat-codes.md","path":"engineering/claude-coach/skills/claude-coach/references/cheat-codes.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/claude-coach/skills/claude-coach/references/cheat-codes.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fclaude-coach%2Fskills%2Fclaude-coach%2Freferences%2Fcheat-codes.md -->","isInternal":false,"tokens":1119,"sizeBytes":5199},{"name":"coaching-rules.md","path":"engineering/claude-coach/skills/claude-coach/references/coaching-rules.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/claude-coach/skills/claude-coach/references/coaching-rules.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fclaude-coach%2Fskills%2Fclaude-coach%2Freferences%2Fcoaching-rules.md -->","isInternal":false,"tokens":617,"sizeBytes":2781},{"name":"SKILL.md","path":"engineering/claude-coach/skills/claude-coach/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/claude-coach/skills/claude-coach/SKILL.md","title":"claude-coach","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fclaude-coach%2Fskills%2Fclaude-coach%2FSKILL.md -->","frontmatter":{"name":"claude-coach","description":"Personal coach that teaches users to become Claude power users. Use this skill the FIRST time a user asks to \"learn Claude\", \"be a power user\", \"coach me\", \"teach me Claude tricks\", \"what can Claude do\", \"make me better at prompting\", or any variation. After activation, also use it on EVERY subsequent turn to detect missed optimization opportunities (vague prompts, ignored capabilities, manual work Claude could automate) and surface a single power-user tip. Trigger generously — most users do not know what they do not know, so err on the side of coaching.","license":"MIT","metadata":{"tier":"POWERFUL","category":"meta","author":"claude-skills","dependencies":"python3.11","version":"2.9.0"}},"isInternal":false,"tokens":1929,"sizeBytes":8465},{"name":"SKILL.md","path":"engineering/code-tour/skills/code-tour/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/code-tour/skills/code-tour/SKILL.md","title":"code-tour","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcode-tour%2Fskills%2Fcode-tour%2FSKILL.md -->","frontmatter":{"name":"code-tour","description":"Use when the user asks to create a CodeTour .tour file — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Trigger for: create a tour, onboarding tour, architecture tour, PR review tour, explain how X works, vibe check, RCA tour, contributor guide, or any structured code walkthrough request."},"isInternal":false,"tokens":1636,"sizeBytes":6332},{"name":"approved-components.example.json","path":"engineering/coding-agent-rollout/skills/coding-agent-rollout/assets/approved-components.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/coding-agent-rollout/skills/coding-agent-rollout/assets/approved-components.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcoding-agent-rollout%2Fskills%2Fcoding-agent-rollout%2Fassets%2Fapproved-components.example.json -->","frontmatter":{"servers":["github","postgres","https://mcp.internal.example.com/docs"],"plugins":["code-review@claude-plugins-official","agent-regression-evals@claude-code-skills"],"marketplaces":["claude-plugins-official","claude-code-skills"]},"isInternal":false,"tokens":68,"sizeBytes":249},{"name":"managed-settings.example.json","path":"engineering/coding-agent-rollout/skills/coding-agent-rollout/assets/managed-settings.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/coding-agent-rollout/skills/coding-agent-rollout/assets/managed-settings.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcoding-agent-rollout%2Fskills%2Fcoding-agent-rollout%2Fassets%2Fmanaged-settings.example.json -->","frontmatter":{"permissions":{"disableBypassPermissionsMode":"disable","deny":["Read(./.env)","Read(./.env.*)","Read(//**/*.pem)","Read(//**/id_rsa*)","Read(~/.aws/**)","Read(~/.ssh/**)","Bash(git push --force *)","Bash(sudo *)","Bash(curl * | sh)"],"ask":["Bash(git push *)","Bash(npm publish *)","Bash(terraform apply *)","Bash(kubectl apply *)"]},"allowManagedHooksOnly":true,"allowedMcpServers":[{"serverName":"github"},{"serverUrl":"https://mcp.internal.example.com/*"}],"strictKnownMarketplaces":[{"source":"github","repo":"alirezarezvani/claude-skills"},{"source":"github","repo":"your-org/claude-marketplace"}],"cleanupPeriodDays":30,"env":{"DISABLE_ERROR_REPORTING":"1"}},"isInternal":false,"tokens":279,"sizeBytes":865},{"name":"rollout_plan.md","path":"engineering/coding-agent-rollout/skills/coding-agent-rollout/assets/rollout_plan.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/coding-agent-rollout/skills/coding-agent-rollout/assets/rollout_plan.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcoding-agent-rollout%2Fskills%2Fcoding-agent-rollout%2Fassets%2Frollout_plan.md -->","isInternal":false,"tokens":531,"sizeBytes":2025},{"name":"mcp_and_plugin_governance.md","path":"engineering/coding-agent-rollout/skills/coding-agent-rollout/references/mcp_and_plugin_governance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/coding-agent-rollout/skills/coding-agent-rollout/references/mcp_and_plugin_governance.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcoding-agent-rollout%2Fskills%2Fcoding-agent-rollout%2Freferences%2Fmcp_and_plugin_governance.md 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It points at the official chapters — it never reproduces them.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-08-25"}},"isInternal":false,"tokens":2928,"sizeBytes":11601},{"name":"scene-design-system.md","path":"engineering/demo-video/skills/demo-video/references/scene-design-system.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/demo-video/skills/demo-video/references/scene-design-system.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdemo-video%2Fskills%2Fdemo-video%2Freferences%2Fscene-design-system.md -->","isInternal":false,"tokens":553,"sizeBytes":1622},{"name":"SKILL.md","path":"engineering/demo-video/skills/demo-video/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/demo-video/skills/demo-video/SKILL.md","title":"demo-video","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdemo-video%2Fskills%2Fdemo-video%2FSKILL.md -->","frontmatter":{"name":"demo-video","description":"Use when the user asks to create a demo video, product walkthrough, feature showcase, animated presentation, marketing video, or GIF from screenshots or scene descriptions. Orchestrates playwright, ffmpeg, and edge-tts MCPs to produce polished video content."},"isInternal":false,"tokens":1258,"sizeBytes":5173},{"name":"compose-patterns.md","path":"engineering/docker-development/skills/docker-development/references/compose-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/docker-development/skills/docker-development/references/compose-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdocker-development%2Fskills%2Fdocker-development%2Freferences%2Fcompose-patterns.md -->","isInternal":false,"tokens":1529,"sizeBytes":5877},{"name":"dockerfile-best-practices.md","path":"engineering/docker-development/skills/docker-development/references/dockerfile-best-practices.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/docker-development/skills/docker-development/references/dockerfile-best-practices.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdocker-development%2Fskills%2Fdocker-development%2Freferences%2Fdockerfile-best-practices.md -->","isInternal":false,"tokens":1456,"sizeBytes":5243},{"name":"SKILL.md","path":"engineering/docker-development/skills/docker-development/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/docker-development/skills/docker-development/SKILL.md","title":"docker-development","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdocker-development%2Fskills%2Fdocker-development%2FSKILL.md -->","frontmatter":{"name":"docker-development","description":"Docker and container development agent skill and plugin for Dockerfile optimization, docker-compose orchestration, multi-stage builds, and container security hardening. Use when: user wants to optimize a Dockerfile, create or improve docker-compose configurations, implement multi-stage builds, audit container security, reduce image size, or follow container best practices. Covers build performance, layer caching, secret management, and production-ready container patterns.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-03-16"}},"isInternal":false,"tokens":2836,"sizeBytes":11876},{"name":"flag_request_template.md","path":"engineering/feature-flags-architect/skills/feature-flags-architect/assets/flag_request_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/skills/feature-flags-architect/assets/flag_request_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2Fskills%2Ffeature-flags-architect%2Fassets%2Fflag_request_template.md -->","isInternal":false,"tokens":459,"sizeBytes":1770},{"name":"flag_lifecycle.md","path":"engineering/feature-flags-architect/skills/feature-flags-architect/references/flag_lifecycle.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/skills/feature-flags-architect/references/flag_lifecycle.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2Fskills%2Ffeature-flags-architect%2Freferences%2Fflag_lifecycle.md -->","isInternal":false,"tokens":1506,"sizeBytes":5869},{"name":"flag_taxonomy.md","path":"engineering/feature-flags-architect/skills/feature-flags-architect/references/flag_taxonomy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/skills/feature-flags-architect/references/flag_taxonomy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2Fskills%2Ffeature-flags-architect%2Freferences%2Fflag_taxonomy.md -->","isInternal":false,"tokens":1099,"sizeBytes":4511},{"name":"provider_comparison.md","path":"engineering/feature-flags-architect/skills/feature-flags-architect/references/provider_comparison.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/skills/feature-flags-architect/references/provider_comparison.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2Fskills%2Ffeature-flags-architect%2Freferences%2Fprovider_comparison.md -->","isInternal":false,"tokens":1342,"sizeBytes":5148},{"name":"rollout_strategies.md","path":"engineering/feature-flags-architect/skills/feature-flags-architect/references/rollout_strategies.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/skills/feature-flags-architect/references/rollout_strategies.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2Fskills%2Ffeature-flags-architect%2Freferences%2Frollout_strategies.md -->","isInternal":false,"tokens":1316,"sizeBytes":5024},{"name":"SKILL.md","path":"engineering/feature-flags-architect/skills/feature-flags-architect/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/skills/feature-flags-architect/SKILL.md","title":"feature-flags-architect","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2Fskills%2Ffeature-flags-architect%2FSKILL.md -->","frontmatter":{"name":"feature-flags-architect","description":"Use when adding, retiring, or auditing feature flags. 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Ships flag debt scanner, rollout planner, and kill-switch auditor (all stdlib Python), 4 references on flag taxonomy + provider trade-offs + rollout strategies + lifecycle, plus a /flag-cleanup slash command.","context":"fork","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["feature-flags","progressive-delivery","rollout","kill-switch","launchdarkly","growthbook","statsig","unleash","flipt","release-engineering"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2475,"sizeBytes":9813},{"name":"companion_tooling.md","path":"engineering/grill-me/skills/grill-me/references/companion_tooling.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/grill-me/skills/grill-me/references/companion_tooling.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fgrill-me%2Fskills%2Fgrill-me%2Freferences%2Fcompanion_tooling.md -->","isInternal":false,"tokens":772,"sizeBytes":3268},{"name":"forcing_question_patterns.md","path":"engineering/grill-me/skills/grill-me/references/forcing_question_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/grill-me/skills/grill-me/references/forcing_question_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fgrill-me%2Fskills%2Fgrill-me%2Freferences%2Fforcing_question_patterns.md -->","isInternal":false,"tokens":1629,"sizeBytes":6786},{"name":"when_to_stop_grilling.md","path":"engineering/grill-me/skills/grill-me/references/when_to_stop_grilling.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/grill-me/skills/grill-me/references/when_to_stop_grilling.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fgrill-me%2Fskills%2Fgrill-me%2Freferences%2Fwhen_to_stop_grilling.md -->","isInternal":false,"tokens":1549,"sizeBytes":6633},{"name":"SKILL.md","path":"engineering/grill-me/skills/grill-me/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/grill-me/skills/grill-me/SKILL.md","title":"grill-me","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fgrill-me%2Fskills%2Fgrill-me%2FSKILL.md -->","frontmatter":{"name":"grill-me","description":"Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. 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Use when user wants to stress-test a plan against documented domain language, or mentions \"grill with docs\".","license":"MIT","metadata":{"derived_from":"https://github.com/mattpocock/skills/tree/main/skills/engineering/grill-with-docs","original_author":"Matt Pocock (@mattpocock)","original_license":"MIT","voice":"Matt Pocock — relentless, one-at-a-time, codebase-and-docs-first, ADRs only when 3 criteria are met","version":"1.0.0"}},"isInternal":false,"tokens":1755,"sizeBytes":7306},{"name":"companion_tooling.md","path":"engineering/handoff/skills/handoff/references/companion_tooling.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/handoff/skills/handoff/references/companion_tooling.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhandoff%2Fskills%2Fhandoff%2Freferences%2Fcompanion_tooling.md -->","isInternal":false,"tokens":753,"sizeBytes":3091},{"name":"deduplication_discipline.md","path":"engineering/handoff/skills/handoff/references/deduplication_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/handoff/skills/handoff/references/deduplication_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhandoff%2Fskills%2Fhandoff%2Freferences%2Fdeduplication_discipline.md -->","isInternal":false,"tokens":1615,"sizeBytes":6441},{"name":"handoff_structure.md","path":"engineering/handoff/skills/handoff/references/handoff_structure.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/handoff/skills/handoff/references/handoff_structure.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhandoff%2Fskills%2Fhandoff%2Freferences%2Fhandoff_structure.md -->","isInternal":false,"tokens":1483,"sizeBytes":6060},{"name":"next_session_skill_matching.md","path":"engineering/handoff/skills/handoff/references/next_session_skill_matching.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/handoff/skills/handoff/references/next_session_skill_matching.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhandoff%2Fskills%2Fhandoff%2Freferences%2Fnext_session_skill_matching.md -->","isInternal":false,"tokens":1551,"sizeBytes":6268},{"name":"SKILL.md","path":"engineering/handoff/skills/handoff/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/handoff/skills/handoff/SKILL.md","title":"handoff","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhandoff%2Fskills%2Fhandoff%2FSKILL.md -->","frontmatter":{"name":"handoff","description":"Compact the current conversation into a handoff document for another agent to pick up. References existing artifacts (PRDs, plans, ADRs, issues, commits, diffs) by path or URL instead of duplicating them. Use when user wants to hand off the conversation to a fresh agent or starts a new session that picks up prior work.","argument-hint":"What will the next session be used for?","license":"MIT","metadata":{"derived_from":"https://github.com/mattpocock/skills/tree/main/skills/productivity/handoff","original_author":"Matt Pocock (@mattpocock)","original_license":"MIT","voice":"Matt Pocock — no-duplication, reference-existing-artifacts, tailored to next-session focus","version":"1.0.0"}},"isInternal":false,"tokens":538,"sizeBytes":2131},{"name":"chart-patterns.md","path":"engineering/helm-chart-builder/skills/helm-chart-builder/references/chart-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/helm-chart-builder/skills/helm-chart-builder/references/chart-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhelm-chart-builder%2Fskills%2Fhelm-chart-builder%2Freferences%2Fchart-patterns.md -->","isInternal":false,"tokens":3036,"sizeBytes":11818},{"name":"values-design.md","path":"engineering/helm-chart-builder/skills/helm-chart-builder/references/values-design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/helm-chart-builder/skills/helm-chart-builder/references/values-design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhelm-chart-builder%2Fskills%2Fhelm-chart-builder%2Freferences%2Fvalues-design.md -->","isInternal":false,"tokens":2539,"sizeBytes":9736},{"name":"SKILL.md","path":"engineering/helm-chart-builder/skills/helm-chart-builder/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/helm-chart-builder/skills/helm-chart-builder/SKILL.md","title":"helm-chart-builder","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhelm-chart-builder%2Fskills%2Fhelm-chart-builder%2FSKILL.md -->","frontmatter":{"name":"helm-chart-builder","description":"Helm chart development agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw — chart scaffolding, values design, template patterns, dependency management, security hardening, and chart testing. Use when: user wants to create or improve Helm charts, design values.yaml files, implement template helpers, audit chart security (RBAC, network policies, pod security), manage subcharts, or run helm lint/test.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-03-15"}},"isInternal":false,"tokens":3601,"sizeBytes":15439},{"name":"SKILL.md","path":"engineering/hivemind/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/hivemind/SKILL.md","title":"hivemind","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhivemind%2FSKILL.md -->","frontmatter":{"name":"hivemind","description":"Orchestrate free opencode workers from Claude Code to cut token costs. Use when delegating grunt work to a single worker or a parallel swarm (scout/coder/tester) with worktree isolation, benchmarking against opencode, or when the user says \"spawn a worker\", \"swarm\", \"delegate to opencode\", or \"/oc\"."},"isInternal":false,"tokens":3052,"sizeBytes":12151},{"name":"batch.v1.schema.json","path":"engineering/human-gate/skills/human-gate/assets/batch.v1.schema.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/human-gate/skills/human-gate/assets/batch.v1.schema.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhuman-gate%2Fskills%2Fhuman-gate%2Fassets%2Fbatch.v1.schema.json -->","frontmatter":{"$schema":"https://json-schema.org/draft/2020-12/schema","$id":"https://github.com/alirezarezvani/claude-skills/engineering/human-gate/batch.v1.schema.json","title":"human-gate feedback batch (batch.v1)","description":"One round of batched human review feedback, produced by feedback_parser.py from a review sidecar and consumed by human_gate.py.","type":"object","required":["schema","target","round","reviewer","approved","blocking_open","counts","items"],"additionalProperties":false,"properties":{"schema":{"const":"batch.v1"},"target":{"type":"string","description":"Basename of the artifact under review."},"round":{"type":"integer","minimum":1,"description":"1-based review round. Capped by human_gate.py --max-rounds."},"reviewer":{"type":"string","description":"Named human reviewer. Empty fails gate rule G3 — approval belongs to a person, not a team."},"approved":{"type":"boolean","description":"True only when an APPROVE item exists AND no BLOCKER/MAJOR item is open. Absence of blockers alone is not approval."},"blocking_open":{"type":"integer","minimum":0,"description":"Count of open BLOCKER + MAJOR comment items. 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Builds a single-file HTML review page, collects batched feedback as a structured artifact instead of chat prose, and runs a gate that refuses to close while a BLOCKER is open, the reviewer is unnamed, or nobody has reviewed at all. Use when a plan, spec, RFC, report, landing page, migration, or any irreversible action needs human sign-off before shipping, or on requests such as 'get sign-off', 'have someone check this', 'hold until reviewed', 'needs approval first'. NOT for making AI text sound human (use content-humanizer or behuman). NOT for reviewing code diffs (use md-review or code-reviewer).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-08-09"}},"isInternal":false,"tokens":1524,"sizeBytes":5915},{"name":"assumption_linter.json","path":"engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/assumption_linter.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/assumption_linter.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Fexpected_outputs%2Fassumption_linter.json -->","frontmatter":{"status":"ok","source":"stdin","total_findings":3,"by_category":{"assumption-just":1,"assumption-obvious":1,"missing-format":1},"verdict":"REVIEW","findings":[{"line":1,"category":"assumption-just","matched":"just","message":"'just' often hides complexity. What's being skipped?","context":"I'll just add a function to export all user data"},{"line":1,"category":"assumption-obvious","matched":"Obviously","message":"Signals an unstated assumption. Is it really obvious?","context":"Obviously we need caching too"},{"line":1,"category":"missing-format","matched":"export all user data","message":"Export/save/fetch mentioned but format not specified (JSON? CSV? API?)","context":"I'll just add a function to export all user data"}]},"isInternal":false,"tokens":262,"sizeBytes":933},{"name":"complexity_checker.json","path":"engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/complexity_checker.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/complexity_checker.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Fexpected_outputs%2Fcomplexity_checker.json -->","frontmatter":{"status":"ok","threshold":"medium","files_analyzed":1,"total_findings":1,"average_score":85,"verdict":"WARN","results":[{"file":"scripts/complexity_checker.py","language":"python","lines":210,"functions":7,"classes":0,"imports":6,"max_nesting":5,"avg_cyclomatic":3.4,"score":85,"findings":[{"rule":"nesting-depth","severity":"warn","message":"Max nesting depth 5 (max 4). Extract or flatten."}]}]},"isInternal":false,"tokens":185,"sizeBytes":584},{"name":"diff_surgeon.json","path":"engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/diff_surgeon.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/diff_surgeon.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Fexpected_outputs%2Fdiff_surgeon.json -->","frontmatter":{"status":"ok","files_in_diff":3,"total_change_lines":45,"noise_lines":4,"noise_ratio":0.09,"verdict":"CLEAN","file_results":[]},"isInternal":false,"tokens":60,"sizeBytes":158},{"name":"goal_verifier.json","path":"engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/goal_verifier.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/expected_outputs/goal_verifier.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Fexpected_outputs%2Fgoal_verifier.json -->","frontmatter":{"status":"ok","source":"plan.md","steps_found":4,"score":4,"max_score":12,"percentage":33.3,"has_final_verification":false,"verdict":"MISSING","step_results":[{"title":"1. Add validation to the form","score":0,"level":"none","has_verify_label":false},{"title":"2. Fix the bug with empty inputs","score":0,"level":"none","has_verify_label":false},{"title":"3. Write test: submit empty form → expect error → verify: test passes","score":2,"level":"reasonable","has_verify_label":true},{"title":"4. Run full test suite → verify: all green","score":2,"level":"reasonable","has_verify_label":true}],"recommendations":["2 step(s) have no verification. Add 'verify: [check]' to each.","No final/end-to-end verification step. Add one at the end."]},"isInternal":false,"tokens":260,"sizeBytes":853},{"name":"anti-patterns.md","path":"engineering/karpathy-coder/skills/karpathy-coder/references/anti-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/references/anti-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Freferences%2Fanti-patterns.md -->","isInternal":false,"tokens":1195,"sizeBytes":4965},{"name":"enforcement-patterns.md","path":"engineering/karpathy-coder/skills/karpathy-coder/references/enforcement-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/references/enforcement-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Freferences%2Fenforcement-patterns.md -->","isInternal":false,"tokens":973,"sizeBytes":3751},{"name":"karpathy-principles.md","path":"engineering/karpathy-coder/skills/karpathy-coder/references/karpathy-principles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/references/karpathy-principles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2Freferences%2Fkarpathy-principles.md -->","isInternal":false,"tokens":860,"sizeBytes":3754},{"name":"SKILL.md","path":"engineering/karpathy-coder/skills/karpathy-coder/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/skills/karpathy-coder/SKILL.md","title":"karpathy-coder","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2Fskills%2Fkarpathy-coder%2FSKILL.md -->","frontmatter":{"name":"karpathy-coder","description":"Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. 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-->","isInternal":false,"tokens":927,"sizeBytes":3613},{"name":"memex-principles.md","path":"engineering/llm-wiki/skills/llm-wiki/references/memex-principles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/skills/llm-wiki/references/memex-principles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2Fskills%2Fllm-wiki%2Freferences%2Fmemex-principles.md -->","isInternal":false,"tokens":959,"sizeBytes":4097},{"name":"obsidian-setup.md","path":"engineering/llm-wiki/skills/llm-wiki/references/obsidian-setup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/skills/llm-wiki/references/obsidian-setup.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2Fskills%2Fllm-wiki%2Freferences%2Fobsidian-setup.md -->","isInternal":false,"tokens":763,"sizeBytes":2991},{"name":"page-formats.md","path":"engineering/llm-wiki/skills/llm-wiki/references/page-formats.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/skills/llm-wiki/references/page-formats.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2Fskills%2Fllm-wiki%2Freferences%2Fpage-formats.md -->","isInternal":false,"tokens":1284,"sizeBytes":5172},{"name":"query-workflow.md","path":"engineering/llm-wiki/skills/llm-wiki/references/query-workflow.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/skills/llm-wiki/references/query-workflow.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2Fskills%2Fllm-wiki%2Freferences%2Fquery-workflow.md -->","isInternal":false,"tokens":791,"sizeBytes":3129},{"name":"wiki-schema.md","path":"engineering/llm-wiki/skills/llm-wiki/references/wiki-schema.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/skills/llm-wiki/references/wiki-schema.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2Fskills%2Fllm-wiki%2Freferences%2Fwiki-schema.md -->","isInternal":false,"tokens":1091,"sizeBytes":4528},{"name":"SKILL.md","path":"engineering/llm-wiki/skills/llm-wiki/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/skills/llm-wiki/SKILL.md","title":"llm-wiki","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2Fskills%2Fllm-wiki%2FSKILL.md -->","frontmatter":{"name":"llm-wiki","description":"Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include \"second brain\", \"Obsidian wiki\", \"personal knowledge management\", \"ingest this paper/article/book\", \"build a research wiki\", \"compound knowledge\", \"Memex\", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.","context":"fork","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["knowledge-management","obsidian","second-brain","pkm","rag-alternative","wiki","karpathy","memex"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2547,"sizeBytes":10364},{"name":"forgetting_policy_template.md","path":"engineering/memory-engineering/skills/memory-engineering/assets/forgetting_policy_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/assets/forgetting_policy_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Fassets%2Fforgetting_policy_template.md -->","isInternal":false,"tokens":1111,"sizeBytes":4511},{"name":"memory_design_spec.example.json","path":"engineering/memory-engineering/skills/memory-engineering/assets/memory_design_spec.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/assets/memory_design_spec.example.json","title":"support-agent memory store (worked example)","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Fassets%2Fmemory_design_spec.example.json -->","frontmatter":{"_comment":"One spec covering every script in the memory-engineering skill. Each top-level block is consumed by a different script; pass this same file to all of them.","_usage":{"memory_cost_profiler.py":"--spec  (reads: name, construction, query, pricing_usd_per_mtok, accuracy)","memory_architecture_picker.py":"--constraints  (reads: name, *_sensitivity/_pressure/_need/growth, hard_constraints)","forgetting_policy_linter.py":"--policy  (reads: name, forgetting, dedup_on_write, consolidation, contradiction_policy, scope, audit_trail, rollback, growth_monitoring)","memory_density_auditor.py":"takes --dir or --jsonl instead of this file"},"name":"support-agent memory store (worked example)","construction":{"records_per_day":400,"prompt_tokens_per_record":12000,"output_tokens_per_record":800,"embedding_tokens_per_record":12000,"colocated_with_queries":true},"query":{"queries_per_day":1200,"prompt_tokens_per_query":2400,"output_tokens_per_query":300,"embedding_tokens_per_query":40},"pricing_usd_per_mtok":{"prompt":3,"output":15,"embedding":0.02},"accuracy":0.72,"query_latency_sensitivity":"high","build_budget_pressure":"medium","recall_need":"high","volume_growth":"high","mutability_need":"medium","hard_constraints":{"max_p99_query_ms":1500,"context_window_tokens":200000,"expected_history_tokens":4000000},"forgetting":{"rule":"ttl","ttl_days":365,"max_records":50000,"decay":"none"},"dedup_on_write":true,"consolidation":{"enabled":true,"cadence":"weekly"},"contradiction_policy":"surface","scope":{"read":["support-agents"],"write":["memory-writer-service"]},"audit_trail":{"timestamp":true,"source_attribution":true},"rollback":{"supported":true,"delete_path":"api"},"growth_monitoring":{"tracks_slope":false,"baseline_only":true}},"isInternal":false,"tokens":601,"sizeBytes":2098},{"name":"memory_engineer_worksheet.md","path":"engineering/memory-engineering/skills/memory-engineering/assets/memory_engineer_worksheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/assets/memory_engineer_worksheet.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Fassets%2Fmemory_engineer_worksheet.md -->","isInternal":false,"tokens":1272,"sizeBytes":5439},{"name":"forgetting_policy_design.md","path":"engineering/memory-engineering/skills/memory-engineering/references/forgetting_policy_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/references/forgetting_policy_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Freferences%2Fforgetting_policy_design.md -->","isInternal":false,"tokens":2167,"sizeBytes":8877},{"name":"memory_control_and_governance.md","path":"engineering/memory-engineering/skills/memory-engineering/references/memory_control_and_governance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/references/memory_control_and_governance.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Freferences%2Fmemory_control_and_governance.md -->","isInternal":false,"tokens":1726,"sizeBytes":7544},{"name":"memory_cost_canon.md","path":"engineering/memory-engineering/skills/memory-engineering/references/memory_cost_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/references/memory_cost_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Freferences%2Fmemory_cost_canon.md -->","isInternal":false,"tokens":1736,"sizeBytes":7030},{"name":"what_to_keep.md","path":"engineering/memory-engineering/skills/memory-engineering/references/what_to_keep.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/references/what_to_keep.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2Freferences%2Fwhat_to_keep.md -->","isInternal":false,"tokens":1852,"sizeBytes":7786},{"name":"SKILL.md","path":"engineering/memory-engineering/skills/memory-engineering/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/skills/memory-engineering/SKILL.md","title":"memory-engineering","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2Fskills%2Fmemory-engineering%2FSKILL.md -->","frontmatter":{"name":"memory-engineering","description":"Use when designing, reviewing, or paying for an agent memory system — adding memory to an agent, choosing between long-context / RAG / graph / agentic memory, auditing what a CLAUDE.md or memory directory actually holds, deciding what to keep and what to expire, or when a memory store keeps growing and nobody has said what leaves it. Prices the write path, picks which cost to pay, classifies records as facts / skills / logs, and refuses a design that has no forgetting policy.","argument-hint":"[optional: path to a memory dir, design spec JSON, or a question]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Four-lens synthesis (Stanford / Microsoft / Anthropic / Nvidia) + 4 deterministic stdlib scripts, with a blocking forgetting gate","distinct_from":"llm-wiki (maintains one specific markdown vault; this audits and prices any memory system); skillopt-sleep (runs a nightly consolidation loop; this decides whether that loop's output is worth keeping); agent-harness (bounds a task loop; this bounds a store)"}},"isInternal":false,"tokens":1619,"sizeBytes":6720},{"name":"SKILL.md","path":"engineering/minimalist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/minimalist/SKILL.md","title":"minimalist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fminimalist%2FSKILL.md -->","frontmatter":{"name":"minimalist","description":"Use when the user asks to write code efficiently, avoid over-engineering, reduce dependencies, or prevent unnecessary abstractions. Enforces a strict efficiency ladder: YAGNI, reuse, stdlib, native platform, existing deps — before writing any new code."},"isInternal":false,"tokens":741,"sizeBytes":3244},{"name":"SKILL.md","path":"engineering/prompt-governance/skills/prompt-governance/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/prompt-governance/skills/prompt-governance/SKILL.md","title":"prompt-governance","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fprompt-governance%2Fskills%2Fprompt-governance%2FSKILL.md -->","frontmatter":{"name":"prompt-governance","description":"Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production AI features. Triggers: 'manage prompts in production', 'prompt versioning', 'prompt regression', 'prompt A/B test', 'prompt registry', 'eval pipeline'. NOT for writing or improving individual prompts (use senior-prompt-engineer). NOT for RAG pipeline design (use rag-architect). NOT for LLM cost reduction (use llm-cost-optimizer)."},"isInternal":false,"tokens":2416,"sizeBytes":11213},{"name":"pretooluse_hook_canon.md","path":"engineering/security-guidance/skills/security-guidance/references/pretooluse_hook_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/security-guidance/skills/security-guidance/references/pretooluse_hook_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fsecurity-guidance%2Fskills%2Fsecurity-guidance%2Freferences%2Fpretooluse_hook_canon.md -->","isInternal":false,"tokens":1842,"sizeBytes":8085},{"name":"SKILL.md","path":"engineering/security-guidance/skills/security-guidance/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/security-guidance/skills/security-guidance/SKILL.md","title":"security-guidance","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fsecurity-guidance%2Fskills%2Fsecurity-guidance%2FSKILL.md -->","frontmatter":{"name":"security-guidance","description":"PreToolUse security-anti-pattern hook for Claude Code. Catches 12 common security risks (command injection, XSS, SQL injection, unsafe deserialization, GitHub Actions workflow injection, eval/new Function code injection) BEFORE the Edit/Write/MultiEdit operation completes. Session-state caching prevents duplicate warnings on the same file+rule combo. Stdlib only — no dependencies. Use when you want a safety net during Claude Code sessions that touch security-sensitive code (auth, payments, user input handling, IaC). Disable with ENABLE_SECURITY_REMINDER=0 if you need to perform a verified-safe operation that would otherwise trip a pattern. Triggers — \"add security hook\", \"block unsafe code\", \"detect command injection before write\", \"prevent SQL injection patterns\", \"security warning hook\"."},"isInternal":false,"tokens":1818,"sizeBytes":7823},{"name":"report.example.json","path":"engineering/skill-doctor/skills/skill-doctor/assets/report.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skill-doctor/skills/skill-doctor/assets/report.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskill-doctor%2Fskills%2Fskill-doctor%2Fassets%2Freport.example.json -->","frontmatter":{"_comment":"Shape score_aggregator.py emits and render_report.py consumes. Never hand-author this file — it is the aggregator's output, and the renderer refuses a report missing scores/stats/top_findings/suggestions.","title":"Agent Skill Report","generated_at":"2026-01-15T10:06:00+00:00","harness":"claude","handle":"example-repo","stats":{"sessions_analyzed":9,"sessions_scanned":41,"skills_found":6,"skills_used":3,"window_days":45},"scores":{"efficiency":0.6444,"code_quality":0.6,"skill_coverage":0.4444,"overall":0.5989},"grade":"F","top_findings":["Files were re-read verbatim in 4 of 9 sessions before any edit was attempted","deploy-checklist never fired in 3 sessions whose first user message contained the word 'deploy'","Two sessions repeated a fix-test cycle three times on the same lint failure a pre-commit run would have caught"],"suggestions":[{"skill":"deploy-checklist","change":"Rewrite the trigger description so the skill fires on 'deploy', 'release', and 'ship'.","evidence":"In 0f3a2b1c-example-claude-session the user asked to 'deploy the staging build'; the skill never fired.","sessions":["0f3a2b1c-example-claude-session"],"proposed_path":"proposed/deploy-checklist/SKILL.md","diff":"--- a/SKILL.md\n+++ b/SKILL.md\n@@ -1,4 +1,4 @@\n ---\n name: deploy-checklist\n-description: Walk the deployment checklist.\n+description: Use when the user asks to deploy, release, or ship a build — walks the pre-deploy checklist including migrations and rollback tags.\n ---\n"}],"session_scores":{"0f3a2b1c-example-claude-session":{"efficiency":{"label":"mostly_inefficient","reason":"Three fix-test cycles on the same import error; a lint run before the first edit would have caught it."},"code_quality":{"label":"block","reason":"Debug print left in src/api/client.py; retry helper duplicates existing backoff logic."}}},"warnings":[]},"isInternal":false,"tokens":594,"sizeBytes":2132},{"name":"session_scores.example.json","path":"engineering/skill-doctor/skills/skill-doctor/assets/session_scores.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skill-doctor/skills/skill-doctor/assets/session_scores.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskill-doctor%2Fskills%2Fskill-doctor%2Fassets%2Fsession_scores.example.json -->","frontmatter":{"_comment":"Shape the scoring agent fills after judging each sampled transcript against scorers/efficiency.md and scorers/code-quality.md. Get a pre-filled skeleton with: python scripts/score_aggregator.py --inventory RUN/inventory.json --emit-template. Labels must come from the rubric tables; score_aggregator.py derives all numbers and rejects anything else.","top_findings":["Files were re-read verbatim in 4 of 9 sessions before any edit was attempted","deploy-checklist never fired in 3 sessions whose first user message contained the word 'deploy'","Two sessions repeated a fix-test cycle three times on the same lint failure a pre-commit run would have caught"],"sessions":[{"session_id":"0f3a2b1c-example-claude-session","harness":"claude","efficiency":{"label":"mostly_inefficient","reason":"Three fix-test cycles on the same import error; running the repo's lint target once before the first edit would have caught it."},"code_quality":{"label":"block","reason":"Left a debug print in src/api/client.py and the new retry helper duplicates the backoff logic already in src/util/net.py."}},{"session_id":"rollout-2026-01-12-example-codex","harness":"codex","efficiency":{"label":"mostly_efficient","reason":"One duplicated read of the config file early on; the rest of the run was direct with batched searches."},"code_quality":{"label":"insufficient_evidence","reason":"Research-only session; no diff was produced in the transcript."}}]},"isInternal":false,"tokens":399,"sizeBytes":1675},{"name":"suggestions.example.json","path":"engineering/skill-doctor/skills/skill-doctor/assets/suggestions.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skill-doctor/skills/skill-doctor/assets/suggestions.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskill-doctor%2Fskills%2Fskill-doctor%2Fassets%2Fsuggestions.example.json -->","frontmatter":{"_comment":"Shape the drafting agent writes in step 3. 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Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer)."},"isInternal":false,"tokens":933,"sizeBytes":4241},{"name":"eval_case_spec.example.json","path":"engineering/skills/agent-regression-evals/assets/eval_case_spec.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/agent-regression-evals/assets/eval_case_spec.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fagent-regression-evals%2Fassets%2Feval_case_spec.example.json -->","frontmatter":{"refund-lookup":{"expected":[{"tool":"get_order","args":{"order_id":"A-1001"}},{"tool":"get_refund_policy","args":{}},{"tool":"issue_refund","args":{"order_id":"A-1001"}}],"match":"strict","args_match":"subset","forbidden":["delete_order"],"max_calls":6},"faq-shipping":{"expected":[{"tool":"search_kb","args":{}}],"match":"superset","args_match":"ignore","forbidden":["issue_refund"]}},"isInternal":false,"tokens":197,"sizeBytes":669},{"name":"eval_statistics.md","path":"engineering/skills/agent-regression-evals/references/eval_statistics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/agent-regression-evals/references/eval_statistics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fagent-regression-evals%2Freferences%2Feval_statistics.md -->","isInternal":false,"tokens":1455,"sizeBytes":4964},{"name":"flaky_cases_and_quarantine.md","path":"engineering/skills/agent-regression-evals/references/flaky_cases_and_quarantine.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/agent-regression-evals/references/flaky_cases_and_quarantine.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fagent-regression-evals%2Freferences%2Fflaky_cases_and_quarantine.md -->","isInternal":false,"tokens":1334,"sizeBytes":4935},{"name":"trajectory_grading.md","path":"engineering/skills/agent-regression-evals/references/trajectory_grading.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/agent-regression-evals/references/trajectory_grading.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fagent-regression-evals%2Freferences%2Ftrajectory_grading.md -->","isInternal":false,"tokens":1083,"sizeBytes":4249},{"name":"SKILL.md","path":"engineering/skills/agent-regression-evals/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/agent-regression-evals/SKILL.md","title":"agent-regression-evals","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fagent-regression-evals%2FSKILL.md -->","frontmatter":{"name":"agent-regression-evals","description":"Use when an agent, prompt, model or tool change needs proof it did not make the agent worse — setting up a regression eval suite, deciding whether a pass-rate drop is real or noise, grading tool-call trajectories, finding flaky eval cases, or wiring an eval gate into CI that blocks the merge. 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Emergency response team activated\n2. {emergency_action_1}\n3. {emergency_action_2}\n\nWar Room: {war_room_location}\nBridge Line: {conference_bridge}\n\nNext Update: {next_update_time}\n\nIncident Commander: {incident_commander}\nExecutive On-Call: {executive_on_call}\n","urgency":"emergency","delivery_methods":["email","sms","phone_call"]}],"escalation_matrix":{"level_1":{"trigger":"Single component failure","response_time_minutes":5,"contacts":["on_call_engineer","migration_lead"],"actions":["Investigate issue","Attempt automated remediation","Monitor closely"]},"level_2":{"trigger":"Multiple component failures or single critical failure","response_time_minutes":2,"contacts":["senior_engineer","team_lead","devops_lead"],"actions":["Initiate rollback","Establish war room","Notify stakeholders"]},"level_3":{"trigger":"System-wide failure or data corruption","response_time_minutes":1,"contacts":["engineering_manager","cto","incident_commander"],"actions":["Emergency rollback","All 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burn rate detected for Feature Availability","description":"Error budget consumption rate is 6x normal, will exhaust 5% of monthly budget"}},{"name":"Feature Availability Burn Rate 10% Alert","description":"Alert when Feature Availability is consuming error budget at 3x rate","severity":"info","short_window":"2h","long_window":"1d","burn_rate_threshold":3,"budget_consumed":"10%","condition":"((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 3) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 3)","annotations":{"summary":"High burn rate detected for Feature Availability","description":"Error budget consumption rate is 3x normal, will exhaust 10% of monthly budget"}},{"name":"Feature Availability Burn Rate 10% Alert","description":"Alert when Feature Availability is consuming error budget at 1x rate","severity":"info","short_window":"6h","long_window":"3d","burn_rate_threshold":1,"budget_consumed":"10%","condition":"((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 1) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 1)","annotations":{"summary":"High burn rate detected for Feature Availability","description":"Error budget consumption rate is 1x normal, will exhaust 10% of monthly budget"}}]}],"sla_recommendations":{"applicable":true,"service":"payment-service","commitments":[{"metric":"Availability","target":0.9989,"target_display":"99.89%","measurement_window":"monthly","measurement_method":"Uptime monitoring with 1-minute granularity"},{"metric":"Feature Availability","target":0.9989,"target_display":"99.89%","measurement_window":"monthly","measurement_method":"Uptime monitoring with 1-minute granularity"}],"penalties":[{"breach_threshold":"< 99.99%","credit_percentage":10},{"breach_threshold":"< 99.9%","credit_percentage":25},{"breach_threshold":"< 99%","credit_percentage":50}],"measurement_methodology":"External synthetic monitoring from multiple geographic locations","exclusions":["Planned maintenance windows (with 72h advance notice)","Customer-side network or infrastructure issues","Force majeure events","Third-party service dependencies beyond our control"]},"monitoring_recommendations":{"metrics":{"collection":"Prometheus with service discovery","retention":"90 days for raw metrics, 1 year for aggregated","alerting":"Prometheus Alertmanager with multi-window burn rate alerts"},"logging":{"format":"Structured JSON logs with correlation IDs","aggregation":"ELK stack or equivalent with proper indexing","retention":"30 days for debug logs, 90 days for error logs"},"tracing":{"sampling":"Adaptive sampling with 1% base rate","storage":"Jaeger or Zipkin with 7-day retention","integration":"OpenTelemetry instrumentation"}},"implementation_guide":{"prerequisites":["Service instrumented with metrics collection (Prometheus format)","Structured logging with correlation IDs","Monitoring infrastructure (Prometheus, Grafana, Alertmanager)","Incident response processes and escalation policies"],"implementation_steps":[{"step":1,"title":"Instrument Service","description":"Add metrics collection for all defined SLIs","estimated_effort":"1-2 days"},{"step":2,"title":"Configure Recording Rules","description":"Set up Prometheus recording rules for SLI calculations","estimated_effort":"4-8 hours"},{"step":3,"title":"Implement Burn Rate Alerts","description":"Configure multi-window burn rate alerting rules","estimated_effort":"1 day"},{"step":4,"title":"Create SLO Dashboard","description":"Build Grafana dashboard for SLO tracking and error budget monitoring","estimated_effort":"4-6 hours"},{"step":5,"title":"Test and Validate","description":"Test alerting and validate SLI measurements against expectations","estimated_effort":"1-2 days"},{"step":6,"title":"Documentation and Training","description":"Document runbooks and train team on SLO monitoring","estimated_effort":"1 day"}],"validation_checklist":["All SLIs produce expected metric values","Burn rate alerts fire correctly during simulated outages","Error budget calculations match manual verification","Dashboard displays accurate SLO achievement rates","Alert routing reaches correct escalation paths","Runbooks are complete and tested"]}},"isInternal":false,"tokens":5491,"sizeBytes":22072},{"name":"README.md","path":"engineering/skills/observability-designer/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/observability-designer/README.md","title":"Observability-designer Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fobservability-designer%2FREADME.md -->","isInternal":false,"tokens":2585,"sizeBytes":11877},{"name":"alert_design_patterns.md","path":"engineering/skills/observability-designer/references/alert_design_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/observability-designer/references/alert_design_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fobservability-designer%2Freferences%2Falert_design_patterns.md -->","isInternal":false,"tokens":3048,"sizeBytes":11972},{"name":"dashboard_best_practices.md","path":"engineering/skills/observability-designer/references/dashboard_best_practices.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/observability-designer/references/dashboard_best_practices.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fobservability-designer%2Freferences%2Fdashboard_best_practices.md -->","isInternal":false,"tokens":3452,"sizeBytes":14117},{"name":"slo_cookbook.md","path":"engineering/skills/observability-designer/references/slo_cookbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/observability-designer/references/slo_cookbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fobservability-designer%2Freferences%2Fslo_cookbook.md -->","isInternal":false,"tokens":2690,"sizeBytes":10608},{"name":"SKILL.md","path":"engineering/skills/observability-designer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/observability-designer/SKILL.md","title":"observability-designer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fobservability-designer%2FSKILL.md -->","frontmatter":{"name":"observability-designer","description":"Design production-ready observability strategies combining metrics, logs, and traces. Includes SLI/SLO design, golden-signals monitoring, alert optimization. Use when adding observability to a new service, refactoring alerting that is too noisy, or designing an SLO program before scaling production load."},"isInternal":false,"tokens":2723,"sizeBytes":13894},{"name":"optimization-playbook.md","path":"engineering/skills/performance-profiler/references/optimization-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/performance-profiler/references/optimization-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fperformance-profiler%2Freferences%2Foptimization-playbook.md -->","isInternal":false,"tokens":849,"sizeBytes":3262},{"name":"profiling-recipes.md","path":"engineering/skills/performance-profiler/references/profiling-recipes.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/performance-profiler/references/profiling-recipes.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fperformance-profiler%2Freferences%2Fprofiling-recipes.md -->","isInternal":false,"tokens":3205,"sizeBytes":11531},{"name":"SKILL.md","path":"engineering/skills/performance-profiler/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/performance-profiler/SKILL.md","title":"performance-profiler","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fperformance-profiler%2FSKILL.md -->","frontmatter":{"name":"performance-profiler","description":"Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks, generates flamegraphs, analyzes bundle sizes, optimizes database queries, runs load tests with k6 and Artillery. Always measures before and after. Use when investigating a slow endpoint, planning a performance budget, or hunting a memory leak in production."},"isInternal":false,"tokens":622,"sizeBytes":2761},{"name":"SKILL.md","path":"engineering/skills/pr-review-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/pr-review-expert/SKILL.md","title":"pr-review-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fpr-review-expert%2FSKILL.md -->","frontmatter":{"name":"pr-review-expert","description":"Use when the user asks to review pull requests, analyze code changes, check for security issues in PRs, or assess code quality of diffs."},"isInternal":false,"tokens":3413,"sizeBytes":12647},{"name":"chunking_strategies_comparison.md","path":"engineering/skills/rag-architect/references/chunking_strategies_comparison.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/rag-architect/references/chunking_strategies_comparison.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Frag-architect%2Freferences%2Fchunking_strategies_comparison.md -->","isInternal":false,"tokens":2329,"sizeBytes":10181},{"name":"embedding_model_benchmark.md","path":"engineering/skills/rag-architect/references/embedding_model_benchmark.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/rag-architect/references/embedding_model_benchmark.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Frag-architect%2Freferences%2Fembedding_model_benchmark.md -->","isInternal":false,"tokens":3854,"sizeBytes":12729},{"name":"rag_evaluation_framework.md","path":"engineering/skills/rag-architect/references/rag_evaluation_framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/rag-architect/references/rag_evaluation_framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Frag-architect%2Freferences%2Frag_evaluation_framework.md -->","isInternal":false,"tokens":3157,"sizeBytes":15137},{"name":"SKILL.md","path":"engineering/skills/rag-architect/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/rag-architect/SKILL.md","title":"rag-architect","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Frag-architect%2FSKILL.md -->","frontmatter":{"name":"rag-architect","description":"Use when the user asks to design a RAG pipeline, choose a chunking strategy or embedding model, pick a vector database, or evaluate retrieval quality (precision@k, recall@k, NDCG). Examples: 'design a RAG system for our docs', 'what chunk size should I use for this corpus', 'evaluate my retriever against ground truth'. NOT for general LLM cost tuning (use llm-cost-optimizer) or agent loops over retrieval (use agenthub)."},"isInternal":false,"tokens":1116,"sizeBytes":4506},{"name":"runbook-templates.md","path":"engineering/skills/runbook-generator/references/runbook-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/runbook-generator/references/runbook-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Frunbook-generator%2Freferences%2Frunbook-templates.md -->","isInternal":false,"tokens":225,"sizeBytes":1079},{"name":"SKILL.md","path":"engineering/skills/runbook-generator/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/runbook-generator/SKILL.md","title":"runbook-generator","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Frunbook-generator%2FSKILL.md -->","frontmatter":{"name":"runbook-generator","description":"Generate operational runbooks from a service name — deployment, incident response, maintenance, and rollback workflows. Templated structure customizable per environment. Use when documenting on-call procedures for a new service, standardizing incident response across teams, or producing runbooks before launching to production."},"isInternal":false,"tokens":431,"sizeBytes":2139},{"name":"cloud_secret_stores.md","path":"engineering/skills/secrets-vault-manager/references/cloud_secret_stores.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/secrets-vault-manager/references/cloud_secret_stores.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsecrets-vault-manager%2Freferences%2Fcloud_secret_stores.md -->","isInternal":false,"tokens":2671,"sizeBytes":11466},{"name":"emergency_procedures.md","path":"engineering/skills/secrets-vault-manager/references/emergency_procedures.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/secrets-vault-manager/references/emergency_procedures.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsecrets-vault-manager%2Freferences%2Femergency_procedures.md -->","isInternal":false,"tokens":2281,"sizeBytes":9939},{"name":"vault_patterns.md","path":"engineering/skills/secrets-vault-manager/references/vault_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/secrets-vault-manager/references/vault_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsecrets-vault-manager%2Freferences%2Fvault_patterns.md -->","isInternal":false,"tokens":2529,"sizeBytes":10496},{"name":"SKILL.md","path":"engineering/skills/secrets-vault-manager/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/secrets-vault-manager/SKILL.md","title":"secrets-vault-manager","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsecrets-vault-manager%2FSKILL.md -->","frontmatter":{"name":"secrets-vault-manager","description":"Use when the user asks to set up secret management infrastructure, integrate HashiCorp Vault, configure cloud secret stores (AWS Secrets Manager, Azure Key Vault, GCP Secret Manager), implement secret rotation, or audit secret access patterns."},"isInternal":false,"tokens":3337,"sizeBytes":14586},{"name":"SKILL.md","path":"engineering/skills/self-eval/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/self-eval/SKILL.md","title":"self-eval","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fself-eval%2FSKILL.md -->","frontmatter":{"name":"self-eval","description":"Honestly evaluate AI work quality using a two-axis scoring system. Use after completing a task, code review, or work session to get an unbiased assessment. Detects score inflation, forces devil's advocate reasoning, and persists scores across sessions.","license":"MIT"},"isInternal":false,"tokens":1898,"sizeBytes":8457},{"name":"checks.md","path":"engineering/skills/ship-gate/references/checks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/ship-gate/references/checks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fship-gate%2Freferences%2Fchecks.md -->","isInternal":false,"tokens":4622,"sizeBytes":19088},{"name":"patterns.md","path":"engineering/skills/ship-gate/references/patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/ship-gate/references/patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fship-gate%2Freferences%2Fpatterns.md -->","isInternal":false,"tokens":5526,"sizeBytes":16780},{"name":"SKILL.md","path":"engineering/skills/ship-gate/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/ship-gate/SKILL.md","title":"ship-gate","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fship-gate%2FSKILL.md -->","frontmatter":{"name":"ship-gate","description":"Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Intercepts deploy commands and blocks until critical items pass. Stack-agnostic. Use for \"run ship gate\", \"am I ready to ship\", \"pre-launch audit\", \"can I deploy\", \"push to production\", \"go live checklist\", \"preflight check\". Not for CI/CD setup or infra provisioning.\n","license":"MIT","metadata":{"author":"Rajaraman Arumugam","version":"1.0.0"}},"isInternal":false,"tokens":1707,"sizeBytes":6606},{"name":"threat-model.md","path":"engineering/skills/skill-security-auditor/references/threat-model.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-security-auditor/references/threat-model.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-security-auditor%2Freferences%2Fthreat-model.md -->","isInternal":false,"tokens":2302,"sizeBytes":10237},{"name":"SKILL.md","path":"engineering/skills/skill-security-auditor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-security-auditor/SKILL.md","title":"skill-security-auditor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-security-auditor%2FSKILL.md -->","frontmatter":{"name":"skill-security-auditor","description":"Security audit and vulnerability scanner for AI agent skills before installation. Use when: (1) evaluating a skill from an untrusted source, (2) auditing a skill directory or git repo URL for malicious code, (3) pre-install security gate for Claude Code plugins, OpenClaw skills, or Codex skills, (4) scanning Python scripts for dangerous patterns like os.system, eval, subprocess, network exfiltration, (5) detecting prompt injection in SKILL.md files, (6) checking dependency supply chain risks, (7) verifying file system access stays within skill boundaries. Triggers: \"audit this skill\", \"is this skill safe\", \"scan skill for security\", \"check skill before install\", \"skill security check\", \"skill vulnerability scan\".\n"},"isInternal":false,"tokens":1998,"sizeBytes":7982},{"name":"sample_text_analysis.json","path":"engineering/skills/skill-tester/assets/sample-skill/expected_outputs/sample_text_analysis.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/assets/sample-skill/expected_outputs/sample_text_analysis.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Fassets%2Fsample-skill%2Fexpected_outputs%2Fsample_text_analysis.json -->","frontmatter":{"file":"assets/sample_text.txt","file_size":855,"total_words":116,"unique_words":87,"total_characters":855,"lines":19,"average_word_length":4.7,"most_frequent":{"word":"the","count":5}},"isInternal":false,"tokens":85,"sizeBytes":234},{"name":"README.md","path":"engineering/skills/skill-tester/assets/sample-skill/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/assets/sample-skill/README.md","title":"Sample-skill Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Fassets%2Fsample-skill%2FREADME.md -->","isInternal":false,"tokens":200,"sizeBytes":976},{"name":"api-reference.md","path":"engineering/skills/skill-tester/assets/sample-skill/references/api-reference.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/assets/sample-skill/references/api-reference.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Fassets%2Fsample-skill%2Freferences%2Fapi-reference.md -->","isInternal":false,"tokens":598,"sizeBytes":2520},{"name":"SKILL.md","path":"engineering/skills/skill-tester/assets/sample-skill/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/assets/sample-skill/SKILL.md","title":"sample-text-processor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Fassets%2Fsample-skill%2FSKILL.md -->","frontmatter":{"name":"sample-text-processor","description":"Reference BASIC-tier skill used as a fixture by skill-tester. Counts words and characters and applies basic text transformations. Use when validating skill-tester itself or when you need a minimal, known-good skill layout to copy. Not a production skill."},"isInternal":false,"tokens":1153,"sizeBytes":5829},{"name":"sample_validation_report.json","path":"engineering/skills/skill-tester/expected_outputs/sample_validation_report.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/expected_outputs/sample_validation_report.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Fexpected_outputs%2Fsample_validation_report.json -->","frontmatter":{"skill_path":"assets/sample-skill","timestamp":"2026-02-16T16:41:00Z","overall_score":85,"compliance_level":"GOOD","checks":{"skill_md_exists":{"passed":true,"message":"SKILL.md found","score":1},"readme_exists":{"passed":true,"message":"README.md found","score":1},"skill_md_length":{"passed":true,"message":"SKILL.md has 145 lines (≥100)","score":1},"frontmatter_complete":{"passed":true,"message":"All required frontmatter fields present","score":1},"required_sections":{"passed":true,"message":"All required sections present","score":1},"dir_scripts_exists":{"passed":true,"message":"scripts/ directory found","score":1},"min_scripts_count":{"passed":true,"message":"Found 1 Python scripts (≥1)","score":1},"script_syntax_text_processor.py":{"passed":true,"message":"text_processor.py has valid Python syntax","score":1},"script_argparse_text_processor.py":{"passed":true,"message":"Uses argparse in text_processor.py","score":1},"script_main_guard_text_processor.py":{"passed":true,"message":"Has main guard in text_processor.py","score":1},"tier_compliance":{"passed":true,"message":"Meets BASIC tier requirements","score":1}},"warnings":[],"errors":[],"suggestions":["Consider adding optional directories: references, expected_outputs"]},"isInternal":false,"tokens":491,"sizeBytes":1702},{"name":"README.md","path":"engineering/skills/skill-tester/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/README.md","title":"Skill-tester Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2FREADME.md -->","isInternal":false,"tokens":1576,"sizeBytes":6829},{"name":"quality-scoring-rubric.md","path":"engineering/skills/skill-tester/references/quality-scoring-rubric.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/references/quality-scoring-rubric.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Freferences%2Fquality-scoring-rubric.md -->","isInternal":false,"tokens":4853,"sizeBytes":20717},{"name":"skill-structure-specification.md","path":"engineering/skills/skill-tester/references/skill-structure-specification.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/references/skill-structure-specification.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Freferences%2Fskill-structure-specification.md -->","isInternal":false,"tokens":2379,"sizeBytes":11945},{"name":"tier-requirements-matrix.md","path":"engineering/skills/skill-tester/references/tier-requirements-matrix.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/references/tier-requirements-matrix.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2Freferences%2Ftier-requirements-matrix.md -->","isInternal":false,"tokens":3636,"sizeBytes":17998},{"name":"SKILL.md","path":"engineering/skills/skill-tester/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/skill-tester/SKILL.md","title":"skill-tester","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fskill-tester%2FSKILL.md -->","frontmatter":{"name":"skill-tester","description":"Validate, test, and score the quality of skills within the claude-skills ecosystem. 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fspec-driven-workflow%2Freferences%2Fspec_format_guide.md -->","isInternal":false,"tokens":4541,"sizeBytes":19127},{"name":"SKILL.md","path":"engineering/skills/spec-driven-workflow/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/spec-driven-workflow/SKILL.md","title":"spec-driven-workflow","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fspec-driven-workflow%2FSKILL.md -->","frontmatter":{"name":"spec-driven-workflow","description":"Use when the user asks to write specs before code, define acceptance criteria, plan features before implementation, generate tests from specifications, or follow spec-first development practices."},"isInternal":false,"tokens":3499,"sizeBytes":15646},{"name":"optimization_guide.md","path":"engineering/skills/sql-database-assistant/references/optimization_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/sql-database-assistant/references/optimization_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsql-database-assistant%2Freferences%2Foptimization_guide.md -->","isInternal":false,"tokens":2704,"sizeBytes":10699},{"name":"orm_patterns.md","path":"engineering/skills/sql-database-assistant/references/orm_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/sql-database-assistant/references/orm_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsql-database-assistant%2Freferences%2Form_patterns.md -->","isInternal":false,"tokens":3229,"sizeBytes":12565},{"name":"query_patterns.md","path":"engineering/skills/sql-database-assistant/references/query_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/sql-database-assistant/references/query_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsql-database-assistant%2Freferences%2Fquery_patterns.md -->","isInternal":false,"tokens":2644,"sizeBytes":9787},{"name":"SKILL.md","path":"engineering/skills/sql-database-assistant/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/sql-database-assistant/SKILL.md","title":"sql-database-assistant","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Fsql-database-assistant%2FSKILL.md -->","frontmatter":{"name":"sql-database-assistant","description":"Use when the user asks to write SQL queries, optimize database performance, generate migrations, explore database schemas, or work with ORMs like Prisma, Drizzle, TypeORM, or 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-->","isInternal":false,"tokens":1315,"sizeBytes":5291},{"name":"lifecycle.md","path":"engineering/skills/tc-tracker/references/lifecycle.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/tc-tracker/references/lifecycle.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Ftc-tracker%2Freferences%2Flifecycle.md -->","isInternal":false,"tokens":908,"sizeBytes":4037},{"name":"tc-schema.md","path":"engineering/skills/tc-tracker/references/tc-schema.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/tc-tracker/references/tc-schema.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Ftc-tracker%2Freferences%2Ftc-schema.md -->","isInternal":false,"tokens":1598,"sizeBytes":5386},{"name":"SKILL.md","path":"engineering/skills/tc-tracker/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/tc-tracker/SKILL.md","title":"tc-tracker","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Ftc-tracker%2FSKILL.md -->","frontmatter":{"name":"tc-tracker","description":"Use when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions. Covers init/create/update/status/resume/close/export workflows for structured code change documentation."},"isInternal":false,"tokens":2487,"sizeBytes":10325},{"name":"historical_debt_2024-01-15.json","path":"engineering/skills/tech-debt-tracker/assets/historical_debt_2024-01-15.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skills/tech-debt-tracker/assets/historical_debt_2024-01-15.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskills%2Ftech-debt-tracker%2Fassets%2Fhistorical_debt_2024-01-15.json -->","frontmatter":{"scan_metadata":{"directory":"/project/src","scan_date":"2024-01-15T09:00:00","scanner_version":"1.0.0"},"summary":{"total_files_scanned":25,"total_lines_scanned":12543,"total_debt_items":28,"health_score":68.5,"debt_density":1.12},"debt_items":[{"id":"DEBT-0001","type":"large_function","description":"create_user function in user_service.py is 89 lines long","file_path":"src/user_service.py","severity":"high","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0002","type":"duplicate_code","description":"Password validation logic duplicated in 3 locations","file_path":"src/user_service.py","severity":"medium","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0003","type":"security_risk","description":"Hardcoded API key in payment_processor.py","file_path":"src/payment_processor.py","severity":"critical","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0004","type":"high_complexity","description":"process_payment function has cyclomatic complexity of 24","file_path":"src/payment_processor.py","severity":"high","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0005","type":"missing_docstring","description":"PaymentProcessor class missing docstring","file_path":"src/payment_processor.py","severity":"low","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0006","type":"todo_comment","description":"TODO: Move this to configuration file","file_path":"src/user_service.py","severity":"low","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0007","type":"empty_catch_blocks","description":"Empty catch block in update_user 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comments","file_path":"src/frontend.js","severity":"low","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0012","type":"global_variables","description":"Global variable userCache should be encapsulated","file_path":"src/frontend.js","severity":"medium","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0013","type":"synchronous_ajax","description":"Synchronous AJAX call blocks UI thread","file_path":"src/frontend.js","severity":"high","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0014","type":"hardcoded_values","description":"Tax rates hardcoded in payment processing logic","file_path":"src/payment_processor.py","severity":"medium","detected_date":"2024-01-15T09:00:00","status":"identified"},{"id":"DEBT-0015","type":"no_error_handling","description":"API calls without proper error 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Prevents the agent from calling methods, imports, or variables that do not provably exist in the user's installed version."},"isInternal":false,"tokens":776,"sizeBytes":3353},{"name":"module-patterns.md","path":"engineering/terraform-patterns/skills/terraform-patterns/references/module-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/terraform-patterns/skills/terraform-patterns/references/module-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fterraform-patterns%2Fskills%2Fterraform-patterns%2Freferences%2Fmodule-patterns.md -->","isInternal":false,"tokens":2581,"sizeBytes":9900},{"name":"state-management.md","path":"engineering/terraform-patterns/skills/terraform-patterns/references/state-management.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/terraform-patterns/skills/terraform-patterns/references/state-management.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fterraform-patterns%2Fskills%2Fterraform-patterns%2Freferences%2Fstate-management.md -->","isInternal":false,"tokens":3030,"sizeBytes":12177},{"name":"SKILL.md","path":"engineering/terraform-patterns/skills/terraform-patterns/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/terraform-patterns/skills/terraform-patterns/SKILL.md","title":"terraform-patterns","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fterraform-patterns%2Fskills%2Fterraform-patterns%2FSKILL.md -->","frontmatter":{"name":"terraform-patterns","description":"Terraform infrastructure-as-code agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Covers module design patterns, state management strategies, provider configuration, security hardening, policy-as-code with Sentinel/OPA, and CI/CD plan/apply workflows. Use when: user wants to design Terraform modules, manage state backends, review Terraform security, implement multi-region deployments, or follow IaC best practices.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"engineering","updated":"2026-03-15"}},"isInternal":false,"tokens":5390,"sizeBytes":22320},{"name":"firecrawl-technical-guide.md","path":"engineering/universal-scraping-architect/skills/universal-scraping-architect/references/firecrawl-technical-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/universal-scraping-architect/skills/universal-scraping-architect/references/firecrawl-technical-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Funiversal-scraping-architect%2Fskills%2Funiversal-scraping-architect%2Freferences%2Ffirecrawl-technical-guide.md -->","isInternal":false,"tokens":622,"sizeBytes":2711},{"name":"local-extraction-patterns.md","path":"engineering/universal-scraping-architect/skills/universal-scraping-architect/references/local-extraction-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/universal-scraping-architect/skills/universal-scraping-architect/references/local-extraction-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Funiversal-scraping-architect%2Fskills%2Funiversal-scraping-architect%2Freferences%2Flocal-extraction-patterns.md -->","isInternal":false,"tokens":609,"sizeBytes":2571},{"name":"scraping-ethics-security.md","path":"engineering/universal-scraping-architect/skills/universal-scraping-architect/references/scraping-ethics-security.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/universal-scraping-architect/skills/universal-scraping-architect/references/scraping-ethics-security.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Funiversal-scraping-architect%2Fskills%2Funiversal-scraping-architect%2Freferences%2Fscraping-ethics-security.md -->","isInternal":false,"tokens":633,"sizeBytes":2573},{"name":"SKILL.md","path":"engineering/universal-scraping-architect/skills/universal-scraping-architect/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/universal-scraping-architect/skills/universal-scraping-architect/SKILL.md","title":"universal-scraping-architect","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Funiversal-scraping-architect%2Fskills%2Funiversal-scraping-architect%2FSKILL.md -->","frontmatter":{"name":"universal-scraping-architect","description":"Use for web scraping, crawling, document extraction, API parsing, or building validation-heavy data pipelines using Firecrawl or local Python scripts."},"isInternal":false,"tokens":1012,"sizeBytes":4598},{"name":"intake_pr_review.json","path":"engineering/workflow-builder/skills/workflow-builder/expected_outputs/intake_pr_review.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/skills/workflow-builder/expected_outputs/intake_pr_review.json","title":"Expected_outputs Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2Fskills%2Fworkflow-builder%2Fexpected_outputs%2Fintake_pr_review.json -->","frontmatter":{"task":"review my open PRs for bugs","recommended_topology":"fan-out","runner_up_topology":"pipeline","resolved_signals":{"verb_chain":false,"panel":false,"costly":false,"loop_like":false,"merge_like":false,"list_like":true,"units_effective":"known","stages_effective":"single","needs_all_effective":"no"},"model_plan":[{"stage":"fan-out stage","model":"haiku","why":"independent, mechanical per-item work is cheap on Haiku"},{"stage":"final synthesis","model":"opus","why":"combining many results into one report needs strong reasoning"}],"structured_output":"yes","budget_guard":"optional; set budget.total if the user gave a token target","rationale":{"topology":"independent units, one pass each, combined at the end -> parallel fan-out then a final synthesis agent","runner_up":"pipeline","structured_output":"default on — a small JSON schema makes downstream stages reliable at near-zero cost","budget":"fixed topology with a known/bounded item count — no runaway risk"},"add_verification":false},"isInternal":false,"tokens":318,"sizeBytes":1206},{"name":"README.md","path":"engineering/workflow-builder/skills/workflow-builder/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/skills/workflow-builder/README.md","title":"Workflow-builder Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2Fskills%2Fworkflow-builder%2FREADME.md -->","isInternal":false,"tokens":370,"sizeBytes":1468},{"name":"api_reference.md","path":"engineering/workflow-builder/skills/workflow-builder/references/api_reference.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/skills/workflow-builder/references/api_reference.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2Fskills%2Fworkflow-builder%2Freferences%2Fapi_reference.md -->","isInternal":false,"tokens":1613,"sizeBytes":6413},{"name":"decision_and_intake_guide.md","path":"engineering/workflow-builder/skills/workflow-builder/references/decision_and_intake_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/skills/workflow-builder/references/decision_and_intake_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2Fskills%2Fworkflow-builder%2Freferences%2Fdecision_and_intake_guide.md -->","isInternal":false,"tokens":1391,"sizeBytes":5948},{"name":"orchestration_patterns.md","path":"engineering/workflow-builder/skills/workflow-builder/references/orchestration_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/skills/workflow-builder/references/orchestration_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2Fskills%2Fworkflow-builder%2Freferences%2Forchestration_patterns.md -->","isInternal":false,"tokens":1452,"sizeBytes":5522},{"name":"SKILL.md","path":"engineering/workflow-builder/skills/workflow-builder/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/skills/workflow-builder/SKILL.md","title":"workflow-builder","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2Fskills%2Fworkflow-builder%2FSKILL.md -->","frontmatter":{"name":"workflow-builder","description":"Design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool. Use when a user wants to build, create, author, scaffold, or run a custom Claude Code workflow, orchestrate sub-agents (fan-out, pipeline, loop, judge-panel), or automate a repeatable multi-step task across fresh-context agents.","license":"MIT","metadata":{"inspired_by":"https://github.com/ray-amjad/claude-code-workflow-creator (Ray Amjad)","targets":"Claude Code Workflow tool (CLAUDE_CODE_WORKFLOWS=1, /workflows)","version":"1.0.0"}},"isInternal":false,"tokens":1267,"sizeBytes":5369},{"name":"companion_tooling.md","path":"engineering/write-a-skill/skills/write-a-skill/references/companion_tooling.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/write-a-skill/skills/write-a-skill/references/companion_tooling.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fwrite-a-skill%2Fskills%2Fwrite-a-skill%2Freferences%2Fcompanion_tooling.md -->","isInternal":false,"tokens":953,"sizeBytes":4085},{"name":"description_design_patterns.md","path":"engineering/write-a-skill/skills/write-a-skill/references/description_design_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/write-a-skill/skills/write-a-skill/references/description_design_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fwrite-a-skill%2Fskills%2Fwrite-a-skill%2Freferences%2Fdescription_design_patterns.md -->","isInternal":false,"tokens":1378,"sizeBytes":6027},{"name":"progressive_disclosure_principles.md","path":"engineering/write-a-skill/skills/write-a-skill/references/progressive_disclosure_principles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/write-a-skill/skills/write-a-skill/references/progressive_disclosure_principles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fwrite-a-skill%2Fskills%2Fwrite-a-skill%2Freferences%2Fprogressive_disclosure_principles.md -->","isInternal":false,"tokens":1284,"sizeBytes":5574},{"name":"quality_gates_for_skills.md","path":"engineering/write-a-skill/skills/write-a-skill/references/quality_gates_for_skills.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/write-a-skill/skills/write-a-skill/references/quality_gates_for_skills.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fwrite-a-skill%2Fskills%2Fwrite-a-skill%2Freferences%2Fquality_gates_for_skills.md -->","isInternal":false,"tokens":2106,"sizeBytes":9169},{"name":"SKILL.md","path":"engineering/write-a-skill/skills/write-a-skill/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/write-a-skill/skills/write-a-skill/SKILL.md","title":"write-a-skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fwrite-a-skill%2Fskills%2Fwrite-a-skill%2FSKILL.md -->","frontmatter":{"name":"write-a-skill","description":"Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author a new skill.","license":"MIT","metadata":{"derived_from":"https://github.com/mattpocock/skills/tree/main/skills/productivity/write-a-skill","original_author":"Matt Pocock (@mattpocock)","original_license":"MIT","voice":"Matt Pocock — direct, concrete, imperative, example-driven","version":"1.0.0"}},"isInternal":false,"tokens":1127,"sizeBytes":4861},{"name":"SKILL.md","path":"engineering/zero-hallucination-coder/skills/zero-hallucination-coder/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/zero-hallucination-coder/skills/zero-hallucination-coder/SKILL.md","title":"zero-hallucination-coder","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fzero-hallucination-coder%2Fskills%2Fzero-hallucination-coder%2FSKILL.md -->","frontmatter":{"name":"zero-hallucination-coder","description":"Runs a disciplined Discuss → Map → Decompose → Execute → Verify loop that grounds code in verified structure — no invented APIs, no assumed imports, no placeholder code — with a lazy-senior-dev YAGNI ladder that deletes unnecessary code before it is written. Use when a coding task is high-stakes, complex, or spans existing code (auth, databases, migrations, multi-file features), or when the user explicitly asks to plan carefully before coding, avoid hallucinated code, or work rigorously. Not for trivial edits, typos, or throwaway one-off scripts — those do not need the full loop."},"isInternal":false,"tokens":3258,"sizeBytes":13925},{"name":"SKILL.md","path":"finance/business-investment-advisor/skills/business-investment-advisor/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/business-investment-advisor/skills/business-investment-advisor/SKILL.md","title":"business-investment-advisor","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fbusiness-investment-advisor%2Fskills%2Fbusiness-investment-advisor%2FSKILL.md -->","frontmatter":{"name":"business-investment-advisor","description":"Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring, technology, or any capital expenditure. Also use for ROI calculations, IRR, NPV, payback period, build vs buy decisions, lease vs buy analysis, vendor evaluation, or deciding where to allocate limited budget for maximum return."},"isInternal":false,"tokens":2252,"sizeBytes":10008},{"name":"close_plan.example.json","path":"finance/month-end-close/skills/month-end-close/assets/close_plan.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/month-end-close/skills/month-end-close/assets/close_plan.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fmonth-end-close%2Fskills%2Fmonth-end-close%2Fassets%2Fclose_plan.example.json -->","frontmatter":{"period":"2026-10","close_start":"2026-11-02","target_wd":5,"holidays":[],"tasks":[{"id":"ap-cutoff","name":"AP cut-off and invoice accrual","owner":"Dana","duration_days":1,"depends_on":[]},{"id":"ar-cutoff","name":"AR cut-off and billing","owner":"Sam","duration_days":1,"depends_on":[]},{"id":"payroll","name":"Payroll accrual","owner":"Dana","duration_days":0.5,"depends_on":[]},{"id":"bank-rec","name":"Bank reconciliations","owner":"Sam","reviewer":"Lee","duration_days":1,"depends_on":["ar-cutoff"],"key_control":true,"deadline_wd":2},{"id":"accruals","name":"Accruals and prepaids","owner":"Dana","reviewer":"Dana","duration_days":1,"depends_on":["ap-cutoff","payroll"],"key_control":true},{"id":"fixed-assets","name":"Depreciation run","owner":"Priya","duration_days":0.5,"depends_on":["ap-cutoff"]},{"id":"interco","name":"Intercompany matching and eliminations","owner":"Dana","duration_days":1.5,"depends_on":["accruals","bank-rec"],"deadline_wd":3},{"id":"consolidation","name":"Consolidation and FX translation","owner":"Lee","duration_days":1,"depends_on":["interco","fixed-assets"]},{"id":"flux","name":"Flux 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-->","isInternal":false,"tokens":326,"sizeBytes":1267},{"name":"close_calendar_and_benchmarks.md","path":"finance/month-end-close/skills/month-end-close/references/close_calendar_and_benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/month-end-close/skills/month-end-close/references/close_calendar_and_benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fmonth-end-close%2Fskills%2Fmonth-end-close%2Freferences%2Fclose_calendar_and_benchmarks.md -->","isInternal":false,"tokens":1061,"sizeBytes":4454},{"name":"flux_analysis_and_materiality.md","path":"finance/month-end-close/skills/month-end-close/references/flux_analysis_and_materiality.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/month-end-close/skills/month-end-close/references/flux_analysis_and_materiality.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fmonth-end-close%2Fskills%2Fmonth-end-close%2Freferences%2Fflux_analysis_and_materiality.md -->","isInternal":false,"tokens":1057,"sizeBytes":4106},{"name":"reconciliation_standards.md","path":"finance/month-end-close/skills/month-end-close/references/reconciliation_standards.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/month-end-close/skills/month-end-close/references/reconciliation_standards.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fmonth-end-close%2Fskills%2Fmonth-end-close%2Freferences%2Freconciliation_standards.md -->","isInternal":false,"tokens":1053,"sizeBytes":4304},{"name":"SKILL.md","path":"finance/month-end-close/skills/month-end-close/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/month-end-close/skills/month-end-close/SKILL.md","title":"month-end-close","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available 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Facilities","type":"expense","department":"Operations","category":"G&A","actual":180000,"budget":200000,"prior_year":175000},{"name":"Travel & Entertainment","type":"expense","department":"Sales","category":"Sales & Marketing","actual":95000,"budget":120000,"prior_year":88000},{"name":"Professional Services","type":"expense","department":"Finance","category":"G&A","actual":310000,"budget":250000,"prior_year":220000},{"name":"R&D Expenses","type":"expense","department":"Engineering","category":"R&D","actual":1500000,"budget":1400000,"prior_year":1200000}]},"forecast":{"historical_periods":[{"period":"Q1 2024","revenue":10500000,"gross_profit":4200000,"operating_income":1575000},{"period":"Q2 2024","revenue":11200000,"gross_profit":4480000,"operating_income":1680000},{"period":"Q3 2024","revenue":11800000,"gross_profit":4720000,"operating_income":1770000},{"period":"Q4 2024","revenue":12500000,"gross_profit":5000000,"operating_income":1875000},{"period":"Q1 2025","revenue":12800000,"gross_profit":5120000,"operating_income":1920000},{"period":"Q2 2025","revenue":13500000,"gross_profit":5400000,"operating_income":2025000},{"period":"Q3 2025","revenue":14100000,"gross_profit":5640000,"operating_income":2115000},{"period":"Q4 2025","revenue":15700000,"gross_profit":6280000,"operating_income":2355000}],"drivers":{"units":{"base_units":5000,"growth_rate":0.04},"pricing":{"base_price":2800,"annual_increase":0.03}},"assumptions":{"revenue_growth_rate":0.08,"gross_margin":0.4,"opex_pct_revenue":0.25,"forecast_periods":12},"scenarios":{"base":{"growth_adjustment":0,"margin_adjustment":0},"bull":{"growth_adjustment":0.04,"margin_adjustment":0.03},"bear":{"growth_adjustment":-0.03,"margin_adjustment":-0.02}},"cash_flow_inputs":{"opening_cash_balance":2500000,"weekly_revenue":350000,"collection_rate":0.85,"collection_lag_weeks":2,"weekly_payroll":160000,"weekly_rent":15000,"weekly_operating":45000,"weekly_other":20000,"one_time_items":[{"week":3,"amount":-250000,"description":"Annual insurance premium"},{"week":6,"amount":500000,"description":"Customer prepayment"},{"week":9,"amount":-180000,"description":"Equipment purchase"},{"week":13,"amount":-75000,"description":"Quarterly tax payment"}]},"forecast_periods":12}},"isInternal":false,"tokens":2004,"sizeBytes":6437},{"name":"variance_report_template.md","path":"finance/skills/financial-analyst/assets/variance_report_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/financial-analyst/assets/variance_report_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Ffinancial-analyst%2Fassets%2Fvariance_report_template.md -->","isInternal":false,"tokens":1285,"sizeBytes":3863},{"name":"financial-ratios-guide.md","path":"finance/skills/financial-analyst/references/financial-ratios-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/financial-analyst/references/financial-ratios-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Ffinancial-analyst%2Freferences%2Ffinancial-ratios-guide.md -->","isInternal":false,"tokens":2540,"sizeBytes":9212},{"name":"forecasting-best-practices.md","path":"finance/skills/financial-analyst/references/forecasting-best-practices.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/financial-analyst/references/forecasting-best-practices.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Ffinancial-analyst%2Freferences%2Fforecasting-best-practices.md -->","isInternal":false,"tokens":2258,"sizeBytes":10012},{"name":"industry-adaptations.md","path":"finance/skills/financial-analyst/references/industry-adaptations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/financial-analyst/references/industry-adaptations.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Ffinancial-analyst%2Freferences%2Findustry-adaptations.md -->","isInternal":false,"tokens":806,"sizeBytes":2914},{"name":"valuation-methodology.md","path":"finance/skills/financial-analyst/references/valuation-methodology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/financial-analyst/references/valuation-methodology.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Ffinancial-analyst%2Freferences%2Fvaluation-methodology.md -->","isInternal":false,"tokens":1983,"sizeBytes":7922},{"name":"SKILL.md","path":"finance/skills/financial-analyst/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/financial-analyst/SKILL.md","title":"financial-analyst","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Ffinancial-analyst%2FSKILL.md -->","frontmatter":{"name":"financial-analyst","description":"Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis."},"isInternal":false,"tokens":1522,"sizeBytes":7204},{"name":"close_plan.example.json","path":"finance/skills/month-end-close/assets/close_plan.example.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/month-end-close/assets/close_plan.example.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fmonth-end-close%2Fassets%2Fclose_plan.example.json -->","frontmatter":{"period":"2026-10","close_start":"2026-11-02","target_wd":5,"holidays":[],"tasks":[{"id":"ap-cutoff","name":"AP cut-off and invoice accrual","owner":"Dana","duration_days":1,"depends_on":[]},{"id":"ar-cutoff","name":"AR cut-off and 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review","owner":"Lee","reviewer":"CFO","duration_days":1,"depends_on":["consolidation"],"key_control":true},{"id":"reporting","name":"Management reporting pack","owner":"","duration_days":0.5,"depends_on":["flux"]}]},"isInternal":false,"tokens":636,"sizeBytes":2070},{"name":"reconciliation_signoff.md","path":"finance/skills/month-end-close/assets/reconciliation_signoff.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/month-end-close/assets/reconciliation_signoff.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fmonth-end-close%2Fassets%2Freconciliation_signoff.md -->","isInternal":false,"tokens":326,"sizeBytes":1267},{"name":"close_calendar_and_benchmarks.md","path":"finance/skills/month-end-close/references/close_calendar_and_benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/month-end-close/references/close_calendar_and_benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fmonth-end-close%2Freferences%2Fclose_calendar_and_benchmarks.md -->","isInternal":false,"tokens":1061,"sizeBytes":4454},{"name":"flux_analysis_and_materiality.md","path":"finance/skills/month-end-close/references/flux_analysis_and_materiality.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/month-end-close/references/flux_analysis_and_materiality.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fmonth-end-close%2Freferences%2Fflux_analysis_and_materiality.md -->","isInternal":false,"tokens":1057,"sizeBytes":4106},{"name":"reconciliation_standards.md","path":"finance/skills/month-end-close/references/reconciliation_standards.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/month-end-close/references/reconciliation_standards.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fmonth-end-close%2Freferences%2Freconciliation_standards.md -->","isInternal":false,"tokens":1053,"sizeBytes":4304},{"name":"SKILL.md","path":"finance/skills/month-end-close/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/month-end-close/SKILL.md","title":"month-end-close","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fmonth-end-close%2FSKILL.md -->","frontmatter":{"name":"month-end-close","description":"Use when running, planning or speeding up a month-end (or quarter-end) close — building or reviewing the close checklist and calendar, reconciling a bank statement or sub-ledger to the general ledger, writing or reviewing flux (variance) explanations, or finding why the close takes too many days. Orders close tasks by dependency and finds the critical path, proves each reconciliation and ages what is left, and refuses to sign off material fluctuations explained with boilerplate.","argument-hint":"[close plan JSON | GL and bank CSVs | trial balance comparison CSV]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Three-gate close (calendar, reconciliation proof, flux explanations) with 3 deterministic stdlib scripts and blocking exit codes; control expectations cited to COSO 2013 and PCAOB AS 2201 / AS 2305 / SAPA 11","distinct_from":"financial-analyst (ratios, DCF, budgets, forecasts); saas-metrics-coach (ARR, churn, unit economics); research-finance (R&D program budgets and capitalisation); this skill runs the accounting close 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/api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2Fexamples%2Fhard-money-fund%2Foutput.md -->","isInternal":false,"tokens":4506,"sizeBytes":16316},{"name":"input.md","path":"finance/skills/passive-deal-screener/examples/private-credit-fund/input.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/passive-deal-screener/examples/private-credit-fund/input.md","title":"Private-credit-fund Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2Fexamples%2Fprivate-credit-fund%2Finput.md 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Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2Freferences%2Fdata%2Fetf-comparators-snapshot.md -->","isInternal":false,"tokens":2309,"sizeBytes":7440},{"name":"fred-10yr-snapshot.md","path":"finance/skills/passive-deal-screener/references/data/fred-10yr-snapshot.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/passive-deal-screener/references/data/fred-10yr-snapshot.md","title":"Data Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2Freferences%2Fdata%2Ffred-10yr-snapshot.md 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available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2Freferences%2Fdata%2Fpreqin-vintage-note.md -->","isInternal":false,"tokens":893,"sizeBytes":3459},{"name":"README.md","path":"finance/skills/passive-deal-screener/references/data/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/passive-deal-screener/references/data/README.md","title":"Data Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2Freferences%2Fdata%2FREADME.md -->","isInternal":false,"tokens":884,"sizeBytes":3289},{"name":"SKILL.md","path":"finance/skills/passive-deal-screener/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/passive-deal-screener/SKILL.md","title":"passive-deal-screener","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fpassive-deal-screener%2FSKILL.md -->","frontmatter":{"name":"passive-deal-screener","description":"Screens private investment opportunities from the passive LP (limited-partner) perspective — equity syndications, preferred equity, hard money / bridge funds, and private credit — pasted from any source (an investment platform listing, a direct GP email, raw terms). Produces a deal snapshot, stress-tests returns against public benchmarks, deconstructs the fee stack to a gross-to-net drag, surfaces severity-ranked red flags and missing disclosures, assesses GP alignment, and generates prioritized GP questions with bad-answer signals. Use whenever asked to analyze, evaluate, screen, or review a real-estate or private-market deal, syndication, offering, or investment opportunity — e.g. 'is this deal worth pursuing', 'what should I ask the GP', 'analyze this offering memo'. LP lens only; not operator-side underwriting (acquisition/development/asset-management). For corporate-finance DCF/ratio work use financial-analyst."},"isInternal":false,"tokens":2620,"sizeBytes":10312},{"name":"input-template.md","path":"finance/skills/saas-metrics-coach/assets/input-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/saas-metrics-coach/assets/input-template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fsaas-metrics-coach%2Fassets%2Finput-template.md -->","isInternal":false,"tokens":200,"sizeBytes":718},{"name":"benchmarks.md","path":"finance/skills/saas-metrics-coach/references/benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/saas-metrics-coach/references/benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fsaas-metrics-coach%2Freferences%2Fbenchmarks.md -->","isInternal":false,"tokens":921,"sizeBytes":2530},{"name":"formulas.md","path":"finance/skills/saas-metrics-coach/references/formulas.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/saas-metrics-coach/references/formulas.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fsaas-metrics-coach%2Freferences%2Fformulas.md -->","isInternal":false,"tokens":801,"sizeBytes":2493},{"name":"SKILL.md","path":"finance/skills/saas-metrics-coach/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/saas-metrics-coach/SKILL.md","title":"saas-metrics-coach","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fsaas-metrics-coach%2FSKILL.md -->","frontmatter":{"name":"saas-metrics-coach","description":"SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how their SaaS business is doing.","license":"MIT","metadata":{"version":"1.0.0","author":"Abbas Mir","category":"finance","updated":"2026-03-08"}},"isInternal":false,"tokens":1455,"sizeBytes":5748},{"name":"evals.json","path":"finance/skills/stock-analysis/evals/evals.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/evals/evals.json","title":"Evals Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Fevals%2Fevals.json -->","frontmatter":{"skill_name":"stock-analysis","evals":[{"id":0,"name":"bank-sector-routing","prompt":"can you take a look at HDFC Bank for me? want to know if it's fundamentally strong or if i'm better off elsewhere. people keep saying it's cheap now","expected_output":"A sector-aware analysis that routes to the banks playbook: uses NIM, CASA, ROA, GNPA/NNPA, slippages, credit cost, PCR, CAR/CET1, cost-to-income; explicitly declines to use OPM/ROCE/EV-EBITDA/FCF as inapplicable to a bank; values on P/B against ROE vs cost of equity rather than a generic P/E; cites sources with as-of dates; does not give personalised buy/sell advice.","files":[],"assertions":["Does NOT report OPM, ROCE, EV/EBITDA or free cash flow as headline metrics for the bank, or explicitly states they are inapplicable to a deposit-taking lender","Uses at least five bank-specific metrics from: NIM, CASA, ROA, GNPA, NNPA, slippage ratio, credit cost, PCR, CAR/CET1, cost-to-income, LCR","Anchors valuation on price-to-book (or price-to-adjusted-book) referenced to ROE versus cost of equity, rather than concluding from P/E alone","Every headline financial figure is accompanied by a source and a reporting period","Contains an explicit data-quality note covering as-of date and consolidated-vs-standalone basis","Addresses the user's 'people say it's cheap' premise directly rather than ignoring it","Includes a bear case or key-risks section","Contains a not-financial-advice disclaimer and gives no personalised buy/sell instruction"]},{"id":1,"name":"cross-sector-margin-trap","prompt":"TCS runs about 24% operating margin and Avenue Supermarts (DMart) is around 8%. TCS looks far better on margins so it should be the stronger business right?","expected_output":"Directly challenges the single-metric premise. Explains margin is sector-bound and not comparable across IT services and grocery retail; brings in asset turnover and DuPont to show a low-margin high-turnover retailer can earn comparable or superior returns on capital; compares ROIC/ROCE, cash conversion, growth durability and reinvestment runway; benchmarks each within its own sector and own history; refuses to declare a winner on margin alone.","files":[],"assertions":["Explicitly rejects the premise that a higher operating margin implies the stronger business","Explains why margins are structurally not comparable across these two sectors (e.g. gross-vs-net revenue recognition, value-add base, capital intensity)","Introduces asset turnover and/or an explicit DuPont decomposition","Compares return on capital (ROCE, ROIC or ROE) for both companies as the cross-sector-valid measure","Benchmarks each company against its OWN sector peers rather than against each other on margin","Separates the question of business quality from the question of valuation / which is the better buy","Does not declare a winner on the basis of margin alone"]},{"id":2,"name":"deep-dive-bear-case","prompt":"do a thorough fundamental analysis of Tata Motors - I want the full picture including what could go wrong. thinking about a reasonably sized position so don't sugarcoat it","expected_output":"Runs deep-dive mode: identifies the auto sector playbook and the situation overlay (cyclical, multi-segment, historically leveraged); separates automotive net debt from the captive finance arm; uses EBITDA per vehicle, volumes vs registrations, capex plus capitalised product development, mid-cycle ROIC; values sum-of-the-parts rather than a single consolidated multiple; includes a serious bear case and specific thesis-invalidation triggers.","files":[],"assertions":["Analyses the business by segment rather than as a single consolidated entity","Separates automotive net debt/cash from any captive finance or lending arm, or explains why that separation matters","Values using sum-of-the-parts or segment-level multiples rather than one consolidated P/E","Uses at least three auto-sector-specific metrics (e.g. EBITDA per vehicle, wholesale vs retail registrations, capex plus capitalised product development, mid-cycle ROIC, capacity utilisation, discount per unit)","Applies a cyclical or situation overlay, including the risk of capitalising peak or trough earnings","Contains a substantive bear case that is genuinely argued, not a token risk list","States specific, observable thesis-invalidation triggers","Includes a data-quality note with as-of dates and sources","Gives no personalised position sizing despite the user hinting at one"]},{"id":3,"name":"document-grounded-red-flags","prompt":"I've attached selected extracts from Kesar Agro Industries' FY26 annual report. Is this a fundamentally sound company worth investing in?","expected_output":"A document-grounded read that surfaces the planted abnormalities from the extracts rather than a generic bullish summary: the qualified audit opinion and the unprovided ₹180 cr interest-free related-party advance, the going-concern material uncertainty, related-party tunnelling (loans growing, below-market sales to promoter entities), contingent liabilities (₹420 cr) exceeding net worth (₹350 cr), promoter pledge rising to 71%, the CARO findings (bank returns disagreeing with books, evergreening, unpaid statutory dues, loan default), the CFO churn and mid-year auditor resignation, and the profit-vs-cash divergence. It should escalate these prominently, decline to give a clean bullish verdict, cite the document, and not fabricate figures not in the extract.","files":["fixtures/synthetic-ar-excerpt.md"],"assertions":["Surfaces the qualified audit opinion and the unprovided related-party advance (~₹180 cr) to the promoter entity","Flags the going-concern material uncertainty and the term-loan default disclosed in CARO","Identifies related-party leakage / tunnelling (growing interest-free loans and/or below-market sales to promoter-linked entities)","Notes that contingent liabilities (~₹420 cr) exceed net worth (~₹350 cr)","Flags the promoter share pledge rising sharply (to ~71% of promoter holding)","Notes the profit-rising-while-CFO-negative divergence, or the CARO bank-returns-vs-books disagreement, or the CFO/auditor turnover","Does NOT conclude the company is fundamentally sound / a clear buy; treats governance and accounting findings as potentially disqualifying","Attributes findings to the annual-report extract and does not invent figures absent from it"]},{"id":4,"name":"forensic-mode-routing","prompt":"Profit at Kesar Agro keeps rising every year but I heard the cash flow is actually negative. Are they cooking the books? I've attached extracts from their FY26 annual report.","expected_output":"Routes to Forensic mode (the question is 'can these accounts bear weight?', not 'is this a good investment?'). Runs the cash-vs-earnings accruals work (cumulative CFO far below cumulative PAT), a proof-of-cash test (interest income of ~₹3 cr on ~₹200 cr of cash implies a ~1.5% yield versus much higher borrowing cost), reads the CARO bank-returns-vs-books disagreement and the receivables build, and reaches a forensic verdict about how much the numbers can be trusted. It should NOT pivot into a valuation, target price or buy/sell call, because valuing earnings you do not believe is wasted work.","files":["fixtures/synthetic-ar-excerpt.md"],"assertions":["Explicitly frames this as a forensic / earnings-quality question rather than a standard buy-side analysis","Compares reported profit against operating cash flow over multiple years (accruals / cash-conversion gap)","Runs a proof-of-cash or interest-income-vs-cash check, or otherwise questions the reported cash balance","Uses the CARO bank-statement-vs-books disagreement and/or the receivables build as evidence","Reaches a verdict about the reliability of the accounts rather than a price target","Does NOT produce a valuation, target price, or personalised buy/sell recommendation"]},{"id":5,"name":"recency-gate-stale-data","prompt":"It's August 2026. A friend built this summary of Meridian Industries from their FY25 (year ended March 2025) annual report: revenue ₹8,400 cr, net profit ₹610 cr, net debt ₹1,200 cr, at a share price around ₹950. Is the stock cheap right now?","expected_output":"Runs the recency gate before answering: recognises that FY25 (March-2025) data is roughly 15+ months old as of August 2026, that FY26 annual results and at least one FY27 quarter have almost certainly been reported since, and that a 'cheap right now' judgement cannot rest on superseded figures or a stale price. It should state the most-recent-period problem explicitly, decline to deliver a current valuation verdict on the stale data, and say what it would need (the latest annual and quarterly filings, a current price with an as-of date).","files":[],"assertions":["Explicitly flags that the FY25 (March-2025) figures are stale as of August 2026 and that newer periods (FY26, and likely an FY27 quarter) should exist","Runs or references a recency check rather than analysing the provided numbers as if current","Does not deliver a definitive 'cheap' / 'expensive' verdict resting on the 15-month-old figures without flagging the staleness","States what current data would be needed (latest annual + quarterly filings, current price with an as-of date)","Treats the provided figures as needing verification against the primary filings rather than as established facts"]},{"id":6,"name":"ipo-mode-drhp","prompt":"Should I apply to the Vayu Mobility IPO? I've attached extracts from their DRHP. The price band is ₹590–620.","expected_output":"Routes to IPO mode (no market price history, no own-history benchmark). Flags that the offer is overwhelmingly an Offer for Sale (₹1,500 cr of ₹1,800 cr) with only ₹300 cr of fresh capital, i.e. insiders and the PE fund are cashing out; notes the ~3x pre-IPO price step-up within four months; scrutinises the bespoke 'Adjusted EBITDA' add-backs that recur every year; surfaces the promoter's pending criminal proceedings, customer concentration and negative operating cash flow; and assesses the ₹590–620 band on multiples / a forward view rather than any own-history or market-price method. No personalised apply/avoid instruction framed as advice.","files":["fixtures/synthetic-drhp-excerpt.md"],"assertions":["Recognises IPO mode: no trading history, so own-history benchmarking and market-price valuation are unavailable","Flags that the offer is mostly an Offer for Sale (sellers cashing out) with little fresh capital entering the business","Notes the steep pre-IPO placement price step-up relative to the price band","Scrutinises the non-GAAP 'Adjusted EBITDA' add-backs, noting the excluded costs recur every year","Surfaces at least one of: promoter criminal litigation, customer concentration, negative operating cash flow, or the restatement adjustments","Assesses the price band using multiples or a forward view rather than own-history or market-price methods","Gives no personalised 'apply' / 'avoid' instruction framed as investment advice"]},{"id":7,"name":"aggregator-primary-source-discipline","prompt":"Here's what screener.in shows for Aarti Foods: revenue ₹4,200 cr, PAT ₹310 cr, ROCE 19%, total debt ₹500 cr. Based on this, is it a good business?","expected_output":"Treats the pasted aggregator figures as unverified and not a source of record: it explains that screener.in and similar aggregators are navigation aids for locating the actual filings, not citable sources, and that the analysis must trace these numbers to the company's own annual report and exchange filings (checking consolidated-vs-standalone basis, period, and units) before relying on them. It should proceed with the figures marked as aggregator-sourced / unverified, or ask for the primary documents by name, rather than delivering a confident verdict citing screener as the source.","files":[],"assertions":["States that aggregator data (screener.in) is a navigation aid, not a source of record, and should be verified against the primary filings","Does not present the pasted screener figures as sourced facts underpinning a final verdict","Marks the provided figures as aggregator-sourced / unverified, or asks for the annual report and exchange filings by name","Notes at least one verification concern that the aggregator figure hides (consolidated vs standalone, period/as-of, units, or definition of ROCE/debt)","Any provisional read is explicitly caveated as resting on unverified aggregator 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/api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Frail-freight.md -->","isInternal":false,"tokens":10231,"sizeBytes":50226},{"name":"realestate-reit.md","path":"finance/skills/stock-analysis/references/sectors/realestate-reit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/realestate-reit.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Frealestate-reit.md -->","isInternal":false,"tokens":10006,"sizeBytes":45388},{"name":"retail-ecommerce.md","path":"finance/skills/stock-analysis/references/sectors/retail-ecommerce.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/retail-ecommerce.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fretail-ecommerce.md -->","isInternal":false,"tokens":10982,"sizeBytes":49480},{"name":"semiconductors.md","path":"finance/skills/stock-analysis/references/sectors/semiconductors.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/semiconductors.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fsemiconductors.md -->","isInternal":false,"tokens":9481,"sizeBytes":44209},{"name":"shipping-logistics.md","path":"finance/skills/stock-analysis/references/sectors/shipping-logistics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/shipping-logistics.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fshipping-logistics.md -->","isInternal":false,"tokens":10430,"sizeBytes":48302},{"name":"telecom-media.md","path":"finance/skills/stock-analysis/references/sectors/telecom-media.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/telecom-media.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Ftelecom-media.md -->","isInternal":false,"tokens":9473,"sizeBytes":44154},{"name":"utilities-power.md","path":"finance/skills/stock-analysis/references/sectors/utilities-power.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/utilities-power.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Futilities-power.md -->","isInternal":false,"tokens":10320,"sizeBytes":45941},{"name":"waste-environmental.md","path":"finance/skills/stock-analysis/references/sectors/waste-environmental.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/references/sectors/waste-environmental.md","title":"Sectors Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Freferences%2Fsectors%2Fwaste-environmental.md -->","isInternal":false,"tokens":9651,"sizeBytes":47612},{"name":"benchmarks.json","path":"finance/skills/stock-analysis/scripts/benchmarks.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/scripts/benchmarks.json","title":"Scripts Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2Fscripts%2Fbenchmarks.json -->","isInternal":false,"tokens":14292,"sizeBytes":50076},{"name":"SKILL.md","path":"finance/skills/stock-analysis/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/skills/stock-analysis/SKILL.md","title":"stock-analysis","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fskills%2Fstock-analysis%2FSKILL.md -->","frontmatter":{"name":"stock-analysis","description":"Produce a rigorous, sector-relative, multi-factor fundamental analysis of a publicly listed company — Indian (NSE/BSE) or US/global. Use when the user asks to analyse, research, evaluate, or value a stock, ticker, or listed company; asks whether a business is fundamentally strong, cheap, or expensive; compares companies or benchmarks one against its sector; or mentions OPM, ROCE, ROE, ROIC, P/E, EV/EBITDA, free cash flow, NIM, GNPA, CASA, promoter holding or pledging. Use it for accounting-quality and forensic questions — \"is the profit real\", \"why is profit rising but cash isn't\", auditor qualifications, related-party concerns — which route to the forensic-only mode, and for IPOs and not-yet-listed companies — \"should I apply to this IPO\", DRHP/RHP or S-1 questions, price band, grey market premium — which route to the IPO mode. Use it even when the request sounds casual (\"is Infosys any good?\"). Do not use it for personalised investment advice, portfolio allocation, or trading signals."},"isInternal":false,"tokens":7600,"sizeBytes":34268},{"name":"SKILL.md","path":"loop-library/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/loop-library/SKILL.md","title":"loop-library","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=loop-library%2FSKILL.md -->","frontmatter":{"name":"loop-library","description":"Discover, find, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Use when a user asks to analyze a codebase for potential loops, mine coding-thread history for work done more than once, turn repeated engineering work into a loop, find or recommend a published loop, create a recurring agent workflow or automation cadence, turn an outcome into a bounded copy-ready loop, or review an existing loop for weak checks, unsafe authority, unbounded repetition, stale state, or unclear stopping behavior."},"isInternal":false,"tokens":2403,"sizeBytes":11482},{"name":"design_system_schema.json","path":"markdown-html/skills/design-system/assets/design_system_schema.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/design-system/assets/design_system_schema.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Fassets%2Fdesign_system_schema.json -->","frontmatter":{"$schema":"https://json-schema.org/draft/2020-12/schema","$id":"https://github.com/alirezarezvani/claude-skills/blob/main/markdown-html/skills/design-system/assets/design_system_schema.json","title":"markdown-html design-system customization config","description":"JSON schema for the design-system config written by onboard.py and consumed by every markdown-html converter via config_loader.py. Lives at ~/.config/markdown-html/design-system.json (global) or ./.markdown-html/design-system.json (project).","type":"object","required":["version","skill","default_output_dir","brand","typography","design_style","code_theme","toc"],"properties":{"version":{"type":"integer","const":1,"description":"Schema version. Bump on breaking changes to the layout."},"skill":{"type":"string","const":"design-system"},"default_output_dir":{"type":"string","minLength":1,"description":"Where converters save generated HTML by default. Must be a writable path. The orchestrator's output_path_resolver.py also accepts a --out override per conversion."},"brand":{"type":"object","required":["primary"],"properties":{"primary":{"type":"string","pattern":"^#?[0-9a-fA-F]{6}$","description":"Primary brand color, HEX."},"accent":{"type":["string","null"],"pattern":"^#?[0-9a-fA-F]{6}$|^$","description":"Optional accent color. If null/empty, brand_palette_validator derives it from the primary via hue-shift + lighten."},"bg":{"type":["string","null"],"description":"Optional background override. If null, derived from primary."},"text":{"type":["string","null"],"description":"Optional body text override. If null, derived (off-white on dark bg, near-black on light bg)."}}},"typography":{"type":"object","required":["heading_font","body_font"],"properties":{"heading_font":{"type":"string","description":"Google Font family for headings. e.g., Inter, Source Serif 4, Playfair Display."},"body_font":{"type":"string","description":"Google Font family for body text."},"scale_ratio":{"type":"number","minimum":1,"maximum":2,"description":"Modular type-scale ratio. 1.25 = major third (default), 1.333 = perfect fourth, 1.5 = perfect fifth."}}},"design_style":{"type":"string","enum":["editorial","technical","minimal","playful"],"description":"Layout density preset consumed by every converter. editorial = magazine-like with wide margins and pull-quotes; technical = docs-like with sticky TOC and code emphasis; minimal = sparse with maximum whitespace; playful = product-marketing with color blocks and varied scale."},"code_theme":{"type":"string","enum":["light","dark","auto"],"description":"Prism.js theme selection. auto = follows prefers-color-scheme."},"toc":{"type":"object","required":["behavior"],"properties":{"behavior":{"type":"string","enum":["sticky-sidebar","collapsible-top","inline","none"]},"max_depth":{"type":"integer","minimum":1,"maximum":6,"description":"Deepest heading level included in the TOC."}}},"company_name":{"type":"string","description":"Optional, shown in footer of every generated HTML."},"logo_url":{"type":"string","description":"Optional. Base64-embedded at render time by default; pass --logo-mode link to inline the URL instead."},"derived_palette":{"type":"object","description":"12 CSS custom properties derived from the brand input by brand_palette_validator.derive_palette(). Stored here so every converter has identical tokens without re-deriving. Keys are CSS variable names; values are HEX or rgba() strings.","properties":{"--md-bg":{"type":"string"},"--md-surface":{"type":"string"},"--md-border":{"type":"string"},"--md-text":{"type":"string"},"--md-text-muted":{"type":"string"},"--md-accent":{"type":"string"},"--md-accent-soft":{"type":"string"},"--md-code-bg":{"type":"string"},"--md-link":{"type":"string"},"--md-link-hover":{"type":"string"},"--md-success":{"type":"string"},"--md-warn":{"type":"string"}}},"setup_completed_at":{"type":["string","null"],"format":"date-time","description":"ISO-8601 timestamp written by onboard.py on successful completion. The orchestrator refuses to convert if this is null."}}},"isInternal":false,"tokens":1186,"sizeBytes":4719},{"name":"design_token_canon.md","path":"markdown-html/skills/design-system/references/design_token_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/design-system/references/design_token_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Freferences%2Fdesign_token_canon.md -->","isInternal":false,"tokens":1026,"sizeBytes":4350},{"name":"typography_pairing.md","path":"markdown-html/skills/design-system/references/typography_pairing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/design-system/references/typography_pairing.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Freferences%2Ftypography_pairing.md -->","isInternal":false,"tokens":1274,"sizeBytes":5285},{"name":"wcag_accessibility.md","path":"markdown-html/skills/design-system/references/wcag_accessibility.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/design-system/references/wcag_accessibility.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2Freferences%2Fwcag_accessibility.md -->","isInternal":false,"tokens":1119,"sizeBytes":4362},{"name":"SKILL.md","path":"markdown-html/skills/design-system/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/design-system/SKILL.md","title":"design-system","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fdesign-system%2FSKILL.md -->","frontmatter":{"name":"design-system","description":"Captures the user's brand identity once via a 10-question onboarding wizard (primary/accent HEX + heading + body Google Fonts + design style editorial/technical/minimal/playful + default output directory + syntax theme + TOC behavior + optional logo/company), validates body-text and link contrast against WCAG 2.2 AA, derives 12 CSS custom properties in HSL space, and stores the result for every markdown-html converter to consume. Use before any markdown-html conversion. Triggers on first-run onboarding (\"set up the brand\", \"configure markdown-html\", \"run onboarding\"), on explicit reset (\"reset the design system\", \"re-onboard\"), and is checked by every converter via config_loader.py before rendering. Refuses to save if body-text contrast fails AA 4.5:1 or the output dir isn't writable. Precedence is project (./.markdown-html/), then global (~/.config/markdown-html/), then built-in defaults; MARKDOWN_HTML_NO_CONFIG=1 bypasses.","license":"MIT","metadata":{"version":"2.10.0","author":"Alireza Rezvani","tags":["design-system","brand-palette","wcag","onboarding","customization","markdown-html","css-variables","typography"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2915,"sizeBytes":11312},{"name":"information_density_canon.md","path":"markdown-html/skills/markdown-html-orchestrator/references/information_density_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/markdown-html-orchestrator/references/information_density_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Finformation_density_canon.md -->","isInternal":false,"tokens":914,"sizeBytes":4072},{"name":"orchestrator_routing_patterns.md","path":"markdown-html/skills/markdown-html-orchestrator/references/orchestrator_routing_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/markdown-html-orchestrator/references/orchestrator_routing_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Forchestrator_routing_patterns.md -->","isInternal":false,"tokens":913,"sizeBytes":4058},{"name":"single_file_html_discipline.md","path":"markdown-html/skills/markdown-html-orchestrator/references/single_file_html_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/markdown-html-orchestrator/references/single_file_html_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2Freferences%2Fsingle_file_html_discipline.md -->","isInternal":false,"tokens":1231,"sizeBytes":5286},{"name":"SKILL.md","path":"markdown-html/skills/markdown-html-orchestrator/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/markdown-html-orchestrator/SKILL.md","title":"markdown-html-orchestrator","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmarkdown-html-orchestrator%2FSKILL.md -->","frontmatter":{"name":"markdown-html-orchestrator","description":"Use when a user wants to convert any markdown file in their Claude project into a single-file, lightly-interactive HTML — long-form documents (specs, plans, RFCs, reports, explainers), code reviews with diffs and severity-tagged annotations, or slide decks. Triggers on \"convert this markdown to HTML\", \"make this an HTML file\", \"turn this into an interactive document\", \"render this report as HTML\", \"PR writeup as HTML\", \"slides from this markdown\". Forks context to route to one of three converter sub-skills (md-document, md-review, md-slides) based on a deterministic doctype classifier, after the user has run the design-system onboarding once. Refuses if input is under 100 lines (per Shihipar — markdown still wins below the threshold) or design-system isn't onboarded. Distinct from Anthropic's official Playground plugin (which is interactive prompt-tuning controls with sliders/knobs/prompt-copy-back) and from marketing/landing/ (which is a landing-page generator).","context":"fork","license":"MIT","metadata":{"version":"2.10.3","author":"Alireza Rezvani","tags":["markdown","html","converter","orchestrator","documentation","code-review","slides","design-system"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2790,"sizeBytes":11095},{"name":"information_density_patterns.md","path":"markdown-html/skills/md-document/references/information_density_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-document/references/information_density_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Finformation_density_patterns.md -->","isInternal":false,"tokens":1149,"sizeBytes":4979},{"name":"single_file_html_discipline.md","path":"markdown-html/skills/md-document/references/single_file_html_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-document/references/single_file_html_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Fsingle_file_html_discipline.md -->","isInternal":false,"tokens":1227,"sizeBytes":5077},{"name":"toc_and_nav_ux.md","path":"markdown-html/skills/md-document/references/toc_and_nav_ux.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-document/references/toc_and_nav_ux.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2Freferences%2Ftoc_and_nav_ux.md -->","isInternal":false,"tokens":1066,"sizeBytes":4477},{"name":"SKILL.md","path":"markdown-html/skills/md-document/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-document/SKILL.md","title":"md-document","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-document%2FSKILL.md -->","frontmatter":{"name":"md-document","description":"Converts long-form markdown (specs, RFCs, reports, plans, explainers) into a single-file, lightly-interactive HTML document with sticky TOC, scrollspy, search filter, code-copy buttons, and design-system-driven brand tokens. Triggers when the markdown-html-orchestrator classifies an input as DOCUMENT, or when invoked directly via /cs-md-document. Reads the design-system config via config_loader.py and inlines the user's 12 derived CSS custom properties; refuses to render if onboarding hasn't run. Single-file output — Google Fonts + Prism.js CDN are the only externals; no framework runtime, no build step. Use after orchestrator routing or after design-system onboarding is confirmed.","license":"MIT","metadata":{"version":"2.10.1","author":"Alireza Rezvani","tags":["markdown","html","documentation","single-file","toc","scrollspy","search","code-copy","design-system"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1605,"sizeBytes":6278},{"name":"diff_rendering_canon.md","path":"markdown-html/skills/md-review/references/diff_rendering_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-review/references/diff_rendering_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2Freferences%2Fdiff_rendering_canon.md -->","isInternal":false,"tokens":1217,"sizeBytes":5161},{"name":"pr_annotation_ux.md","path":"markdown-html/skills/md-review/references/pr_annotation_ux.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-review/references/pr_annotation_ux.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2Freferences%2Fpr_annotation_ux.md -->","isInternal":false,"tokens":1267,"sizeBytes":5491},{"name":"severity_coding.md","path":"markdown-html/skills/md-review/references/severity_coding.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-review/references/severity_coding.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2Freferences%2Fseverity_coding.md -->","isInternal":false,"tokens":1238,"sizeBytes":5064},{"name":"SKILL.md","path":"markdown-html/skills/md-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-review/SKILL.md","title":"md-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-review%2FSKILL.md -->","frontmatter":{"name":"md-review","description":"Converts a markdown PR writeup or code review (one with ```diff fenced blocks and severity-tagged GFM callouts [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer. Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs-md-review. Refuses without explicit --reviewer (a code review must name a human), refuses if no diff hunks present (route to md-document instead), and refuses to encode severity in color only (every badge ships color + icon + aria-label per WCAG 1.4.1). Use after orchestrator routing.","license":"MIT","metadata":{"version":"2.10.2","author":"Alireza Rezvani","tags":["markdown","html","code-review","diff","severity","annotations","single-file","design-system","wcag-1.4.1"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1651,"sizeBytes":6561},{"name":"keyboard_nav_patterns.md","path":"markdown-html/skills/md-slides/references/keyboard_nav_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-slides/references/keyboard_nav_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fkeyboard_nav_patterns.md -->","isInternal":false,"tokens":1147,"sizeBytes":4706},{"name":"presentation_ux.md","path":"markdown-html/skills/md-slides/references/presentation_ux.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-slides/references/presentation_ux.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fpresentation_ux.md -->","isInternal":false,"tokens":1174,"sizeBytes":5187},{"name":"single_file_deck_conventions.md","path":"markdown-html/skills/md-slides/references/single_file_deck_conventions.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-slides/references/single_file_deck_conventions.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2Freferences%2Fsingle_file_deck_conventions.md -->","isInternal":false,"tokens":1210,"sizeBytes":5208},{"name":"SKILL.md","path":"markdown-html/skills/md-slides/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/skills/md-slides/SKILL.md","title":"md-slides","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2Fskills%2Fmd-slides%2FSKILL.md -->","frontmatter":{"name":"md-slides","description":"Converts a markdown deck (slides separated by `---` HR boundaries or by `# ` H1 headings, with optional HTML-comment `notes:` presenter-notes blocks) into a single-file HTML presentation with arrow-key / space / PgDn / PgUp / Home / End / P / Esc keyboard navigation, presenter mode (split view with current slide + speaker notes + clock + next-slide preview), URL-hash deep linking, and `@media print` page-per-slide for PDF export. Triggers when the markdown-html-orchestrator classifies an input as SLIDES, or when invoked directly via /cs-md-slides. Reuses md-document's markdown parser for slide-body rendering and reads design-system tokens via config_loader.py. Refuses if input has no clear slide boundaries, produces a 1-slide deck, or `--strict-notes` is on with under 50% notes coverage. Use after orchestrator routing.","license":"MIT","metadata":{"version":"2.10.3","author":"Alireza Rezvani","tags":["markdown","html","slides","deck","presenter-mode","keyboard-nav","print-to-pdf","single-file","design-system"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":1660,"sizeBytes":6592},{"name":"sample-size-guide.md","path":"marketing-skill/skills/ab-test-setup/references/sample-size-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ab-test-setup/references/sample-size-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2Freferences%2Fsample-size-guide.md -->","isInternal":false,"tokens":2046,"sizeBytes":7068},{"name":"test-templates.md","path":"marketing-skill/skills/ab-test-setup/references/test-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ab-test-setup/references/test-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2Freferences%2Ftest-templates.md -->","isInternal":false,"tokens":1674,"sizeBytes":6250},{"name":"SKILL.md","path":"marketing-skill/skills/ab-test-setup/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ab-test-setup/SKILL.md","title":"ab-test-setup","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fab-test-setup%2FSKILL.md -->","frontmatter":{"name":"ab-test-setup","description":"When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions \"A/B test,\" \"split test,\" \"experiment,\" \"test this change,\" \"variant copy,\" \"multivariate test,\" \"hypothesis,\" \"conversion experiment,\" \"statistical significance,\" or \"test this.\" For tracking implementation, see analytics-tracking.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2347,"sizeBytes":10220},{"name":"creative-frameworks.md","path":"marketing-skill/skills/ad-creative/references/creative-frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ad-creative/references/creative-frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fad-creative%2Freferences%2Fcreative-frameworks.md -->","isInternal":false,"tokens":2461,"sizeBytes":10046},{"name":"platform-specs.md","path":"marketing-skill/skills/ad-creative/references/platform-specs.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ad-creative/references/platform-specs.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fad-creative%2Freferences%2Fplatform-specs.md -->","isInternal":false,"tokens":1624,"sizeBytes":6568},{"name":"SKILL.md","path":"marketing-skill/skills/ad-creative/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ad-creative/SKILL.md","title":"ad-creative","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fad-creative%2FSKILL.md -->","frontmatter":{"name":"ad-creative","description":"When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2648,"sizeBytes":11293},{"name":"authoring-notes.json","path":"marketing-skill/skills/aeo/.claude-plugin/authoring-notes.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/.claude-plugin/authoring-notes.json","title":".claude-plugin Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2F.claude-plugin%2Fauthoring-notes.json -->","frontmatter":{"source":{"upstream":"https://github.com/alirezarezvani/aeo-box/tree/main/answer-engine-optimization","upstream_version":"1.0.0","build_pattern":"Port from aeo-box answer-engine-optimization/ skill (9 modules, 2,464 LOC). Distilled into 3 stdlib CLI tools per claude-skills convention. Preserves E-E-A-T scoring methodology, citation-tracking schema, and industry-aware thresholds. Adds cs-aeo agent + /cs-aeo command + 3 references citing 8 sources each.","distinct_from":"marketing-skill/skills/seo-audit (traditional click-through SEO) — AEO and SEO complement, not substitute. Both can run on the same content."}},"isInternal":false,"tokens":174,"sizeBytes":653},{"name":"aeo_eeat_canon.md","path":"marketing-skill/skills/aeo/references/aeo_eeat_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/references/aeo_eeat_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Faeo_eeat_canon.md -->","isInternal":false,"tokens":2155,"sizeBytes":9718},{"name":"aeo_vs_seo.md","path":"marketing-skill/skills/aeo/references/aeo_vs_seo.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/references/aeo_vs_seo.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Faeo_vs_seo.md -->","isInternal":false,"tokens":2057,"sizeBytes":8755},{"name":"bot_access_and_monitoring.md","path":"marketing-skill/skills/aeo/references/bot_access_and_monitoring.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/references/bot_access_and_monitoring.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Fbot_access_and_monitoring.md -->","isInternal":false,"tokens":1604,"sizeBytes":6839},{"name":"extractable_content_patterns.md","path":"marketing-skill/skills/aeo/references/extractable_content_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/references/extractable_content_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Fextractable_content_patterns.md -->","isInternal":false,"tokens":2534,"sizeBytes":10463},{"name":"llm_citation_patterns.md","path":"marketing-skill/skills/aeo/references/llm_citation_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/references/llm_citation_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2Freferences%2Fllm_citation_patterns.md -->","isInternal":false,"tokens":1969,"sizeBytes":8629},{"name":"SKILL.md","path":"marketing-skill/skills/aeo/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/SKILL.md","title":"aeo","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2FSKILL.md -->","frontmatter":{"name":"aeo","description":"Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools."},"isInternal":false,"tokens":2661,"sizeBytes":11052},{"name":"SKILL.md","path":"marketing-skill/skills/ai-decision-authority/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/ai-decision-authority/SKILL.md","title":"ai-decision-authority","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fai-decision-authority%2FSKILL.md -->","frontmatter":{"name":"ai-decision-authority","description":"Routes marketing and GTM decisions into three AI governance zones (AI-Primary, Collaborative, Human-Primary) by stakes and reversibility. Use when deciding which AI outputs need human review, whether an agent may act autonomously on a task, why AI adoption is collapsing under review requirements, or when auditing a list of workflows for safe autonomy. Triggers on 'should a human review this', 'can the agent just do this', 'AI governance policy', 'human in the loop'."},"isInternal":false,"tokens":1303,"sizeBytes":6126},{"name":"debugging-playbook.md","path":"marketing-skill/skills/analytics-tracking/references/debugging-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/analytics-tracking/references/debugging-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fanalytics-tracking%2Freferences%2Fdebugging-playbook.md -->","isInternal":false,"tokens":1927,"sizeBytes":8140},{"name":"event-taxonomy-guide.md","path":"marketing-skill/skills/analytics-tracking/references/event-taxonomy-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/analytics-tracking/references/event-taxonomy-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fanalytics-tracking%2Freferences%2Fevent-taxonomy-guide.md -->","isInternal":false,"tokens":1969,"sizeBytes":7929},{"name":"gtm-patterns.md","path":"marketing-skill/skills/analytics-tracking/references/gtm-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/analytics-tracking/references/gtm-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fanalytics-tracking%2Freferences%2Fgtm-patterns.md -->","isInternal":false,"tokens":2086,"sizeBytes":8348},{"name":"SKILL.md","path":"marketing-skill/skills/analytics-tracking/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/analytics-tracking/SKILL.md","title":"analytics-tracking","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fanalytics-tracking%2FSKILL.md -->","frontmatter":{"name":"analytics-tracking","description":"Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality. Use when building a tracking plan from scratch, auditing existing analytics for gaps or errors, debugging missing events, or setting up GTM. Trigger keywords: GA4 setup, Google Tag Manager, GTM, event tracking, analytics implementation, conversion tracking, tracking plan, event taxonomy, custom dimensions, UTM tracking, analytics audit, missing events, tracking broken. NOT for analyzing marketing campaign data — use campaign-analytics for that. NOT for BI dashboards — use product-analytics for in-product event analysis.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3579,"sizeBytes":15274},{"name":"aso-audit-template.md","path":"marketing-skill/skills/app-store-optimization/assets/aso-audit-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/app-store-optimization/assets/aso-audit-template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fapp-store-optimization%2Fassets%2Faso-audit-template.md -->","isInternal":false,"tokens":1383,"sizeBytes":4871},{"name":"expected_output.json","path":"marketing-skill/skills/app-store-optimization/expected_output.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/app-store-optimization/expected_output.json","title":"App-store-optimization Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fapp-store-optimization%2Fexpected_output.json -->","frontmatter":{"request_type":"keyword_research","app_name":"TaskFlow Pro","keyword_analysis":{"total_keywords_analyzed":25,"primary_keywords":[{"keyword":"task manager","search_volume":45000,"competition_level":"high","relevance_score":0.95,"difficulty_score":72.5,"potential_score":78.3,"recommendation":"High priority - target immediately"},{"keyword":"productivity app","search_volume":38000,"competition_level":"high","relevance_score":0.9,"difficulty_score":68.2,"potential_score":75.1,"recommendation":"High priority - target immediately"},{"keyword":"todo list","search_volume":52000,"competition_level":"very_high","relevance_score":0.85,"difficulty_score":78.9,"potential_score":71.4,"recommendation":"High priority - target immediately"}],"secondary_keywords":[{"keyword":"team task manager","search_volume":8500,"competition_level":"medium","relevance_score":0.88,"difficulty_score":42.3,"potential_score":68.7,"recommendation":"Good opportunity - include in metadata"},{"keyword":"project planning app","search_volume":12000,"competition_level":"medium","relevance_score":0.75,"difficulty_score":48.1,"potential_score":64.2,"recommendation":"Good opportunity - include in metadata"}],"long_tail_keywords":[{"keyword":"ai task prioritization","search_volume":2800,"competition_level":"low","relevance_score":0.95,"difficulty_score":25.4,"potential_score":82.6,"recommendation":"Excellent long-tail opportunity"},{"keyword":"team productivity tool","search_volume":3500,"competition_level":"low","relevance_score":0.85,"difficulty_score":28.7,"potential_score":79.3,"recommendation":"Excellent long-tail opportunity"}]},"competitor_insights":{"competitors_analyzed":4,"common_keywords":["task","todo","list","productivity","organize","manage"],"keyword_gaps":[{"keyword":"ai prioritization","used_by":["None of the major competitors"],"opportunity":"Unique positioning opportunity"},{"keyword":"smart task manager","used_by":["Things 3"],"opportunity":"Underutilized by most competitors"}]},"metadata_recommendations":{"apple_app_store":{"title_options":[{"title":"TaskFlow - AI Task Manager","length":26,"keywords_included":["task manager","ai"],"strategy":"brand_plus_primary"},{"title":"TaskFlow: Smart Todo & Tasks","length":29,"keywords_included":["todo","tasks"],"strategy":"brand_plus_multiple"}],"subtitle_recommendation":"AI-Powered Team Productivity","keyword_field":"productivity,organize,planner,schedule,workflow,reminders,collaboration,calendar,sync,priorities","description_focus":"Lead with AI differentiation, emphasize team features"},"google_play_store":{"title_options":[{"title":"TaskFlow - AI Task Manager & Team Productivity","length":48,"keywords_included":["task manager","ai","team","productivity"],"strategy":"keyword_rich"}],"short_description_recommendation":"AI task manager - Organize, prioritize, and collaborate with your team","description_focus":"Keywords naturally integrated throughout 4000 character description"}},"strategic_recommendations":["Focus on 'AI prioritization' as unique differentiator - low competition, high relevance","Target 'team task manager' and 'team productivity' keywords - good search volume, lower competition than generic terms","Include long-tail keywords in description for additional discovery opportunities","Test title variations with A/B testing after launch","Monitor competitor keyword changes quarterly"],"priority_actions":[{"action":"Optimize app title with primary keyword","priority":"high","expected_impact":"15-25% improvement in search visibility"},{"action":"Create description highlighting AI features with natural keyword integration","priority":"high","expected_impact":"10-15% improvement in conversion rate"},{"action":"Plan A/B tests for icon and screenshots post-launch","priority":"medium","expected_impact":"5-10% improvement in conversion rate"}],"aso_health_estimate":{"current_score":"N/A (pre-launch)","potential_score_with_optimizations":"75-80/100","key_strengths":["Unique AI differentiation","Clear target audience","Strong feature set"],"areas_to_develop":["Build rating volume post-launch","Monitor and respond to reviews","Continuous keyword 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researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.","metadata":{"triggers":["ASO","app store optimization","app store ranking","app keywords","app metadata","play store optimization","app store listing","improve app rankings","app visibility","app store SEO","mobile app marketing","app conversion rate"]}},"isInternal":false,"tokens":3859,"sizeBytes":16953},{"name":"brand-identity-and-framework.md","path":"marketing-skill/skills/brand-guidelines/references/brand-identity-and-framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/brand-guidelines/references/brand-identity-and-framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fbrand-guidelines%2Freferences%2Fbrand-identity-and-framework.md -->","isInternal":false,"tokens":2348,"sizeBytes":9434},{"name":"SKILL.md","path":"marketing-skill/skills/brand-guidelines/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/brand-guidelines/SKILL.md","title":"brand-guidelines","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fbrand-guidelines%2FSKILL.md -->","frontmatter":{"name":"brand-guidelines","description":"When the user wants to apply, document, or enforce brand guidelines for any product or company. 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Use when someone is naming a company, brand, or product and cares about how it lands across languages and regions — for example a name that sounds right at home but might read oddly to English speakers, or an authentic name they want to check before committing. Trigger this for any request about choosing a business name, checking if a name \"works\" abroad, spotting bad meanings in other languages, or making a name sound trustworthy in a specific market — even if the person doesn't say the word \"skill\"."},"isInternal":false,"tokens":2476,"sizeBytes":11186},{"name":"ab_test_template.md","path":"marketing-skill/skills/campaign-analytics/assets/ab_test_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/campaign-analytics/assets/ab_test_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcampaign-analytics%2Fassets%2Fab_test_template.md 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-->","frontmatter":{"journeys":[{"journey_id":"j001","touchpoints":[{"channel":"organic_search","timestamp":"2025-10-01T10:00:00","interaction":"click"},{"channel":"email","timestamp":"2025-10-05T14:30:00","interaction":"open"},{"channel":"paid_search","timestamp":"2025-10-08T09:15:00","interaction":"click"}],"converted":true,"revenue":500},{"journey_id":"j002","touchpoints":[{"channel":"paid_social","timestamp":"2025-10-02T11:00:00","interaction":"click"},{"channel":"organic_search","timestamp":"2025-10-06T16:45:00","interaction":"click"},{"channel":"email","timestamp":"2025-10-09T08:00:00","interaction":"click"},{"channel":"direct","timestamp":"2025-10-10T13:20:00","interaction":"visit"}],"converted":true,"revenue":1200},{"journey_id":"j003","touchpoints":[{"channel":"display","timestamp":"2025-10-03T09:30:00","interaction":"view"},{"channel":"paid_search","timestamp":"2025-10-07T10:00:00","interaction":"click"}],"converted":true,"revenue":350},{"journey_id":"j004","touchpoints":[{"channel":"organic_social","timestamp":"2025-10-01T08:00:00","interaction":"click"},{"channel":"email","timestamp":"2025-10-04T12:00:00","interaction":"click"},{"channel":"paid_search","timestamp":"2025-10-08T14:00:00","interaction":"click"},{"channel":"email","timestamp":"2025-10-11T09:00:00","interaction":"click"},{"channel":"direct","timestamp":"2025-10-12T16:00:00","interaction":"visit"}],"converted":true,"revenue":800},{"journey_id":"j005","touchpoints":[{"channel":"paid_social","timestamp":"2025-10-05T10:00:00","interaction":"click"},{"channel":"display","timestamp":"2025-10-08T11:30:00","interaction":"view"}],"converted":false,"revenue":0},{"journey_id":"j006","touchpoints":[{"channel":"referral","timestamp":"2025-10-06T14:00:00","interaction":"click"},{"channel":"email","timestamp":"2025-10-10T09:30:00","interaction":"click"},{"channel":"paid_search","timestamp":"2025-10-13T11:00:00","interaction":"click"}],"converted":true,"revenue":650},{"journey_id":"j007","touchpoints":[{"channel":"organic_search","timestamp":"2025-10-04T08:30:00","interaction":"click"}],"converted":true,"revenue":200},{"journey_id":"j008","touchpoints":[{"channel":"paid_social","timestamp":"2025-10-07T13:00:00","interaction":"click"},{"channel":"organic_search","timestamp":"2025-10-09T10:00:00","interaction":"click"},{"channel":"email","timestamp":"2025-10-12T15:00:00","interaction":"click"}],"converted":false,"revenue":0}],"funnel":{"stages":["Awareness","Interest","Consideration","Intent","Purchase"],"counts":[10000,5200,2800,1400,420]},"segments":{"organic":{"counts":[5000,2800,1600,850,280]},"paid":{"counts":[3000,1500,750,350,90]},"email":{"counts":[2000,900,450,200,50]}},"stages":["Awareness","Interest","Consideration","Intent","Purchase"],"campaigns":[{"name":"Spring 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Use when analyzing marketing campaigns, ad performance, attribution models, conversion rates, or calculating marketing ROI, ROAS, CPA, and campaign metrics across channels.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","domain":"campaign-analytics","updated":"2026-02-06","python-tools":"attribution_analyzer.py, funnel_analyzer.py, campaign_roi_calculator.py","tech-stack":"marketing-analytics, attribution-modeling"}},"isInternal":false,"tokens":1862,"sizeBytes":8406},{"name":"cancel-flow-playbook.md","path":"marketing-skill/skills/churn-prevention/references/cancel-flow-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/churn-prevention/references/cancel-flow-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fchurn-prevention%2Freferences%2Fcancel-flow-playbook.md -->","isInternal":false,"tokens":1903,"sizeBytes":8573},{"name":"dunning-guide.md","path":"marketing-skill/skills/churn-prevention/references/dunning-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/churn-prevention/references/dunning-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fchurn-prevention%2Freferences%2Fdunning-guide.md -->","isInternal":false,"tokens":2040,"sizeBytes":8652},{"name":"SKILL.md","path":"marketing-skill/skills/churn-prevention/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/churn-prevention/SKILL.md","title":"churn-prevention","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fchurn-prevention%2FSKILL.md -->","frontmatter":{"name":"churn-prevention","description":"Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing a cancel flow, building save offers, setting up dunning emails, or reducing failed-payment churn. Trigger keywords: cancel flow, churn reduction, save offers, dunning, exit survey, payment recovery, win-back, involuntary churn, failed payments, cancel page. NOT for customer health scoring or expansion revenue — use customer-success-manager for that.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2566,"sizeBytes":11104},{"name":"deliverability-guide.md","path":"marketing-skill/skills/cold-email/references/deliverability-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/cold-email/references/deliverability-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcold-email%2Freferences%2Fdeliverability-guide.md -->","isInternal":false,"tokens":2089,"sizeBytes":9167},{"name":"follow-up-playbook.md","path":"marketing-skill/skills/cold-email/references/follow-up-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/cold-email/references/follow-up-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcold-email%2Freferences%2Ffollow-up-playbook.md -->","isInternal":false,"tokens":2204,"sizeBytes":9288},{"name":"frameworks.md","path":"marketing-skill/skills/cold-email/references/frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/cold-email/references/frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcold-email%2Freferences%2Fframeworks.md -->","isInternal":false,"tokens":2062,"sizeBytes":9209},{"name":"SKILL.md","path":"marketing-skill/skills/cold-email/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/cold-email/SKILL.md","title":"cold-email","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcold-email%2FSKILL.md -->","frontmatter":{"name":"cold-email","description":"When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them. Use when the user mentions 'cold email,' 'cold outreach,' 'prospecting emails,' 'SDR emails,' 'sales emails,' 'first touch email,' 'follow-up sequence,' or 'email prospecting.' Also use when they share an email draft that sounds too sales-y and needs to be humanized. Distinct from email-sequence (lifecycle/nurture to opted-in subscribers) — this is unsolicited outreach to new prospects. NOT for lifecycle emails, newsletters, or drip campaigns (use email-sequence).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3423,"sizeBytes":14706},{"name":"content-architecture.md","path":"marketing-skill/skills/competitor-alternatives/references/content-architecture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/competitor-alternatives/references/content-architecture.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcompetitor-alternatives%2Freferences%2Fcontent-architecture.md -->","isInternal":false,"tokens":1719,"sizeBytes":7370},{"name":"templates.md","path":"marketing-skill/skills/competitor-alternatives/references/templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/competitor-alternatives/references/templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcompetitor-alternatives%2Freferences%2Ftemplates.md -->","isInternal":false,"tokens":1275,"sizeBytes":5084},{"name":"SKILL.md","path":"marketing-skill/skills/competitor-alternatives/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/competitor-alternatives/SKILL.md","title":"competitor-alternatives","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcompetitor-alternatives%2FSKILL.md -->","frontmatter":{"name":"competitor-alternatives","description":"When the user wants to create competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' 'competitive landing pages,' 'switch from competitor,' or 'comparison content.' Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. Emphasizes deep research, modular content architecture, and varied section types beyond feature tables.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2400,"sizeBytes":11162},{"name":"content_calendar_template.md","path":"marketing-skill/skills/content-creator/assets/content_calendar_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/assets/content_calendar_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Fassets%2Fcontent_calendar_template.md -->","isInternal":false,"tokens":471,"sizeBytes":1610},{"name":"brand_voice_analysis_example.md","path":"marketing-skill/skills/content-creator/examples/brand_voice_analysis_example.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/examples/brand_voice_analysis_example.md","title":"Examples Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Fexamples%2Fbrand_voice_analysis_example.md -->","isInternal":false,"tokens":1183,"sizeBytes":4992},{"name":"seo_optimization_example.md","path":"marketing-skill/skills/content-creator/examples/seo_optimization_example.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/examples/seo_optimization_example.md","title":"Examples Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Fexamples%2Fseo_optimization_example.md -->","isInternal":false,"tokens":1697,"sizeBytes":7309},{"name":"analytics_guide.md","path":"marketing-skill/skills/content-creator/references/analytics_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/references/analytics_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Freferences%2Fanalytics_guide.md -->","isInternal":false,"tokens":2061,"sizeBytes":8824},{"name":"brand_guidelines.md","path":"marketing-skill/skills/content-creator/references/brand_guidelines.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/references/brand_guidelines.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Freferences%2Fbrand_guidelines.md -->","isInternal":false,"tokens":1599,"sizeBytes":6814},{"name":"content_frameworks.md","path":"marketing-skill/skills/content-creator/references/content_frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/references/content_frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Freferences%2Fcontent_frameworks.md -->","isInternal":false,"tokens":2827,"sizeBytes":11170},{"name":"social_media_optimization.md","path":"marketing-skill/skills/content-creator/references/social_media_optimization.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/references/social_media_optimization.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2Freferences%2Fsocial_media_optimization.md -->","isInternal":false,"tokens":2526,"sizeBytes":10040},{"name":"SKILL.md","path":"marketing-skill/skills/content-creator/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-creator/SKILL.md","title":"content-creator","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-creator%2FSKILL.md -->","frontmatter":{"name":"content-creator","description":"Deprecated redirect skill that routes legacy 'content creator' requests to the correct specialist. Use when a user invokes 'content creator', asks to write a blog post, article, guide, or brand voice analysis (routes to content-production), or asks to plan content, build a topic cluster, or create a content calendar (routes to content-strategy). Does not handle requests directly — identifies user intent and redirects to content-production for writing/SEO/brand-voice tasks or content-strategy for planning tasks.","license":"MIT","metadata":{"version":"2.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06","status":"deprecated"}},"isInternal":false,"tokens":627,"sizeBytes":2871},{"name":"ai-tells-checklist.md","path":"marketing-skill/skills/content-humanizer/references/ai-tells-checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-humanizer/references/ai-tells-checklist.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-humanizer%2Freferences%2Fai-tells-checklist.md -->","isInternal":false,"tokens":1747,"sizeBytes":7509},{"name":"voice-techniques.md","path":"marketing-skill/skills/content-humanizer/references/voice-techniques.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-humanizer/references/voice-techniques.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-humanizer%2Freferences%2Fvoice-techniques.md -->","isInternal":false,"tokens":1924,"sizeBytes":8924},{"name":"SKILL.md","path":"marketing-skill/skills/content-humanizer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-humanizer/SKILL.md","title":"content-humanizer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-humanizer%2FSKILL.md -->","frontmatter":{"name":"content-humanizer","description":"Makes AI-generated content sound genuinely human — not just cleaned up, but alive. Use when content feels robotic, uses too many AI clichés, lacks personality, or reads like it was written by committee. Triggers: 'this sounds like AI', 'make it more human', 'add personality', 'it feels generic', 'sounds robotic', 'fix AI writing', 'inject our voice'. NOT for initial content creation (use content-production). NOT for SEO optimization (use content-production Mode 3).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3406,"sizeBytes":14828},{"name":"ai-citation-readiness.md","path":"marketing-skill/skills/content-production/references/ai-citation-readiness.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-production/references/ai-citation-readiness.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-production%2Freferences%2Fai-citation-readiness.md -->","isInternal":false,"tokens":705,"sizeBytes":3131},{"name":"content-brief-guide.md","path":"marketing-skill/skills/content-production/references/content-brief-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-production/references/content-brief-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-production%2Freferences%2Fcontent-brief-guide.md -->","isInternal":false,"tokens":1333,"sizeBytes":6012},{"name":"content-templates.md","path":"marketing-skill/skills/content-production/references/content-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-production/references/content-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-production%2Freferences%2Fcontent-templates.md -->","isInternal":false,"tokens":1052,"sizeBytes":3474},{"name":"optimization-checklist.md","path":"marketing-skill/skills/content-production/references/optimization-checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-production/references/optimization-checklist.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-production%2Freferences%2Foptimization-checklist.md -->","isInternal":false,"tokens":1320,"sizeBytes":5295},{"name":"SKILL.md","path":"marketing-skill/skills/content-production/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-production/SKILL.md","title":"content-production","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-production%2FSKILL.md -->","frontmatter":{"name":"content-production","description":"Full content production pipeline — takes a topic from blank page to published-ready piece. Use when you need to execute content: write a blog post, article, or guide end-to-end. Triggers: 'write a post about', 'draft an article', 'create content for', 'help me write', 'I need a blog post'. NOT for content strategy or calendar planning (use content-strategy). NOT for repurposing existing content (use content-repurposing). NOT for social captions only.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2626,"sizeBytes":11368},{"name":"content-brief-template.md","path":"marketing-skill/skills/content-production/templates/content-brief-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-production/templates/content-brief-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-production%2Ftemplates%2Fcontent-brief-template.md -->","isInternal":false,"tokens":657,"sizeBytes":2617},{"name":"content-strategy-reference.md","path":"marketing-skill/skills/content-strategy/references/content-strategy-reference.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-strategy/references/content-strategy-reference.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-strategy%2Freferences%2Fcontent-strategy-reference.md -->","isInternal":false,"tokens":1966,"sizeBytes":8749},{"name":"SKILL.md","path":"marketing-skill/skills/content-strategy/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/content-strategy/SKILL.md","title":"content-strategy","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcontent-strategy%2FSKILL.md -->","frontmatter":{"name":"content-strategy","description":"When the user wants to plan a content strategy, decide what content to create, or figure out what topics to cover. Also use when the user mentions \"content strategy,\" \"what should I write about,\" \"content ideas,\" \"blog strategy,\" \"topic clusters,\" or \"content planning.\" For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1478,"sizeBytes":6990},{"name":"ai-detection-patterns.md","path":"marketing-skill/skills/copy-editing/references/ai-detection-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/copy-editing/references/ai-detection-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcopy-editing%2Freferences%2Fai-detection-patterns.md -->","isInternal":false,"tokens":1030,"sizeBytes":4039},{"name":"plain-english-alternatives.md","path":"marketing-skill/skills/copy-editing/references/plain-english-alternatives.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/copy-editing/references/plain-english-alternatives.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcopy-editing%2Freferences%2Fplain-english-alternatives.md -->","isInternal":false,"tokens":2022,"sizeBytes":8146},{"name":"SKILL.md","path":"marketing-skill/skills/copy-editing/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/copy-editing/SKILL.md","title":"copy-editing","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcopy-editing%2FSKILL.md -->","frontmatter":{"name":"copy-editing","description":"When the user wants to edit, review, or improve existing marketing copy. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' or 'copy sweep.' This skill provides a systematic approach to editing marketing copy through multiple focused passes.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3821,"sizeBytes":16684},{"name":"copy-frameworks.md","path":"marketing-skill/skills/copywriting/references/copy-frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/copywriting/references/copy-frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcopywriting%2Freferences%2Fcopy-frameworks.md -->","isInternal":false,"tokens":1850,"sizeBytes":7428},{"name":"natural-transitions.md","path":"marketing-skill/skills/copywriting/references/natural-transitions.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/copywriting/references/natural-transitions.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcopywriting%2Freferences%2Fnatural-transitions.md -->","isInternal":false,"tokens":1241,"sizeBytes":5179},{"name":"SKILL.md","path":"marketing-skill/skills/copywriting/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/copywriting/SKILL.md","title":"copywriting","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fcopywriting%2FSKILL.md -->","frontmatter":{"name":"copywriting","description":"When the user wants to write, rewrite, or improve marketing copy for any page — including homepage, landing pages, pricing pages, feature pages, about pages, or product pages. Also use when the user says \"write copy for,\" \"improve this copy,\" \"rewrite this page,\" \"marketing copy,\" \"headline help,\" or \"CTA copy.\" For email copy, see email-sequence. For popup copy, see popup-cro.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2348,"sizeBytes":10313},{"name":"email-sequence-playbook.md","path":"marketing-skill/skills/email-sequence/references/email-sequence-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/email-sequence/references/email-sequence-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Femail-sequence%2Freferences%2Femail-sequence-playbook.md -->","isInternal":false,"tokens":1310,"sizeBytes":4820},{"name":"SKILL.md","path":"marketing-skill/skills/email-sequence/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/email-sequence/SKILL.md","title":"email-sequence","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Femail-sequence%2FSKILL.md -->","frontmatter":{"name":"email-sequence","description":"When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions \"email sequence,\" \"drip campaign,\" \"nurture sequence,\" \"onboarding emails,\" \"welcome sequence,\" \"re-engagement emails,\" \"email automation,\" or \"lifecycle emails.\" For in-app onboarding, see onboarding-cro.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1275,"sizeBytes":5912},{"name":"form-cro-playbook.md","path":"marketing-skill/skills/form-cro/references/form-cro-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/form-cro/references/form-cro-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fform-cro%2Freferences%2Fform-cro-playbook.md -->","isInternal":false,"tokens":1449,"sizeBytes":6156},{"name":"SKILL.md","path":"marketing-skill/skills/form-cro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/form-cro/SKILL.md","title":"form-cro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fform-cro%2FSKILL.md -->","frontmatter":{"name":"form-cro","description":"When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions \"form optimization,\" \"lead form conversions,\" \"form friction,\" \"form fields,\" \"form completion rate,\" or \"contact form.\" For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-cro.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2042,"sizeBytes":9419},{"name":"launch-playbook.md","path":"marketing-skill/skills/free-tool-strategy/references/launch-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/free-tool-strategy/references/launch-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Ffree-tool-strategy%2Freferences%2Flaunch-playbook.md -->","isInternal":false,"tokens":1974,"sizeBytes":8187},{"name":"tool-types-guide.md","path":"marketing-skill/skills/free-tool-strategy/references/tool-types-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/free-tool-strategy/references/tool-types-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Ffree-tool-strategy%2Freferences%2Ftool-types-guide.md -->","isInternal":false,"tokens":2121,"sizeBytes":9367},{"name":"SKILL.md","path":"marketing-skill/skills/free-tool-strategy/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/free-tool-strategy/SKILL.md","title":"free-tool-strategy","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Ffree-tool-strategy%2FSKILL.md -->","frontmatter":{"name":"free-tool-strategy","description":"When the user wants to build a free tool for marketing — lead generation, SEO value, or brand awareness. Use when they mention 'engineering as marketing,' 'free tool,' 'calculator,' 'generator,' 'checker,' 'grader,' 'marketing tool,' 'lead gen tool,' 'build something for traffic,' 'interactive tool,' or 'free resource.' Covers idea evaluation, tool design, and launch strategy. For pure SEO content strategy (no tool), use seo-audit or content-strategy instead.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2859,"sizeBytes":12276},{"name":"launch-frameworks-and-checklists.md","path":"marketing-skill/skills/launch-strategy/references/launch-frameworks-and-checklists.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/launch-strategy/references/launch-frameworks-and-checklists.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Flaunch-strategy%2Freferences%2Flaunch-frameworks-and-checklists.md -->","isInternal":false,"tokens":2324,"sizeBytes":10860},{"name":"SKILL.md","path":"marketing-skill/skills/launch-strategy/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/launch-strategy/SKILL.md","title":"launch-strategy","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Flaunch-strategy%2FSKILL.md -->","frontmatter":{"name":"launch-strategy","description":"When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' 'product update,' 'GTM plan,' 'launch checklist,' or 'launch momentum.' This skill covers phased launches, channel strategy, and ongoing launch momentum.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1229,"sizeBytes":5829},{"name":"local-schema-types.md","path":"marketing-skill/skills/local-seo-manager/references/local-schema-types.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/local-seo-manager/references/local-schema-types.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Flocal-seo-manager%2Freferences%2Flocal-schema-types.md -->","isInternal":false,"tokens":2054,"sizeBytes":8074},{"name":"local-seo-checklist.md","path":"marketing-skill/skills/local-seo-manager/references/local-seo-checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/local-seo-manager/references/local-seo-checklist.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Flocal-seo-manager%2Freferences%2Flocal-seo-checklist.md -->","isInternal":false,"tokens":1538,"sizeBytes":6171},{"name":"review-response-templates.md","path":"marketing-skill/skills/local-seo-manager/references/review-response-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/local-seo-manager/references/review-response-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Flocal-seo-manager%2Freferences%2Freview-response-templates.md -->","isInternal":false,"tokens":1936,"sizeBytes":8511},{"name":"SKILL.md","path":"marketing-skill/skills/local-seo-manager/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/local-seo-manager/SKILL.md","title":"local-seo-manager","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Flocal-seo-manager%2FSKILL.md -->","frontmatter":{"name":"local-seo-manager","description":"Manage local SEO for service-area businesses — appliance repair, HVAC, plumbing, cleaning, and any business that serves customers at their location. Use when the user wants to: audit Google Business Profile, generate neighborhood service area pages, check NAP consistency across directories, create LocalBusiness schema, or write review responses. Triggers: 'local SEO', 'Google Business Profile', 'GBP', 'service area page', 'NAP consistency', 'local citations', 'LocalBusiness schema', 'review responses', 'Google Maps ranking'. NOT for national SEO (use seo-audit). NOT for general schema (use schema-markup). NOT for AI answer-engine visibility (use aeo).","license":"MIT","metadata":{"version":"1.0.0","author":"Stan Varashilov (Steffonet)","category":"marketing","updated":"2026-06-03"}},"isInternal":false,"tokens":3102,"sizeBytes":13345},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-context/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-context/SKILL.md","title":"marketing-context","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-context%2FSKILL.md -->","frontmatter":{"name":"marketing-context","description":"Create and maintain the marketing context document that all marketing skills read before starting. Use when the user mentions 'marketing context,' 'brand voice,' 'set up context,' 'target audience,' 'ICP,' 'style guide,' 'who is my customer,' 'positioning,' or wants to avoid repeating foundational information across marketing tasks. Run this at the start of any new project before using other marketing skills.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1715,"sizeBytes":7779},{"name":"marketing-context-template.md","path":"marketing-skill/skills/marketing-context/templates/marketing-context-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-context/templates/marketing-context-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-context%2Ftemplates%2Fmarketing-context-template.md -->","isInternal":false,"tokens":946,"sizeBytes":3439},{"name":"attribution-guide.md","path":"marketing-skill/skills/marketing-demand-acquisition/references/attribution-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-demand-acquisition/references/attribution-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-demand-acquisition%2Freferences%2Fattribution-guide.md -->","isInternal":false,"tokens":1336,"sizeBytes":5622},{"name":"campaign-templates.md","path":"marketing-skill/skills/marketing-demand-acquisition/references/campaign-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-demand-acquisition/references/campaign-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-demand-acquisition%2Freferences%2Fcampaign-templates.md -->","isInternal":false,"tokens":1585,"sizeBytes":5954},{"name":"hubspot-workflows.md","path":"marketing-skill/skills/marketing-demand-acquisition/references/hubspot-workflows.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-demand-acquisition/references/hubspot-workflows.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-demand-acquisition%2Freferences%2Fhubspot-workflows.md -->","isInternal":false,"tokens":1104,"sizeBytes":4573},{"name":"international-playbooks.md","path":"marketing-skill/skills/marketing-demand-acquisition/references/international-playbooks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-demand-acquisition/references/international-playbooks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-demand-acquisition%2Freferences%2Finternational-playbooks.md -->","isInternal":false,"tokens":1229,"sizeBytes":5270},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-demand-acquisition/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-demand-acquisition/SKILL.md","title":"marketing-demand-acquisition","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-demand-acquisition%2FSKILL.md -->","frontmatter":{"name":"marketing-demand-acquisition","description":"Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs. Use when planning demand gen strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, technical SEO, and co-marketing partnerships. Default calibration profile is a Series A+ B2B SaaS scaling internationally (EU/US/Canada, hybrid PLG/Sales-Led) — adapt benchmarks for other stages and motions rather than skipping the skill.","metadata":{"version":"1.1.0","author":"Alireza Rezvani","category":"marketing","domain":"demand-generation","updated":"2026-06","triggers":["demand gen","demand generation","paid ads","paid media","LinkedIn ads","Google ads","Meta ads","CAC","customer acquisition cost","lead generation","MQL","SQL","pipeline generation","acquisition strategy","HubSpot campaigns"]}},"isInternal":false,"tokens":2510,"sizeBytes":9969},{"name":"ideas-by-category.md","path":"marketing-skill/skills/marketing-ideas/references/ideas-by-category.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-ideas/references/ideas-by-category.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-ideas%2Freferences%2Fideas-by-category.md -->","isInternal":false,"tokens":2991,"sizeBytes":14682},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-ideas/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-ideas/SKILL.md","title":"marketing-ideas","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-ideas%2FSKILL.md -->","frontmatter":{"name":"marketing-ideas","description":"When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' or 'ideas to grow.' This skill provides 139 proven marketing approaches organized by category.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1835,"sizeBytes":7932},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-ops/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-ops/SKILL.md","title":"marketing-ops","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-ops%2FSKILL.md -->","frontmatter":{"name":"marketing-ops","description":"Central router for the marketing skill ecosystem. Use when unsure which marketing skill to use, when orchestrating a multi-skill campaign, or when coordinating across content, SEO, CRO, channels, and analytics. Also use when the user mentions 'marketing help,' 'campaign plan,' 'what should I do next,' 'marketing priorities,' or 'coordinate marketing.'","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2828,"sizeBytes":11415},{"name":"mental-models-catalog.md","path":"marketing-skill/skills/marketing-psychology/references/mental-models-catalog.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-psychology/references/mental-models-catalog.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-psychology%2Freferences%2Fmental-models-catalog.md -->","isInternal":false,"tokens":3670,"sizeBytes":18944},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-psychology/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-psychology/SKILL.md","title":"marketing-psychology","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-psychology%2FSKILL.md -->","frontmatter":{"name":"marketing-psychology","description":"When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.","license":"MIT","metadata":{"version":"1.1.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1569,"sizeBytes":6860},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-skills/SKILL.md","title":"marketing-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-skills%2FSKILL.md -->","frontmatter":{"name":"marketing-skills","description":"Directory and router for the marketing skills library. Use when you need to find the right marketing skill for a task, see what marketing capabilities exist, or get oriented in this plugin. 44 specialist skills across 8 pods (content, SEO + AEO, CRO, channels, growth, intelligence, sales enablement, ops), 59 stdlib Python tools. Routes to one skill — it does not execute marketing work itself.","license":"MIT","metadata":{"version":"2.10.3","author":"Alireza Rezvani","tags":["marketing","router","index"],"agents":["claude-code","codex-cli","openclaw"]}},"isInternal":false,"tokens":1395,"sizeBytes":5272},{"name":"international-gtm.md","path":"marketing-skill/skills/marketing-strategy-pmm/references/international-gtm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-strategy-pmm/references/international-gtm.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-strategy-pmm%2Freferences%2Finternational-gtm.md -->","isInternal":false,"tokens":2556,"sizeBytes":10517},{"name":"launch-checklists.md","path":"marketing-skill/skills/marketing-strategy-pmm/references/launch-checklists.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-strategy-pmm/references/launch-checklists.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-strategy-pmm%2Freferences%2Flaunch-checklists.md -->","isInternal":false,"tokens":2457,"sizeBytes":8992},{"name":"messaging-templates.md","path":"marketing-skill/skills/marketing-strategy-pmm/references/messaging-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-strategy-pmm/references/messaging-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-strategy-pmm%2Freferences%2Fmessaging-templates.md -->","isInternal":false,"tokens":2648,"sizeBytes":10783},{"name":"positioning-frameworks.md","path":"marketing-skill/skills/marketing-strategy-pmm/references/positioning-frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-strategy-pmm/references/positioning-frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-strategy-pmm%2Freferences%2Fpositioning-frameworks.md -->","isInternal":false,"tokens":1815,"sizeBytes":7807},{"name":"SKILL.md","path":"marketing-skill/skills/marketing-strategy-pmm/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/marketing-strategy-pmm/SKILL.md","title":"marketing-strategy-pmm","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fmarketing-strategy-pmm%2FSKILL.md -->","frontmatter":{"name":"marketing-strategy-pmm","description":"Product marketing skill for positioning, GTM strategy, competitive intelligence, and product launches. Use when the user asks about product positioning, go-to-market planning, competitive analysis, target audience definition, ICP definition, market research, launch plans, or sales enablement. Covers April Dunford positioning, ICP definition, competitive battlecards, launch playbooks, and international market entry. Produces deliverables including positioning statements, battlecard documents, launch plans, and go-to-market strategies.","metadata":{"triggers":["product marketing","PMM","positioning","GTM strategy","go-to-market","competitive analysis","battlecard","product launch","market entry","sales enablement","win loss analysis"]}},"isInternal":false,"tokens":2974,"sizeBytes":12410},{"name":"SKILL.md","path":"marketing-skill/skills/onboarding-cro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/onboarding-cro/SKILL.md","title":"onboarding-cro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fonboarding-cro%2FSKILL.md -->","frontmatter":{"name":"onboarding-cro","description":"When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions \"onboarding flow,\" \"activation rate,\" \"user activation,\" \"first-run experience,\" \"empty states,\" \"onboarding checklist,\" \"aha moment,\" or \"new user experience.\" For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1987,"sizeBytes":9032},{"name":"SKILL.md","path":"marketing-skill/skills/page-cro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/page-cro/SKILL.md","title":"page-cro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpage-cro%2FSKILL.md -->","frontmatter":{"name":"page-cro","description":"When the user wants to optimize, improve, or increase conversions on any marketing page — including homepage, landing pages, pricing pages, feature pages, or blog posts. Also use when the user says \"CRO,\" \"conversion rate optimization,\" \"this page isn't converting,\" \"improve conversions,\" or \"why isn't this page working.\" For signup/registration flows, see signup-flow-cro. For post-signup activation, see onboarding-cro. For forms outside of signup, see form-cro. For popups/modals, see popup-cro.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2109,"sizeBytes":9632},{"name":"ad-copy-templates.md","path":"marketing-skill/skills/paid-ads/references/ad-copy-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paid-ads/references/ad-copy-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaid-ads%2Freferences%2Fad-copy-templates.md -->","isInternal":false,"tokens":1111,"sizeBytes":4446},{"name":"audience-targeting.md","path":"marketing-skill/skills/paid-ads/references/audience-targeting.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paid-ads/references/audience-targeting.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaid-ads%2Freferences%2Faudience-targeting.md -->","isInternal":false,"tokens":1391,"sizeBytes":5716},{"name":"copy-frameworks.md","path":"marketing-skill/skills/paid-ads/references/copy-frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paid-ads/references/copy-frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaid-ads%2Freferences%2Fcopy-frameworks.md -->","isInternal":false,"tokens":1005,"sizeBytes":3759},{"name":"platform-setup-checklists.md","path":"marketing-skill/skills/paid-ads/references/platform-setup-checklists.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paid-ads/references/platform-setup-checklists.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaid-ads%2Freferences%2Fplatform-setup-checklists.md -->","isInternal":false,"tokens":1714,"sizeBytes":6943},{"name":"scoring-system.md","path":"marketing-skill/skills/paid-ads/references/scoring-system.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paid-ads/references/scoring-system.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaid-ads%2Freferences%2Fscoring-system.md -->","isInternal":false,"tokens":945,"sizeBytes":3910},{"name":"SKILL.md","path":"marketing-skill/skills/paid-ads/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paid-ads/SKILL.md","title":"paid-ads","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaid-ads%2FSKILL.md -->","frontmatter":{"name":"paid-ads","description":"When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ad copy,' 'ad creative,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' or 'audience targeting.' This skill covers campaign strategy, ad creation, audience targeting, and optimization.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3040,"sizeBytes":13136},{"name":"SKILL.md","path":"marketing-skill/skills/paywall-upgrade-cro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/paywall-upgrade-cro/SKILL.md","title":"paywall-upgrade-cro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpaywall-upgrade-cro%2FSKILL.md -->","frontmatter":{"name":"paywall-upgrade-cro","description":"When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions \"paywall,\" \"upgrade screen,\" \"upgrade modal,\" \"upsell,\" \"feature gate,\" \"convert free to paid,\" \"freemium conversion,\" \"trial expiration screen,\" \"limit reached screen,\" \"plan upgrade prompt,\" or \"in-app pricing.\" Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1813,"sizeBytes":7942},{"name":"popup-cro-playbook.md","path":"marketing-skill/skills/popup-cro/references/popup-cro-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/popup-cro/references/popup-cro-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpopup-cro%2Freferences%2Fpopup-cro-playbook.md -->","isInternal":false,"tokens":1491,"sizeBytes":6128},{"name":"SKILL.md","path":"marketing-skill/skills/popup-cro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/popup-cro/SKILL.md","title":"popup-cro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpopup-cro%2FSKILL.md -->","frontmatter":{"name":"popup-cro","description":"When the user wants to create or optimize popups, modals, overlays, slide-ins, or banners for conversion purposes. Also use when the user mentions \"exit intent,\" \"popup conversions,\" \"modal optimization,\" \"lead capture popup,\" \"email popup,\" \"announcement banner,\" or \"overlay.\" For forms outside of popups, see form-cro. For general page conversion optimization, see page-cro.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1734,"sizeBytes":7796},{"name":"pricing-models.md","path":"marketing-skill/skills/pricing-strategy/references/pricing-models.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/pricing-strategy/references/pricing-models.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpricing-strategy%2Freferences%2Fpricing-models.md -->","isInternal":false,"tokens":1830,"sizeBytes":7885},{"name":"pricing-page-playbook.md","path":"marketing-skill/skills/pricing-strategy/references/pricing-page-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/pricing-strategy/references/pricing-page-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpricing-strategy%2Freferences%2Fpricing-page-playbook.md -->","isInternal":false,"tokens":1862,"sizeBytes":7834},{"name":"SKILL.md","path":"marketing-skill/skills/pricing-strategy/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/pricing-strategy/SKILL.md","title":"pricing-strategy","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fpricing-strategy%2FSKILL.md -->","frontmatter":{"name":"pricing-strategy","description":"Design, optimize, and communicate SaaS pricing — tier structure, value metrics, pricing pages, and price increase strategy. Use when building a pricing model from scratch, redesigning existing pricing, planning a price increase, or improving a pricing page. Trigger keywords: pricing tiers, pricing page, price increase, packaging, value metric, per seat pricing, usage-based pricing, freemium, good-better-best, pricing strategy, monetization, pricing page conversion, Van Westendorp. NOT for broader product strategy — use product-strategist for that. NOT for customer success or renewals — use customer-success-manager for expansion revenue.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3294,"sizeBytes":14446},{"name":"SKILL.md","path":"marketing-skill/skills/programmatic-seo/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/programmatic-seo/SKILL.md","title":"programmatic-seo","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fprogrammatic-seo%2FSKILL.md -->","frontmatter":{"name":"programmatic-seo","description":"When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions \"programmatic SEO,\" \"template pages,\" \"pages at scale,\" \"directory pages,\" \"location pages,\" \"[keyword] + [city] pages,\" \"comparison pages,\" \"integration pages,\" or \"building many pages for SEO.\" For auditing existing SEO issues, see seo-audit.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2396,"sizeBytes":10668},{"name":"README.md","path":"marketing-skill/skills/prompt-engineer-toolkit/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/prompt-engineer-toolkit/README.md","title":"Prompt-engineer-toolkit Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fprompt-engineer-toolkit%2FREADME.md -->","isInternal":false,"tokens":312,"sizeBytes":1244},{"name":"evaluation-rubric.md","path":"marketing-skill/skills/prompt-engineer-toolkit/references/evaluation-rubric.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/prompt-engineer-toolkit/references/evaluation-rubric.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fprompt-engineer-toolkit%2Freferences%2Fevaluation-rubric.md -->","isInternal":false,"tokens":1097,"sizeBytes":4752},{"name":"prompt-templates.md","path":"marketing-skill/skills/prompt-engineer-toolkit/references/prompt-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/prompt-engineer-toolkit/references/prompt-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fprompt-engineer-toolkit%2Freferences%2Fprompt-templates.md -->","isInternal":false,"tokens":1452,"sizeBytes":6097},{"name":"technique-guide.md","path":"marketing-skill/skills/prompt-engineer-toolkit/references/technique-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/prompt-engineer-toolkit/references/technique-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fprompt-engineer-toolkit%2Freferences%2Ftechnique-guide.md -->","isInternal":false,"tokens":1292,"sizeBytes":5983},{"name":"SKILL.md","path":"marketing-skill/skills/prompt-engineer-toolkit/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/prompt-engineer-toolkit/SKILL.md","title":"prompt-engineer-toolkit","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fprompt-engineer-toolkit%2FSKILL.md -->","frontmatter":{"name":"prompt-engineer-toolkit","description":"Turns marketing prompts into tested, versioned production assets: A/B prompt evaluation against structured test cases, immutable prompt version history with diffs, ready-to-use marketing prompt templates (ad copy, email campaigns, social posts, landing pages, SEO meta), and an LLM-governance playbook for marketing teams (claim discipline, disclosure rules, human-review gates). Use when a marketing team relies on AI-generated content and needs prompt quality to be measurable and safe — or when the user mentions 'prompt engineering,' 'improve my prompts,' 'prompt templates,' 'prompt versioning,' 'AI content workflow,' or 'AI governance for marketing.'","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1251,"sizeBytes":5779},{"name":"measurement-framework.md","path":"marketing-skill/skills/referral-program/references/measurement-framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/referral-program/references/measurement-framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Freferral-program%2Freferences%2Fmeasurement-framework.md -->","isInternal":false,"tokens":1961,"sizeBytes":8014},{"name":"program-mechanics.md","path":"marketing-skill/skills/referral-program/references/program-mechanics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/referral-program/references/program-mechanics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Freferral-program%2Freferences%2Fprogram-mechanics.md -->","isInternal":false,"tokens":2068,"sizeBytes":9308},{"name":"SKILL.md","path":"marketing-skill/skills/referral-program/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/referral-program/SKILL.md","title":"referral-program","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Freferral-program%2FSKILL.md -->","frontmatter":{"name":"referral-program","description":"When the user wants to design, launch, or optimize a referral or affiliate program. Use when they mention 'referral program,' 'affiliate program,' 'word of mouth,' 'refer a friend,' 'incentive program,' 'customer referrals,' 'brand ambassador,' 'partner program,' 'referral link,' or 'growth through referrals.' Covers program mechanics, incentive design, and optimization — not just the idea of referrals but the actual system.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3071,"sizeBytes":13868},{"name":"implementation-patterns.md","path":"marketing-skill/skills/schema-markup/references/implementation-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/schema-markup/references/implementation-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fschema-markup%2Freferences%2Fimplementation-patterns.md -->","isInternal":false,"tokens":2831,"sizeBytes":9695},{"name":"schema-types-guide.md","path":"marketing-skill/skills/schema-markup/references/schema-types-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/schema-markup/references/schema-types-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fschema-markup%2Freferences%2Fschema-types-guide.md -->","isInternal":false,"tokens":2558,"sizeBytes":10692},{"name":"SKILL.md","path":"marketing-skill/skills/schema-markup/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/schema-markup/SKILL.md","title":"schema-markup","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fschema-markup%2FSKILL.md -->","frontmatter":{"name":"schema-markup","description":"When the user wants to implement, audit, or validate structured data (schema markup) on their website. Use when the user mentions 'structured data,' 'schema.org,' 'JSON-LD,' 'rich results,' 'rich snippets,' 'schema markup,' 'FAQ schema,' 'Product schema,' 'HowTo schema,' or 'structured data errors in Search Console.' Also use when someone asks why their content isn't showing rich results or wants to improve AI search visibility. NOT for general SEO audits (use seo-audit) or technical SEO crawl issues (use site-architecture).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2620,"sizeBytes":11661},{"name":"cwv-thresholds.md","path":"marketing-skill/skills/seo-audit/references/cwv-thresholds.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/seo-audit/references/cwv-thresholds.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fseo-audit%2Freferences%2Fcwv-thresholds.md -->","isInternal":false,"tokens":482,"sizeBytes":1751},{"name":"eeat-framework.md","path":"marketing-skill/skills/seo-audit/references/eeat-framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/seo-audit/references/eeat-framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fseo-audit%2Freferences%2Feeat-framework.md -->","isInternal":false,"tokens":621,"sizeBytes":2884},{"name":"schema-types.md","path":"marketing-skill/skills/seo-audit/references/schema-types.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/seo-audit/references/schema-types.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fseo-audit%2Freferences%2Fschema-types.md -->","isInternal":false,"tokens":619,"sizeBytes":2573},{"name":"seo-audit-reference.md","path":"marketing-skill/skills/seo-audit/references/seo-audit-reference.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/seo-audit/references/seo-audit-reference.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fseo-audit%2Freferences%2Fseo-audit-reference.md -->","isInternal":false,"tokens":1396,"sizeBytes":5987},{"name":"SKILL.md","path":"marketing-skill/skills/seo-audit/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/seo-audit/SKILL.md","title":"seo-audit","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fseo-audit%2FSKILL.md -->","frontmatter":{"name":"seo-audit","description":"When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions \"SEO audit,\" \"technical SEO,\" \"why am I not ranking,\" \"SEO issues,\" \"on-page SEO,\" \"meta tags review,\" or \"SEO health check.\" For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":1775,"sizeBytes":7577},{"name":"signup-cro-playbook.md","path":"marketing-skill/skills/signup-flow-cro/references/signup-cro-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/signup-flow-cro/references/signup-cro-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsignup-flow-cro%2Freferences%2Fsignup-cro-playbook.md -->","isInternal":false,"tokens":1092,"sizeBytes":4778},{"name":"SKILL.md","path":"marketing-skill/skills/signup-flow-cro/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/signup-flow-cro/SKILL.md","title":"signup-flow-cro","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsignup-flow-cro%2FSKILL.md -->","frontmatter":{"name":"signup-flow-cro","description":"When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions \"signup conversions,\" \"registration friction,\" \"signup form optimization,\" \"free trial signup,\" \"reduce signup dropoff,\" or \"account creation flow.\" For post-signup onboarding, see onboarding-cro. For lead capture forms (not account creation), see form-cro.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2145,"sizeBytes":9644},{"name":"internal-linking-playbook.md","path":"marketing-skill/skills/site-architecture/references/internal-linking-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/site-architecture/references/internal-linking-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsite-architecture%2Freferences%2Finternal-linking-playbook.md -->","isInternal":false,"tokens":1982,"sizeBytes":8651},{"name":"url-design-guide.md","path":"marketing-skill/skills/site-architecture/references/url-design-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/site-architecture/references/url-design-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsite-architecture%2Freferences%2Furl-design-guide.md -->","isInternal":false,"tokens":2141,"sizeBytes":8505},{"name":"SKILL.md","path":"marketing-skill/skills/site-architecture/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/site-architecture/SKILL.md","title":"site-architecture","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsite-architecture%2FSKILL.md -->","frontmatter":{"name":"site-architecture","description":"When the user wants to audit, redesign, or plan their website's structure, URL hierarchy, navigation design, or internal linking strategy. Use when the user mentions 'site architecture,' 'URL structure,' 'internal links,' 'site navigation,' 'breadcrumbs,' 'topic clusters,' 'hub pages,' 'orphan pages,' 'silo structure,' 'information architecture,' or 'website reorganization.' Also use when someone has SEO problems and the root cause is structural (not content or schema). NOT for content strategy decisions about what to write (use content-strategy) or for schema markup (use schema-markup).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":3156,"sizeBytes":14024},{"name":"platforms.md","path":"marketing-skill/skills/social-content/references/platforms.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-content/references/platforms.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-content%2Freferences%2Fplatforms.md -->","isInternal":false,"tokens":1078,"sizeBytes":4352},{"name":"post-templates.md","path":"marketing-skill/skills/social-content/references/post-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-content/references/post-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-content%2Freferences%2Fpost-templates.md -->","isInternal":false,"tokens":910,"sizeBytes":3342},{"name":"reverse-engineering.md","path":"marketing-skill/skills/social-content/references/reverse-engineering.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-content/references/reverse-engineering.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-content%2Freferences%2Freverse-engineering.md -->","isInternal":false,"tokens":1287,"sizeBytes":5409},{"name":"SKILL.md","path":"marketing-skill/skills/social-content/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-content/SKILL.md","title":"social-content","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-content%2FSKILL.md -->","frontmatter":{"name":"social-content","description":"When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2556,"sizeBytes":11257},{"name":"expected_output.json","path":"marketing-skill/skills/social-media-analyzer/assets/expected_output.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-media-analyzer/assets/expected_output.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-media-analyzer%2Fassets%2Fexpected_output.json -->","frontmatter":{"campaign_metrics":{"platform":"instagram","total_posts":3,"total_engagements":1521,"total_reach":18200,"total_impressions":27700,"total_clicks":430,"avg_engagement_rate":8.36,"ctr":1.55},"roi_metrics":{"total_spend":500,"cost_per_engagement":0.33,"cost_per_click":1.16,"estimated_value":3802.5,"roi_percentage":660.5},"top_posts":[{"post_id":"post_002","content_type":"video","engagement_rate":8.18,"likes":587,"reach":8900},{"post_id":"post_001","content_type":"image","engagement_rate":8.27,"likes":342,"reach":5200},{"post_id":"post_003","content_type":"carousel","engagement_rate":8.85,"likes":298,"reach":4100}],"insights":{"overall_health":"excellent","benchmark_comparison":{"engagement_status":"excellent","engagement_benchmark":"1.22%","engagement_actual":"8.36%","ctr_status":"excellent","ctr_benchmark":"0.22%","ctr_actual":"1.55%"},"recommendations":["Excellent ROI (660.5%)! Consider: (1) Scaling this campaign with increased budget, (2) Replicating successful elements to other campaigns, (3) Testing similar audiences"],"key_strengths":["Strong audience engagement","Excellent return on investment","High click-through rate"]}},"isInternal":false,"tokens":466,"sizeBytes":1519},{"name":"sample_input.json","path":"marketing-skill/skills/social-media-analyzer/assets/sample_input.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-media-analyzer/assets/sample_input.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-media-analyzer%2Fassets%2Fsample_input.json -->","frontmatter":{"platform":"instagram","total_spend":500,"posts":[{"post_id":"post_001","content_type":"image","likes":342,"comments":28,"shares":15,"saves":45,"reach":5200,"impressions":8500,"clicks":120,"posted_at":"2025-10-15T14:30:00Z"},{"post_id":"post_002","content_type":"video","likes":587,"comments":42,"shares":31,"saves":68,"reach":8900,"impressions":12400,"clicks":215,"posted_at":"2025-10-16T18:45:00Z"},{"post_id":"post_003","content_type":"carousel","likes":298,"comments":19,"shares":12,"saves":34,"reach":4100,"impressions":6800,"clicks":95,"posted_at":"2025-10-18T12:15:00Z"}]},"isInternal":false,"tokens":313,"sizeBytes":867},{"name":"HOW_TO_USE.md","path":"marketing-skill/skills/social-media-analyzer/HOW_TO_USE.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-media-analyzer/HOW_TO_USE.md","title":"Social-media-analyzer Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-media-analyzer%2FHOW_TO_USE.md -->","isInternal":false,"tokens":395,"sizeBytes":1863},{"name":"platform-benchmarks.md","path":"marketing-skill/skills/social-media-analyzer/references/platform-benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-media-analyzer/references/platform-benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-media-analyzer%2Freferences%2Fplatform-benchmarks.md -->","isInternal":false,"tokens":2031,"sizeBytes":6020},{"name":"SKILL.md","path":"marketing-skill/skills/social-media-analyzer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-media-analyzer/SKILL.md","title":"social-media-analyzer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-media-analyzer%2FSKILL.md -->","frontmatter":{"name":"social-media-analyzer","description":"Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use when analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards. Also use when the user mentions \"social media audit,\" \"engagement rate,\" or \"which platform performs best.\"","metadata":{"triggers":["analyze social media","calculate engagement rate","social media ROI","campaign performance","compare platforms","benchmark engagement","Instagram analytics","Facebook metrics","TikTok performance","LinkedIn engagement"]}},"isInternal":false,"tokens":2187,"sizeBytes":8641},{"name":"SKILL.md","path":"marketing-skill/skills/social-media-manager/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/social-media-manager/SKILL.md","title":"social-media-manager","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fsocial-media-manager%2FSKILL.md -->","frontmatter":{"name":"social-media-manager","description":"When the user wants to develop social media strategy, plan content calendars, manage community engagement, or grow their social presence across platforms. Also use when the user mentions 'social media strategy,' 'social calendar,' 'community management,' 'social media plan,' 'grow followers,' 'engagement rate,' 'social media audit,' or 'which platforms should I use.' For writing individual social posts, see social-content. For analyzing social performance data, see social-media-analyzer.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-06"}},"isInternal":false,"tokens":2170,"sizeBytes":9631},{"name":"evals.json","path":"marketing-skill/skills/webinar-marketing/evals/evals.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/webinar-marketing/evals/evals.json","title":"Evals Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fwebinar-marketing%2Fevals%2Fevals.json -->","frontmatter":{"skill_name":"webinar-marketing","evals":[{"id":0,"name":"plan-first-webinar-from-scratch","prompt":"We're a Series A B2B SaaS selling an AP automation tool to finance teams. I want to run our first webinar next month to generate leads. I've got an email list of about 8,000 finance and ops people. Can you help me plan the whole thing? I honestly have no idea where to start.","expected_output":"A full webinar plan: clear attendee promise, format recommendation, funnel targets worked backward from a lead goal, a promotion calendar across the runway, a show-up/reminder sequence, live structure with a live-to-close, and a segmented follow-up plan (incl. no-shows).","files":[]},{"id":1,"name":"rescue-low-attendance","prompt":"Our last webinar flopped on attendance. We had 540 registrations but only 95 people showed up live, and barely anyone watched the recording afterward. The content itself was good — it's the turnout that's killing us. What should we do differently next time?","expected_output":"Diagnosis that correctly identifies registration->attendance (show-up) as the broken stage, then specific fixes: a full reminder sequence with timing, one-click calendar add, a live-only incentive, and shortening the registration-to-event gap. Should NOT just rewrite the landing page or content.","files":[]},{"id":2,"name":"write-segmented-followup","prompt":"I need follow-up emails for a webinar we ran yesterday on 'Cutting cloud costs in 2026.' 220 people registered and 80 attended live. Can you write the follow-up emails? I want to push everyone toward booking a demo.","expected_output":"A segmented follow-up sequence: attendees who engaged, attendees who didn't act, and no-shows (the ~140 who registered but didn't attend) each get tailored copy. Recording sent within 24h, one clear demo CTA per email, with the no-show segment treated as warm.","files":[]}]},"isInternal":false,"tokens":482,"sizeBytes":2048},{"name":"benchmarks.md","path":"marketing-skill/skills/webinar-marketing/references/benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/webinar-marketing/references/benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fwebinar-marketing%2Freferences%2Fbenchmarks.md -->","isInternal":false,"tokens":796,"sizeBytes":3332},{"name":"promotion-playbook.md","path":"marketing-skill/skills/webinar-marketing/references/promotion-playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/webinar-marketing/references/promotion-playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fwebinar-marketing%2Freferences%2Fpromotion-playbook.md -->","isInternal":false,"tokens":1233,"sizeBytes":5158},{"name":"webinar-formats.md","path":"marketing-skill/skills/webinar-marketing/references/webinar-formats.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/webinar-marketing/references/webinar-formats.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fwebinar-marketing%2Freferences%2Fwebinar-formats.md -->","isInternal":false,"tokens":844,"sizeBytes":3618},{"name":"SKILL.md","path":"marketing-skill/skills/webinar-marketing/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/webinar-marketing/SKILL.md","title":"webinar-marketing","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fwebinar-marketing%2FSKILL.md -->","frontmatter":{"name":"webinar-marketing","description":"When the user wants to plan, promote, run, or improve a webinar or virtual event to generate and convert demand. Use when the user mentions 'webinar,' 'virtual event,' 'online event,' 'live demo,' 'virtual summit,' 'workshop,' 'masterclass,' 'fireside chat,' 'roundtable,' 'registration funnel,' 'show-up rate,' 'attendance rate,' 'webinar promotion,' 'webinar follow-up,' or 'on-demand webinar.' Also use when they have a webinar that isn't converting — low registrations, low show-up, or attendees who don't buy — and want to diagnose and fix it. Covers the full funnel: registration, promotion, show-up, live engagement, live-to-close, and post-event nurture. Distinct from launch-strategy (full product launches) and email-sequence (lifecycle nurture) — this is the end-to-end webinar/event motion. NOT for in-person field events logistics, and NOT for generic lifecycle email (use email-sequence).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-06-01"}},"isInternal":false,"tokens":3009,"sizeBytes":13098},{"name":"webinar-plan-template.md","path":"marketing-skill/skills/webinar-marketing/templates/webinar-plan-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/webinar-marketing/templates/webinar-plan-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fwebinar-marketing%2Ftemplates%2Fwebinar-plan-template.md -->","isInternal":false,"tokens":809,"sizeBytes":2716},{"name":"algorithm-signals.md","path":"marketing-skill/skills/x-twitter-growth/references/algorithm-signals.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/x-twitter-growth/references/algorithm-signals.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fx-twitter-growth%2Freferences%2Falgorithm-signals.md -->","isInternal":false,"tokens":685,"sizeBytes":2824},{"name":"SKILL.md","path":"marketing-skill/skills/x-twitter-growth/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/x-twitter-growth/SKILL.md","title":"x-twitter-growth","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fx-twitter-growth%2FSKILL.md -->","frontmatter":{"name":"x-twitter-growth","description":"X/Twitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X/Twitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-03-10"}},"isInternal":false,"tokens":2162,"sizeBytes":8674},{"name":"authoring-notes.json","path":"marketing-skill/skills/youtube-full/.claude-plugin/authoring-notes.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/youtube-full/.claude-plugin/authoring-notes.json","title":".claude-plugin Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fyoutube-full%2F.claude-plugin%2Fauthoring-notes.json -->","frontmatter":{"source":"https://github.com/ZeroPointRepo/youtube-skills","attribution":"Ported from ZeroPointRepo/youtube-skills (MIT). Original skill authored by ZeroPointRepo contributors."},"isInternal":false,"tokens":48,"sizeBytes":189},{"name":"SKILL.md","path":"marketing-skill/skills/youtube-full/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/youtube-full/SKILL.md","title":"youtube-full","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fyoutube-full%2FSKILL.md -->","frontmatter":{"name":"youtube-full","description":"Use when the user needs YouTube transcripts, video search, channel browsing, playlist extraction, or content monitoring. Trigger phrases: 'get the transcript for', 'search YouTube for', 'what are the latest videos on', 'list this playlist', 'monitor this channel', or any request involving a YouTube URL, video ID, or @handle. Do NOT use for downloading video or audio files, YouTube engagement data (likes, comments), or private/age-restricted videos.","license":"MIT"},"isInternal":false,"tokens":1667,"sizeBytes":7055},{"name":"SKILL.md","path":"marketing-skill/video-content-strategist/skills/video-content-strategist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/video-content-strategist/skills/video-content-strategist/SKILL.md","title":"video-content-strategist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fvideo-content-strategist%2Fskills%2Fvideo-content-strategist%2FSKILL.md -->","frontmatter":{"name":"video-content-strategist","description":"Use when planning video content strategy, writing video scripts, optimizing YouTube channels, building short-form video pipelines (Reels, TikTok, Shorts), or repurposing long-form content into video. Triggers: 'start a YouTube channel', 'video content strategy', 'write a video script', 'repurpose into video', 'YouTube SEO', 'short-form video'. NOT for written blog content (use content-production). NOT for social captions without video (use social-media-manager)."},"isInternal":false,"tokens":2621,"sizeBytes":11430},{"name":"brand_system_design.md","path":"marketing/landing/skills/landing/references/brand_system_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/landing/skills/landing/references/brand_system_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flanding%2Fskills%2Flanding%2Freferences%2Fbrand_system_design.md -->","isInternal":false,"tokens":2307,"sizeBytes":8401},{"name":"gsap_animation_patterns.md","path":"marketing/landing/skills/landing/references/gsap_animation_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/landing/skills/landing/references/gsap_animation_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flanding%2Fskills%2Flanding%2Freferences%2Fgsap_animation_patterns.md -->","isInternal":false,"tokens":2670,"sizeBytes":9654},{"name":"single_file_html_discipline.md","path":"marketing/landing/skills/landing/references/single_file_html_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/landing/skills/landing/references/single_file_html_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flanding%2Fskills%2Flanding%2Freferences%2Fsingle_file_html_discipline.md -->","isInternal":false,"tokens":2109,"sizeBytes":8528},{"name":"SKILL.md","path":"marketing/landing/skills/landing/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/landing/skills/landing/SKILL.md","title":"landing","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flanding%2Fskills%2Flanding%2FSKILL.md -->","frontmatter":{"name":"landing","description":"Generates a premium single-page HTML landing page with 3D CSS animations, GSAP scroll effects, and mouse-parallax depth. Forcing intake (product + elevator pitch, audience register, brand overrides, tone) locks down positioning before any copy or markup is written, so the page reflects the actual product rather than generic boilerplate. Use whenever the user says 'landing for X', 'create a landing page', 'build a landing page', 'make a landing page for X', 'I need a web page for Y', or provides product/service details and wants a polished website. Also triggers on 'promotional page', 'product page', 'one-pager', 'web presence', 'sales page'. Outputs a single self-contained HTML file (Claude Code) or HTML artifact (Claude.ai). Supports configurable brand colors via CSS custom property overrides.","license":"MIT","metadata":{"source_spec":"megaprompts/04-landing-megaprompt.md","build_pattern":"Path B (direct conversion)","distinct_from":"product-team/skills/landing-page-generator (different output format + optimization target)","version":"1.0.0"}},"isInternal":false,"tokens":4069,"sizeBytes":15120},{"name":"measurement_log_template.md","path":"marketing/linkedin/skills/linkedin-analytics/assets/measurement_log_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-analytics/assets/measurement_log_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-analytics%2Fassets%2Fmeasurement_log_template.md -->","isInternal":false,"tokens":583,"sizeBytes":2440},{"name":"evidence_thresholds.md","path":"marketing/linkedin/skills/linkedin-analytics/references/evidence_thresholds.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-analytics/references/evidence_thresholds.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-analytics%2Freferences%2Fevidence_thresholds.md -->","isInternal":false,"tokens":1513,"sizeBytes":6592},{"name":"linkedin_metrics_canon.md","path":"marketing/linkedin/skills/linkedin-analytics/references/linkedin_metrics_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-analytics/references/linkedin_metrics_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-analytics%2Freferences%2Flinkedin_metrics_canon.md -->","isInternal":false,"tokens":1332,"sizeBytes":5913},{"name":"SKILL.md","path":"marketing/linkedin/skills/linkedin-analytics/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-analytics/SKILL.md","title":"linkedin-analytics","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-analytics%2FSKILL.md -->","frontmatter":{"name":"linkedin-analytics","description":"Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Triggers on \"why did my reach drop\", \"what's working on my LinkedIn\", \"analyze my posts\", \"do carousels do better for me\", \"should I test this\", \"LinkedIn analytics\". Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below 10 posts.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-08-25"}},"isInternal":false,"tokens":1282,"sizeBytes":5365},{"name":"example_post.md","path":"marketing/linkedin/skills/linkedin-content/assets/example_post.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/assets/example_post.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2Fassets%2Fexample_post.md -->","isInternal":false,"tokens":547,"sizeBytes":2321},{"name":"post_templates.md","path":"marketing/linkedin/skills/linkedin-content/assets/post_templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/assets/post_templates.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2Fassets%2Fpost_templates.md -->","isInternal":false,"tokens":928,"sizeBytes":3873},{"name":"accessibility_and_inclusion.md","path":"marketing/linkedin/skills/linkedin-content/references/accessibility_and_inclusion.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/references/accessibility_and_inclusion.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2Freferences%2Faccessibility_and_inclusion.md -->","isInternal":false,"tokens":1398,"sizeBytes":5914},{"name":"hook_and_fold_mechanics.md","path":"marketing/linkedin/skills/linkedin-content/references/hook_and_fold_mechanics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/references/hook_and_fold_mechanics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2Freferences%2Fhook_and_fold_mechanics.md -->","isInternal":false,"tokens":1477,"sizeBytes":6191},{"name":"post_formats_canon.md","path":"marketing/linkedin/skills/linkedin-content/references/post_formats_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/references/post_formats_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2Freferences%2Fpost_formats_canon.md -->","isInternal":false,"tokens":1408,"sizeBytes":6122},{"name":"repurposing_discipline.md","path":"marketing/linkedin/skills/linkedin-content/references/repurposing_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/references/repurposing_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2Freferences%2Frepurposing_discipline.md -->","isInternal":false,"tokens":1387,"sizeBytes":5963},{"name":"SKILL.md","path":"marketing/linkedin/skills/linkedin-content/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-content/SKILL.md","title":"linkedin-content","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-content%2FSKILL.md -->","frontmatter":{"name":"linkedin-content","description":"Use when someone wants to write, edit, or lint a LinkedIn post — a story, how-to, opinion piece, carousel script, video script, or poll — or wants an article, talk, or transcript repurposed into posts. Triggers on \"write a LinkedIn post\", \"is this hook any good\", \"review my post\", \"turn this into LinkedIn posts\", \"carousel\", \"what format should this be\". Lints posts 0-100 on mechanics, hook, integrity, and accessibility; picks the format the material actually supports; and splits long sources into standalone units with a reuse ledger.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-08-25"}},"isInternal":false,"tokens":1313,"sizeBytes":5515},{"name":"example_outreach.json","path":"marketing/linkedin/skills/linkedin-engagement/assets/example_outreach.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-engagement/assets/example_outreach.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-engagement%2Fassets%2Fexample_outreach.json -->","frontmatter":{"_comment":"Input shape for outreach_message_builder.py. This example passes at exit 0: the specific line names an artifact and the part that mattered, the reason is a clause, and there is no ask - because this is a first-touch connection note and the note's job is the conversation, not the meeting.","type":"connection","recipient":"Priya","specific_line":"Your teardown of the dbt exposures rollout matched what broke for us at step three.","reason":"I am working the same problem from the platform side and would like to follow what you publish.","ask":"","premium":false},"isInternal":false,"tokens":141,"sizeBytes":607},{"name":"outreach_worksheet.md","path":"marketing/linkedin/skills/linkedin-engagement/assets/outreach_worksheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-engagement/assets/outreach_worksheet.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-engagement%2Fassets%2Foutreach_worksheet.md -->","isInternal":false,"tokens":573,"sizeBytes":2480},{"name":"comment_strategy.md","path":"marketing/linkedin/skills/linkedin-engagement/references/comment_strategy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-engagement/references/comment_strategy.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-engagement%2Freferences%2Fcomment_strategy.md -->","isInternal":false,"tokens":1554,"sizeBytes":6756},{"name":"outreach_ethics_and_benchmarks.md","path":"marketing/linkedin/skills/linkedin-engagement/references/outreach_ethics_and_benchmarks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-engagement/references/outreach_ethics_and_benchmarks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-engagement%2Freferences%2Foutreach_ethics_and_benchmarks.md -->","isInternal":false,"tokens":1588,"sizeBytes":6617},{"name":"SKILL.md","path":"marketing/linkedin/skills/linkedin-engagement/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-engagement/SKILL.md","title":"linkedin-engagement","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-engagement%2FSKILL.md -->","frontmatter":{"name":"linkedin-engagement","description":"Use when someone wants to grow reach through comments, replies, groups, or outreach on LinkedIn — a commenting roster, a connection request note, a DM or InMail, a networking plan, or a check on whether their outreach volume is safe. Triggers on \"who should I engage with\", \"write a connection request\", \"cold DM\", \"LinkedIn outreach\", \"networking strategy\", \"how many invites can I send\". Builds a weekly comment roster inside a real time budget, assembles one message at a time and refuses templates, and caps volume against LinkedIn's limits. Nothing is ever sent.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-08-25"}},"isInternal":false,"tokens":1287,"sizeBytes":5423},{"name":"example_profile.json","path":"marketing/linkedin/skills/linkedin-profile/assets/example_profile.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-profile/assets/example_profile.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-profile%2Fassets%2Fexample_profile.json -->","frontmatter":{"_comment":"Input shape for profile_completeness_auditor.py. Every key is optional; a missing key is treated as absent. Nothing here is fetched from LinkedIn - you fill it in from your own profile.","photo":true,"banner_custom":true,"custom_url":true,"headline":"Fractional Head of Data for Series A SaaS | Cut BigQuery spend 62% at Zendesk scale | ex-Stripe | I make dashboards people trust","about":"Most data teams do not have a data problem. They have a trust problem - nobody believes the dashboard, so everyone rebuilds the number in a spreadsheet. I work with Series A SaaS companies whose analytics stack grew faster than anyone's confidence in it. Cut BigQuery spend 62% at Zendesk scale without dropping a single dashboard. Rebuilt reporting for three Series B teams; two retired their shadow spreadsheets inside a quarter. If your team is re-deriving the same metric in three places, message me.","current_role":{"title":"Fractional Head of Data","bullets":["Cut BigQuery spend 62% while keeping every dashboard live","Reduced median time-to-trusted-number from 9 days to under 1","Led the migration of 140 legacy models down to 38"]},"featured_items":2,"featured_updated_days_ago":45,"skills":["analytics engineering","dbt","BigQuery","data governance","SQL","Python"],"recommendations_received":3,"open_to_or_services":true,"education":true,"certifications":1,"contact_info":true,"days_since_last_post":6},"isInternal":false,"tokens":387,"sizeBytes":1531},{"name":"profile_worksheet.md","path":"marketing/linkedin/skills/linkedin-profile/assets/profile_worksheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-profile/assets/profile_worksheet.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-profile%2Fassets%2Fprofile_worksheet.md -->","isInternal":false,"tokens":472,"sizeBytes":1897},{"name":"headline_and_positioning.md","path":"marketing/linkedin/skills/linkedin-profile/references/headline_and_positioning.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-profile/references/headline_and_positioning.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-profile%2Freferences%2Fheadline_and_positioning.md -->","isInternal":false,"tokens":1326,"sizeBytes":5752},{"name":"profile_architecture.md","path":"marketing/linkedin/skills/linkedin-profile/references/profile_architecture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-profile/references/profile_architecture.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-profile%2Freferences%2Fprofile_architecture.md -->","isInternal":false,"tokens":1342,"sizeBytes":5897},{"name":"SKILL.md","path":"marketing/linkedin/skills/linkedin-profile/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-profile/SKILL.md","title":"linkedin-profile","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-profile%2FSKILL.md -->","frontmatter":{"name":"linkedin-profile","description":"Use when someone wants their LinkedIn profile audited or rewritten — headline, About section, experience bullets, Featured, banner, recommendations — or says \"fix my headline\", \"my profile gets views but nothing happens\", \"optimize my LinkedIn profile\", \"what should my About section say\". Scores the headline on five dimensions, audits the whole profile 0-100 and ranks fixes by points per hour, and assembles an About section that survives the \"…see more\" fold.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-08-25"}},"isInternal":false,"tokens":1186,"sizeBytes":5013},{"name":"linkedin_operating_agreement.md","path":"marketing/linkedin/skills/linkedin-skills/assets/linkedin_operating_agreement.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-skills/assets/linkedin_operating_agreement.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-skills%2Fassets%2Flinkedin_operating_agreement.md -->","isInternal":false,"tokens":770,"sizeBytes":3371},{"name":"linkedin_platform_canon.md","path":"marketing/linkedin/skills/linkedin-skills/references/linkedin_platform_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-skills/references/linkedin_platform_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-skills%2Freferences%2Flinkedin_platform_canon.md -->","isInternal":false,"tokens":1776,"sizeBytes":7999},{"name":"policy_and_account_safety.md","path":"marketing/linkedin/skills/linkedin-skills/references/policy_and_account_safety.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-skills/references/policy_and_account_safety.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-skills%2Freferences%2Fpolicy_and_account_safety.md -->","isInternal":false,"tokens":1696,"sizeBytes":7916},{"name":"SKILL.md","path":"marketing/linkedin/skills/linkedin-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-skills/SKILL.md","title":"linkedin-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-skills%2FSKILL.md -->","frontmatter":{"name":"linkedin-skills","description":"Use when someone wants to grow an organic LinkedIn presence — a content strategy for a career change or consulting or thought leadership, a rewritten profile or headline, post drafts and hooks, a posting cadence or newsletter plan, connection notes and outreach, a commenting strategy, repurposing an article or talk into posts, or a read on why their reach dropped. Triggers on \"grow my LinkedIn\", \"fix my headline\", \"write a LinkedIn post\", \"what should I post about\", \"LinkedIn strategy\", \"connection request\", \"my reach dropped\". Forks context to route to one of five sub-skills, and refuses automation, scraping, pods, and bulk DMs before any drafting starts.","context":"fork","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-08-25","build_pattern":"Domain orchestrator — deterministic lane router + policy gate, five managed sub-skills","distinct_from":"marketing-skill/x-twitter-growth (X/Twitter-specific); marketing-skill/social-content (multi-platform calendars); marketing-skill/social-media-analyzer (cross-platform reporting); productivity/andreessen (venture judgement, not audience building)"}},"isInternal":false,"tokens":1367,"sizeBytes":5702},{"name":"example_brief.json","path":"marketing/linkedin/skills/linkedin-strategy/assets/example_brief.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-strategy/assets/example_brief.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Fassets%2Fexample_brief.json -->","frontmatter":{"_comment":"A brief that passes positioning_brief.py at exit 0. Note the audience is specific enough to exclude someone, three of four pillars carry proof that already exists, one pillar sits at 10% as the experimental slot, and there are three reasoned exclusions.","objective":"consulting","audience":"heads of data at Series A-B SaaS companies who have three analysts and no analytics engineer, and whose CEO does not trust the dashboard","pillars":[{"name":"Trust debt in analytics","why_you":"I have rebuilt this at three companies and measured it each time","proof":"the 6-vs-35-days handoff measurement, published","share":40},{"name":"dbt and modelling decisions","why_you":"I maintain two open-source dbt packages","proof":"public repos plus a conference talk","share":35},{"name":"Hiring the first analytics engineer","why_you":"I have written three of these job specs and run the loops","proof":"two hires who are still in role two years later","share":15},{"name":"Field notes and experiments","why_you":"unproven; testing whether the audience wants this","proof":"","share":10}],"exclusions":["generic AI commentary - I have no edge there and neither does anyone posting it","hot takes on other companies' layoffs","vendor comparison posts that would compromise client confidentiality"]},"isInternal":false,"tokens":365,"sizeBytes":1512},{"name":"positioning_brief_template.md","path":"marketing/linkedin/skills/linkedin-strategy/assets/positioning_brief_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-strategy/assets/positioning_brief_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Fassets%2Fpositioning_brief_template.md -->","isInternal":false,"tokens":620,"sizeBytes":2734},{"name":"cadence_and_consistency.md","path":"marketing/linkedin/skills/linkedin-strategy/references/cadence_and_consistency.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-strategy/references/cadence_and_consistency.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Freferences%2Fcadence_and_consistency.md -->","isInternal":false,"tokens":1293,"sizeBytes":5589},{"name":"newsletter_playbook.md","path":"marketing/linkedin/skills/linkedin-strategy/references/newsletter_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-strategy/references/newsletter_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Freferences%2Fnewsletter_playbook.md -->","isInternal":false,"tokens":1337,"sizeBytes":5955},{"name":"objective_to_pillars.md","path":"marketing/linkedin/skills/linkedin-strategy/references/objective_to_pillars.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-strategy/references/objective_to_pillars.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2Freferences%2Fobjective_to_pillars.md -->","isInternal":false,"tokens":1403,"sizeBytes":6242},{"name":"SKILL.md","path":"marketing/linkedin/skills/linkedin-strategy/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/skills/linkedin-strategy/SKILL.md","title":"linkedin-strategy","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2Fskills%2Flinkedin-strategy%2FSKILL.md -->","frontmatter":{"name":"linkedin-strategy","description":"Use when someone needs a LinkedIn plan rather than a post — content pillars, positioning for a career change or consulting or thought leadership, a sustainable posting cadence, or a newsletter decision. Triggers on \"what should I post about\", \"how often should I post\", \"LinkedIn content strategy\", \"should I start a LinkedIn newsletter\", \"grow my following\", \"90-day plan\". Validates the positioning brief, sizes the week against real hours and refuses a plan that will not survive week five, and gates a newsletter against eligibility and a six-month cadence commitment.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","updated":"2026-08-25"}},"isInternal":false,"tokens":1208,"sizeBytes":5148},{"name":"sprint_planning_template.md","path":"product-team/agile-product-owner/skills/agile-product-owner/assets/sprint_planning_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/agile-product-owner/skills/agile-product-owner/assets/sprint_planning_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2Fskills%2Fagile-product-owner%2Fassets%2Fsprint_planning_template.md -->","isInternal":false,"tokens":668,"sizeBytes":2328},{"name":"user_story_template.md","path":"product-team/agile-product-owner/skills/agile-product-owner/assets/user_story_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/agile-product-owner/skills/agile-product-owner/assets/user_story_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2Fskills%2Fagile-product-owner%2Fassets%2Fuser_story_template.md -->","isInternal":false,"tokens":340,"sizeBytes":1278},{"name":"sprint-planning-guide.md","path":"product-team/agile-product-owner/skills/agile-product-owner/references/sprint-planning-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/agile-product-owner/skills/agile-product-owner/references/sprint-planning-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2Fskills%2Fagile-product-owner%2Freferences%2Fsprint-planning-guide.md -->","isInternal":false,"tokens":2300,"sizeBytes":8757},{"name":"user-story-templates.md","path":"product-team/agile-product-owner/skills/agile-product-owner/references/user-story-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/agile-product-owner/skills/agile-product-owner/references/user-story-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2Fskills%2Fagile-product-owner%2Freferences%2Fuser-story-templates.md -->","isInternal":false,"tokens":1967,"sizeBytes":8432},{"name":"SKILL.md","path":"product-team/agile-product-owner/skills/agile-product-owner/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/agile-product-owner/skills/agile-product-owner/SKILL.md","title":"agile-product-owner","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2Fskills%2Fagile-product-owner%2FSKILL.md -->","frontmatter":{"name":"agile-product-owner","description":"Agile product ownership for backlog management and sprint execution. Covers user story writing, acceptance criteria, sprint planning, and velocity tracking. Use when writing user stories, creating acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing the backlog.","metadata":{"not_for":"Kanban-only workflows, waterfall project planning, general task management, non-Scrum agile frameworks (SAFe, LeSS) without adaptation","triggers":["write user story","create acceptance criteria","plan sprint","estimate story points","break down epic","prioritize backlog","sprint planning","backlog grooming","sprint retrospective","definition of done","INVEST criteria","Given When Then","user story template","sprint capacity","velocity tracking"]}},"isInternal":false,"tokens":2988,"sizeBytes":12737},{"name":"accessibility.md","path":"product-team/apple-hig-expert/skills/apple-hig-expert/references/accessibility.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/apple-hig-expert/skills/apple-hig-expert/references/accessibility.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fapple-hig-expert%2Fskills%2Fapple-hig-expert%2Freferences%2Faccessibility.md -->","isInternal":false,"tokens":617,"sizeBytes":2743},{"name":"platform-specifics.md","path":"product-team/apple-hig-expert/skills/apple-hig-expert/references/platform-specifics.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/apple-hig-expert/skills/apple-hig-expert/references/platform-specifics.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fapple-hig-expert%2Fskills%2Fapple-hig-expert%2Freferences%2Fplatform-specifics.md -->","isInternal":false,"tokens":636,"sizeBytes":2784},{"name":"visual-design.md","path":"product-team/apple-hig-expert/skills/apple-hig-expert/references/visual-design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/apple-hig-expert/skills/apple-hig-expert/references/visual-design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fapple-hig-expert%2Fskills%2Fapple-hig-expert%2Freferences%2Fvisual-design.md -->","isInternal":false,"tokens":836,"sizeBytes":3506},{"name":"SKILL.md","path":"product-team/apple-hig-expert/skills/apple-hig-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/apple-hig-expert/skills/apple-hig-expert/SKILL.md","title":"apple-hig-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fapple-hig-expert%2Fskills%2Fapple-hig-expert%2FSKILL.md -->","frontmatter":{"name":"apple-hig-expert","description":"Audits and designs iOS/macOS/watchOS/visionOS interfaces against the Apple Human Interface Guidelines, including the Liquid Glass design language (announced WWDC25, shipped with iOS 26/macOS Tahoe, Sept 2025). Use when reviewing an Apple-platform mockup or app for HIG compliance, checking contrast or tap-target sizes, or designing native-feeling Apple UI (e.g., 'audit my iOS app against the HIG', 'is this text readable on Liquid Glass?').","license":"MIT","metadata":{"version":"1.1.0","author":"Alireza Rezvani","category":"design","updated":"2026-06-11"}},"isInternal":false,"tokens":1400,"sizeBytes":5412},{"name":"hig-audit-template.md","path":"product-team/apple-hig-expert/skills/apple-hig-expert/templates/hig-audit-template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/apple-hig-expert/skills/apple-hig-expert/templates/hig-audit-template.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fapple-hig-expert%2Fskills%2Fapple-hig-expert%2Ftemplates%2Fhig-audit-template.md -->","isInternal":false,"tokens":554,"sizeBytes":2056},{"name":"sample-analysis.json","path":"product-team/code-to-prd/skills/code-to-prd/assets/sample-analysis.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/code-to-prd/skills/code-to-prd/assets/sample-analysis.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fcode-to-prd%2Fskills%2Fcode-to-prd%2Fassets%2Fsample-analysis.json 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-->","isInternal":false,"tokens":2423,"sizeBytes":10223},{"name":"strategy_types.md","path":"product-team/skills/product-strategist/references/strategy_types.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/product-strategist/references/strategy_types.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fproduct-strategist%2Freferences%2Fstrategy_types.md -->","isInternal":false,"tokens":2677,"sizeBytes":11914},{"name":"SKILL.md","path":"product-team/skills/product-strategist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/product-strategist/SKILL.md","title":"product-strategist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fproduct-strategist%2FSKILL.md -->","frontmatter":{"name":"product-strategist","description":"Strategic product leadership toolkit for Head of Product covering OKR cascade generation, quarterly planning, competitive landscape analysis, product vision documents, and team scaling proposals. Use when creating quarterly OKR documents, defining product goals or KPIs, building product roadmaps, running competitive analysis, drafting team structure or hiring plans, aligning product strategy across engineering and design, or generating cascaded goal hierarchies from company to team level."},"isInternal":false,"tokens":1828,"sizeBytes":7325},{"name":"communication-templates.md","path":"product-team/skills/roadmap-communicator/references/communication-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/roadmap-communicator/references/communication-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Froadmap-communicator%2Freferences%2Fcommunication-templates.md -->","isInternal":false,"tokens":232,"sizeBytes":961},{"name":"roadmap-templates.md","path":"product-team/skills/roadmap-communicator/references/roadmap-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/roadmap-communicator/references/roadmap-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Froadmap-communicator%2Freferences%2Froadmap-templates.md -->","isInternal":false,"tokens":308,"sizeBytes":1064},{"name":"SKILL.md","path":"product-team/skills/roadmap-communicator/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/roadmap-communicator/SKILL.md","title":"roadmap-communicator","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via 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-->","isInternal":false,"tokens":2063,"sizeBytes":9028},{"name":"SKILL.md","path":"product-team/skills/saas-scaffolder/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/saas-scaffolder/SKILL.md","title":"saas-scaffolder","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fsaas-scaffolder%2FSKILL.md -->","frontmatter":{"name":"saas-scaffolder","description":"Generates complete, production-ready SaaS project boilerplate including authentication, database schemas, billing integration, API routes, and a working dashboard using Next.js 14+ App Router, TypeScript, Tailwind CSS, shadcn/ui, Drizzle ORM, and Stripe. Use when the user wants to create a new SaaS app, start a subscription-based web project, scaffold a Next.js application, or mentions terms like starter template, boilerplate, new project, or wiring up auth and payments."},"isInternal":false,"tokens":2660,"sizeBytes":10805},{"name":"spec-parsing-guide.md","path":"product-team/skills/spec-to-repo/references/spec-parsing-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/spec-to-repo/references/spec-parsing-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fspec-to-repo%2Freferences%2Fspec-parsing-guide.md -->","isInternal":false,"tokens":956,"sizeBytes":4043},{"name":"stack-templates.md","path":"product-team/skills/spec-to-repo/references/stack-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/spec-to-repo/references/stack-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fspec-to-repo%2Freferences%2Fstack-templates.md -->","isInternal":false,"tokens":1597,"sizeBytes":6062},{"name":"SKILL.md","path":"product-team/skills/spec-to-repo/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/spec-to-repo/SKILL.md","title":"spec-to-repo","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fspec-to-repo%2FSKILL.md -->","frontmatter":{"name":"spec-to-repo","description":"Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and need a codebase', or provides a natural-language project specification and expects a complete, runnable repository. Stack-agnostic: Next.js, FastAPI, Rails, Go, Rust, Flutter, and more."},"isInternal":false,"tokens":2700,"sizeBytes":11296},{"name":"design_system_doc_template.md","path":"product-team/skills/ui-design-system/assets/design_system_doc_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ui-design-system/assets/design_system_doc_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fui-design-system%2Fassets%2Fdesign_system_doc_template.md -->","isInternal":false,"tokens":1760,"sizeBytes":6906},{"name":"component-architecture.md","path":"product-team/skills/ui-design-system/references/component-architecture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ui-design-system/references/component-architecture.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fui-design-system%2Freferences%2Fcomponent-architecture.md -->","isInternal":false,"tokens":2271,"sizeBytes":10129},{"name":"developer-handoff.md","path":"product-team/skills/ui-design-system/references/developer-handoff.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ui-design-system/references/developer-handoff.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fui-design-system%2Freferences%2Fdeveloper-handoff.md -->","isInternal":false,"tokens":2737,"sizeBytes":10244},{"name":"responsive-calculations.md","path":"product-team/skills/ui-design-system/references/responsive-calculations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ui-design-system/references/responsive-calculations.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fui-design-system%2Freferences%2Fresponsive-calculations.md -->","isInternal":false,"tokens":2599,"sizeBytes":8766},{"name":"token-generation.md","path":"product-team/skills/ui-design-system/references/token-generation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ui-design-system/references/token-generation.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fui-design-system%2Freferences%2Ftoken-generation.md -->","isInternal":false,"tokens":2515,"sizeBytes":8530},{"name":"SKILL.md","path":"product-team/skills/ui-design-system/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ui-design-system/SKILL.md","title":"ui-design-system","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fui-design-system%2FSKILL.md -->","frontmatter":{"name":"ui-design-system","description":"UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use when creating design systems, generating design tokens, maintaining visual consistency, or facilitating design-dev collaboration and developer handoff."},"isInternal":false,"tokens":2880,"sizeBytes":10789},{"name":"research_plan_template.md","path":"product-team/skills/ux-researcher-designer/assets/research_plan_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ux-researcher-designer/assets/research_plan_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fux-researcher-designer%2Fassets%2Fresearch_plan_template.md -->","isInternal":false,"tokens":1143,"sizeBytes":4802},{"name":"example-personas.md","path":"product-team/skills/ux-researcher-designer/references/example-personas.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ux-researcher-designer/references/example-personas.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fux-researcher-designer%2Freferences%2Fexample-personas.md -->","isInternal":false,"tokens":2908,"sizeBytes":11990},{"name":"journey-mapping-guide.md","path":"product-team/skills/ux-researcher-designer/references/journey-mapping-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ux-researcher-designer/references/journey-mapping-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fux-researcher-designer%2Freferences%2Fjourney-mapping-guide.md -->","isInternal":false,"tokens":3399,"sizeBytes":18102},{"name":"persona-methodology.md","path":"product-team/skills/ux-researcher-designer/references/persona-methodology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ux-researcher-designer/references/persona-methodology.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fux-researcher-designer%2Freferences%2Fpersona-methodology.md -->","isInternal":false,"tokens":2622,"sizeBytes":11644},{"name":"usability-testing-frameworks.md","path":"product-team/skills/ux-researcher-designer/references/usability-testing-frameworks.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ux-researcher-designer/references/usability-testing-frameworks.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fux-researcher-designer%2Freferences%2Fusability-testing-frameworks.md -->","isInternal":false,"tokens":2831,"sizeBytes":11932},{"name":"SKILL.md","path":"product-team/skills/ux-researcher-designer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/skills/ux-researcher-designer/SKILL.md","title":"ux-researcher-designer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fskills%2Fux-researcher-designer%2FSKILL.md -->","frontmatter":{"name":"ux-researcher-designer","description":"UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when conducting user research, creating personas, mapping user journeys, planning usability tests, or validating designs."},"isInternal":false,"tokens":2864,"sizeBytes":12007},{"name":"blank_3x5_card.md","path":"productivity/andreessen/skills/andreessen/assets/blank_3x5_card.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/assets/blank_3x5_card.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Fassets%2Fblank_3x5_card.md -->","isInternal":false,"tokens":263,"sizeBytes":929},{"name":"example_3x5_card.md","path":"productivity/andreessen/skills/andreessen/assets/example_3x5_card.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/assets/example_3x5_card.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Fassets%2Fexample_3x5_card.md -->","isInternal":false,"tokens":473,"sizeBytes":1713},{"name":"example_market_verdict.md","path":"productivity/andreessen/skills/andreessen/assets/example_market_verdict.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/assets/example_market_verdict.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Fassets%2Fexample_market_verdict.md -->","isInternal":false,"tokens":712,"sizeBytes":2906},{"name":"example_pmf_check.md","path":"productivity/andreessen/skills/andreessen/assets/example_pmf_check.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/assets/example_pmf_check.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Fassets%2Fexample_pmf_check.md -->","isInternal":false,"tokens":522,"sizeBytes":1944},{"name":"forcing_question_worksheet.md","path":"productivity/andreessen/skills/andreessen/assets/forcing_question_worksheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/assets/forcing_question_worksheet.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Fassets%2Fforcing_question_worksheet.md -->","isInternal":false,"tokens":546,"sizeBytes":2541},{"name":"README.md","path":"productivity/andreessen/skills/andreessen/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/README.md","title":"Andreessen Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2FREADME.md -->","isInternal":false,"tokens":736,"sizeBytes":2634},{"name":"market_first_canon.md","path":"productivity/andreessen/skills/andreessen/references/market_first_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/references/market_first_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Freferences%2Fmarket_first_canon.md -->","isInternal":false,"tokens":1187,"sizeBytes":5112},{"name":"operating_prompt.md","path":"productivity/andreessen/skills/andreessen/references/operating_prompt.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/references/operating_prompt.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Freferences%2Foperating_prompt.md -->","isInternal":false,"tokens":1203,"sizeBytes":5294},{"name":"personal_productivity_system.md","path":"productivity/andreessen/skills/andreessen/references/personal_productivity_system.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/references/personal_productivity_system.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Freferences%2Fpersonal_productivity_system.md -->","isInternal":false,"tokens":1313,"sizeBytes":5409},{"name":"pmf_and_build_canon.md","path":"productivity/andreessen/skills/andreessen/references/pmf_and_build_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/references/pmf_and_build_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2Freferences%2Fpmf_and_build_canon.md -->","isInternal":false,"tokens":1327,"sizeBytes":5500},{"name":"SKILL.md","path":"productivity/andreessen/skills/andreessen/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/skills/andreessen/SKILL.md","title":"andreessen","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2Fskills%2Fandreessen%2FSKILL.md -->","frontmatter":{"name":"andreessen","description":"Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ideas, ventures, features, and career bets through Andreessen's actual frameworks — market dominates team and product; the only milestone that matters is product/market fit; bias to build over deliberate. Use when the user says 'andreessen', 'pmarca mode', 'should I build this', 'is there a market', 'are we at product/market fit', 'pmf check', 'pressure-test this idea', 'be brutal about this venture', 'market-first take', or wants a no-disclaimers, no-hedging, confidence-leveled verdict on whether something is worth pursuing. Also provides the 3x5-card + Anti-Todo personal productivity routine. Runs on a fixed anti-sycophancy operating prompt: leads with the strongest counterargument, never validates premises, uses explicit confidence levels, never apologizes for disagreeing. Not for polite brainstorming — this skill exists to tell you the market is dead when it is.","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Persona skill — verbatim operating prompt + Andreessen canon","inspired_by":"Marc Andreessen (a16z); custom operating prompt supplied by user"}},"isInternal":false,"tokens":2926,"sizeBytes":11996},{"name":"complexity_matching.md","path":"productivity/capture/skills/capture/references/complexity_matching.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/capture/skills/capture/references/complexity_matching.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fcapture%2Fskills%2Fcapture%2Freferences%2Fcomplexity_matching.md -->","isInternal":false,"tokens":1886,"sizeBytes":7660},{"name":"voice_preservation.md","path":"productivity/capture/skills/capture/references/voice_preservation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/capture/skills/capture/references/voice_preservation.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fcapture%2Fskills%2Fcapture%2Freferences%2Fvoice_preservation.md -->","isInternal":false,"tokens":1088,"sizeBytes":4526},{"name":"workspace_detection.md","path":"productivity/capture/skills/capture/references/workspace_detection.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/capture/skills/capture/references/workspace_detection.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fcapture%2Fskills%2Fcapture%2Freferences%2Fworkspace_detection.md -->","isInternal":false,"tokens":1152,"sizeBytes":4937},{"name":"SKILL.md","path":"productivity/capture/skills/capture/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/capture/skills/capture/SKILL.md","title":"capture","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fcapture%2Fskills%2Fcapture%2FSKILL.md -->","frontmatter":{"name":"capture","description":"Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed ideas — even without the exact phrase — the intent is the same. Fast-to-action by design: no upfront intake. Output is four sections (Projects/Ideas, Tasks, Connections, How I Can Help) ending with a directive question. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project.","license":"MIT","metadata":{"source_spec":"megaprompts/05-capture-megaprompt.md","build_pattern":"Path B (direct conversion)","version":"1.0.0"}},"isInternal":false,"tokens":2536,"sizeBytes":11105},{"name":"example_time_block_plan.md","path":"productivity/deep-work/skills/deep-work/assets/example_time_block_plan.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/skills/deep-work/assets/example_time_block_plan.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2Fskills%2Fdeep-work%2Fassets%2Fexample_time_block_plan.md -->","isInternal":false,"tokens":1102,"sizeBytes":3869},{"name":"shutdown_checklist.md","path":"productivity/deep-work/skills/deep-work/assets/shutdown_checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/skills/deep-work/assets/shutdown_checklist.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2Fskills%2Fdeep-work%2Fassets%2Fshutdown_checklist.md -->","isInternal":false,"tokens":486,"sizeBytes":2013},{"name":"deep_work_canon.md","path":"productivity/deep-work/skills/deep-work/references/deep_work_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/skills/deep-work/references/deep_work_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2Fskills%2Fdeep-work%2Freferences%2Fdeep_work_canon.md -->","isInternal":false,"tokens":1490,"sizeBytes":6560},{"name":"shallow_work_budget.md","path":"productivity/deep-work/skills/deep-work/references/shallow_work_budget.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/skills/deep-work/references/shallow_work_budget.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2Fskills%2Fdeep-work%2Freferences%2Fshallow_work_budget.md -->","isInternal":false,"tokens":1513,"sizeBytes":6590},{"name":"time_blocking_method.md","path":"productivity/deep-work/skills/deep-work/references/time_blocking_method.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/skills/deep-work/references/time_blocking_method.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2Fskills%2Fdeep-work%2Freferences%2Ftime_blocking_method.md -->","isInternal":false,"tokens":1479,"sizeBytes":6139},{"name":"SKILL.md","path":"productivity/deep-work/skills/deep-work/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/skills/deep-work/SKILL.md","title":"deep-work","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2Fskills%2Fdeep-work%2FSKILL.md -->","frontmatter":{"name":"deep-work","description":"Use when someone wants to plan a deep work day, time-block their calendar or task list, budget or cut shallow work, protect focus hours, track deep-work sessions and streaks, run an end-of-day shutdown ritual, or says \"/deep-work\" or \"/time-block\". Classifies tasks deep vs shallow, builds an energy-first time-blocked schedule that refuses deep demand past the 4-hour ceiling, batches shallow work into at most two windows, and logs focus sessions against a weekly target.","argument-hint":"[today's task list]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Path-B method skill — Cal Newport time-block discipline preserved + deterministic scheduling scripts added","distinct_from":"andreessen 3x5 card (picks WHAT to do today; deep-work plans WHEN and HOW with attention protected); project-management capacity planning (team capacity; this is one person's attention)"}},"isInternal":false,"tokens":1450,"sizeBytes":6095},{"name":"grill_me_section_walk.md","path":"productivity/email/skills/inbox-setup/references/grill_me_section_walk.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-setup/references/grill_me_section_walk.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-setup%2Freferences%2Fgrill_me_section_walk.md -->","isInternal":false,"tokens":1863,"sizeBytes":7259},{"name":"kb_file_contract.md","path":"productivity/email/skills/inbox-setup/references/kb_file_contract.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-setup/references/kb_file_contract.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-setup%2Freferences%2Fkb_file_contract.md -->","isInternal":false,"tokens":1611,"sizeBytes":6185},{"name":"voice_calibration.md","path":"productivity/email/skills/inbox-setup/references/voice_calibration.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-setup/references/voice_calibration.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-setup%2Freferences%2Fvoice_calibration.md -->","isInternal":false,"tokens":1901,"sizeBytes":8352},{"name":"SKILL.md","path":"productivity/email/skills/inbox-setup/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-setup/SKILL.md","title":"inbox-setup","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-setup%2FSKILL.md -->","frontmatter":{"name":"inbox-setup","description":"One-time setup skill that builds a personalized inbox triage knowledge base via interactive interview. Interviews the user about their email patterns, business context, reply style, and priorities using grill-me discipline (one question at a time, forcing format where possible, dependency-ordered, each question explains why I'm asking), then generates the knowledge base files that power the companion 'inbox-triage' skill. Run this once before using inbox-triage for the first time. Re-run when business, pricing, or priorities change significantly. Triggers: 'set up my inbox', 'configure inbox triage', 'set up my email system', 'configure email triage', 'build my email knowledge base', 'initialize email management', 'set up inbox triage', 'onboard email triage', or any variation where someone wants to get the email triage system running for the first time.","license":"MIT","metadata":{"source_spec":"megaprompts/06-inbox-setup-megaprompt.md","build_pattern":"Path B (direct conversion)","paired_with":"inbox-triage (shared 7-file KB contract)","version":"1.0.0"}},"isInternal":false,"tokens":3608,"sizeBytes":15347},{"name":"drafts_only_safety.md","path":"productivity/email/skills/inbox-triage/references/drafts_only_safety.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-triage/references/drafts_only_safety.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-triage%2Freferences%2Fdrafts_only_safety.md -->","isInternal":false,"tokens":1755,"sizeBytes":7408},{"name":"kb_file_contract.md","path":"productivity/email/skills/inbox-triage/references/kb_file_contract.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-triage/references/kb_file_contract.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-triage%2Freferences%2Fkb_file_contract.md -->","isInternal":false,"tokens":1508,"sizeBytes":6164},{"name":"triage_decision_framework.md","path":"productivity/email/skills/inbox-triage/references/triage_decision_framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-triage/references/triage_decision_framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-triage%2Freferences%2Ftriage_decision_framework.md -->","isInternal":false,"tokens":1790,"sizeBytes":7450},{"name":"SKILL.md","path":"productivity/email/skills/inbox-triage/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/skills/inbox-triage/SKILL.md","title":"inbox-triage","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2Fskills%2Finbox-triage%2FSKILL.md -->","frontmatter":{"name":"inbox-triage","description":"Runs a full inbox triage using the knowledge base created by the 'inbox-setup' skill. Light-intake by design (most invocations skip questions and run with KB-default preferences); asks at most 2 grill-me override questions when invocation is outside normal cadence or includes category-skip intent. Searches recent emails, classifies them via the user's taxonomy, researches new senders, generates recommendations, drafts replies (NEVER sends), delivers a report in the user's preferred format, and updates the knowledge base with learnings. Designed to run on a recurring schedule (1-3x daily) or on demand. Use when the user wants their inbox processed, in any variation (e.g., 'triage my inbox', 'inbox triage', 'check my email', 'run email triage', 'process my inbox', 'what's new in my email', 'handle my email', 'email triage'). Requires the inbox-setup skill to have been run first.","license":"MIT","metadata":{"source_spec":"megaprompts/07-inbox-triage-megaprompt.md","build_pattern":"Path B (direct conversion)","paired_with":"inbox-setup (consumes the 7-file KB it produces)","version":"1.0.0"}},"isInternal":false,"tokens":3395,"sizeBytes":14231},{"name":"goal_prompt_patterns.md","path":"productivity/fable-goal/skills/fable-goal/references/goal_prompt_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/fable-goal/skills/fable-goal/references/goal_prompt_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Ffable-goal%2Fskills%2Ffable-goal%2Freferences%2Fgoal_prompt_patterns.md -->","isInternal":false,"tokens":1869,"sizeBytes":8908},{"name":"SKILL.md","path":"productivity/fable-goal/skills/fable-goal/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/fable-goal/skills/fable-goal/SKILL.md","title":"fable-goal","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Ffable-goal%2Fskills%2Ffable-goal%2FSKILL.md -->","frontmatter":{"name":"fable-goal","description":"Convert a rambling description of a desired outcome into one polished, autonomous /goal prompt ready to paste into a fresh session. Use when the user says \"/fable-goal\", \"turn this into a goal prompt\", \"write me a fable prompt\", \"write the prompt that builds X\", or rambles about something they want made and asks for the prompt that makes it happen. The output is a single copy-paste prompt, never the build itself. Do NOT use when the user wants the thing built right now in this session — only when they want the PROMPT that will make it happen in a fresh session."},"isInternal":false,"tokens":2140,"sizeBytes":9553},{"name":"example_handoff.md","path":"productivity/handoff/skills/session-handoff/assets/example_handoff.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/assets/example_handoff.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2Fassets%2Fexample_handoff.md -->","frontmatter":{"generated_at":"2026-05-21T16:30:00Z","goal":"Finish wiring the redaction linter into /cs-handoff and ship a draft PR before EOD."},"isInternal":false,"tokens":631,"sizeBytes":2331},{"name":"README.md","path":"productivity/handoff/skills/session-handoff/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/README.md","title":"Session-handoff Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2FREADME.md -->","isInternal":false,"tokens":297,"sizeBytes":1204},{"name":"configuration.md","path":"productivity/handoff/skills/session-handoff/references/configuration.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/references/configuration.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2Freferences%2Fconfiguration.md -->","isInternal":false,"tokens":1352,"sizeBytes":5407},{"name":"deduplication_discipline.md","path":"productivity/handoff/skills/session-handoff/references/deduplication_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/references/deduplication_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2Freferences%2Fdeduplication_discipline.md -->","isInternal":false,"tokens":1157,"sizeBytes":4633},{"name":"handoff_prompt.md","path":"productivity/handoff/skills/session-handoff/references/handoff_prompt.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/references/handoff_prompt.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2Freferences%2Fhandoff_prompt.md -->","isInternal":false,"tokens":1020,"sizeBytes":4366},{"name":"handoff_structure.md","path":"productivity/handoff/skills/session-handoff/references/handoff_structure.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/references/handoff_structure.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2Freferences%2Fhandoff_structure.md -->","isInternal":false,"tokens":1177,"sizeBytes":4579},{"name":"redaction_checklist.md","path":"productivity/handoff/skills/session-handoff/references/redaction_checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/references/redaction_checklist.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2Freferences%2Fredaction_checklist.md -->","isInternal":false,"tokens":1194,"sizeBytes":4739},{"name":"SKILL.md","path":"productivity/handoff/skills/session-handoff/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/skills/session-handoff/SKILL.md","title":"session-handoff","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2Fskills%2Fsession-handoff%2FSKILL.md -->","frontmatter":{"name":"session-handoff","description":"Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'm ending this session', 'pick this up later', or any variation signaling intent to pass work to a fresh agent. Also trigger on implicit signals: the user announcing they're switching machines, ending the day mid-task, or context is growing long without a natural stopping point.","license":"MIT","argument-hint":"What will the next session be used for?","metadata":{"version":"1.0.0","voice":"Matt Pocock — no-duplication, reference-existing-artifacts, tailored to next-session focus","inspired_by":"https://github.com/mattpocock/skills/tree/main/skills/productivity/handoff"}},"isInternal":false,"tokens":2329,"sizeBytes":9968},{"name":"example_agenda.md","path":"productivity/meetings/skills/meetings/assets/example_agenda.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/skills/meetings/assets/example_agenda.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Fassets%2Fexample_agenda.md -->","isInternal":false,"tokens":887,"sizeBytes":3361},{"name":"meeting_gate_worksheet.md","path":"productivity/meetings/skills/meetings/assets/meeting_gate_worksheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/skills/meetings/assets/meeting_gate_worksheet.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Fassets%2Fmeeting_gate_worksheet.md -->","isInternal":false,"tokens":722,"sizeBytes":3180},{"name":"action_item_discipline.md","path":"productivity/meetings/skills/meetings/references/action_item_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/skills/meetings/references/action_item_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Freferences%2Faction_item_discipline.md -->","isInternal":false,"tokens":1327,"sizeBytes":5681},{"name":"agenda_discipline.md","path":"productivity/meetings/skills/meetings/references/agenda_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/skills/meetings/references/agenda_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Freferences%2Fagenda_discipline.md -->","isInternal":false,"tokens":1449,"sizeBytes":6388},{"name":"meeting_cost_canon.md","path":"productivity/meetings/skills/meetings/references/meeting_cost_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/skills/meetings/references/meeting_cost_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2Freferences%2Fmeeting_cost_canon.md -->","isInternal":false,"tokens":1474,"sizeBytes":6356},{"name":"SKILL.md","path":"productivity/meetings/skills/meetings/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/skills/meetings/SKILL.md","title":"meetings","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2Fskills%2Fmeetings%2FSKILL.md -->","frontmatter":{"name":"meetings","description":"Use when someone wants to decide whether a meeting is worth calling, price a meeting in dollars, build a timeboxed agenda with desired outcomes, or turn messy meeting notes into owned action items — or says \"should this be a meeting\", \"/cs-meeting-prep\", or \"/cs-meeting-actions\". Runs a cost gate (ASYNC / NOT-READY / MEET), builds a decision-first agenda, and extracts an owner + due-date checklist that flags every orphan.","argument-hint":"[the meeting to gate, or the notes to extract actions from]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Path-B discipline skill — Rogelberg/HBR meeting-science canon + deterministic gate/agenda/extraction scripts","distinct_from":"project-management (team ceremonies + Jira delivery flow; this is personal meeting hygiene); business-operations/internal-comms (org-level communication design; this never auto-sends); productivity/capture (private brain-dump triage; this parses shared meeting notes)"}},"isInternal":false,"tokens":1430,"sizeBytes":6003},{"name":"cognitive_bias_canon.md","path":"productivity/reflect/skills/reflect/references/cognitive_bias_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/reflect/skills/reflect/references/cognitive_bias_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Freflect%2Fskills%2Freflect%2Freferences%2Fcognitive_bias_canon.md -->","isInternal":false,"tokens":1850,"sizeBytes":8450},{"name":"conversation_reflection_practice.md","path":"productivity/reflect/skills/reflect/references/conversation_reflection_practice.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/reflect/skills/reflect/references/conversation_reflection_practice.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Freflect%2Fskills%2Freflect%2Freferences%2Fconversation_reflection_practice.md -->","isInternal":false,"tokens":1927,"sizeBytes":8758},{"name":"honest_output_discipline.md","path":"productivity/reflect/skills/reflect/references/honest_output_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/reflect/skills/reflect/references/honest_output_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Freflect%2Fskills%2Freflect%2Freferences%2Fhonest_output_discipline.md -->","isInternal":false,"tokens":2046,"sizeBytes":9693},{"name":"SKILL.md","path":"productivity/reflect/skills/reflect/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/reflect/skills/reflect/SKILL.md","title":"reflect","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Freflect%2Fskills%2Freflect%2FSKILL.md -->","frontmatter":{"name":"reflect","description":"Mid-conversation reflection skill that pauses execution and zooms out from detail-mode to honestly reassess direction, assumptions, and bias. Use when the user says 'reflect', 'take a step back', 'step back', 'zoom out', 'are we missing something', 'bigger picture', 'sanity check this', 'are we on track', 'are we overthinking this', 'forest for the trees', or any variation signaling intent to break out of detail-mode and reassess. Also trigger when the conversation has gone deep on implementation details without strategic check-in, or when the user shows signs of being stuck — that's often a signal the framing needs a reset, not more detail work. Intentionally low-intake: runs the 5-dimension analysis immediately when prior context is rich enough; asks one forcing clarifier only when invocation context is too thin to reassess from.","license":"MIT","metadata":{"source_spec":"megaprompts/02-reflect-megaprompt.md","build_pattern":"Path B (direct conversion)","version":"1.0.0"}},"isInternal":false,"tokens":2178,"sizeBytes":9809},{"name":"example_roast_verdict.md","path":"productivity/roast/skills/roast/assets/example_roast_verdict.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/assets/example_roast_verdict.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Fassets%2Fexample_roast_verdict.md -->","isInternal":false,"tokens":999,"sizeBytes":3969},{"name":"roast_brief_worksheet.md","path":"productivity/roast/skills/roast/assets/roast_brief_worksheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/assets/roast_brief_worksheet.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Fassets%2Froast_brief_worksheet.md -->","isInternal":false,"tokens":389,"sizeBytes":1535},{"name":"README.md","path":"productivity/roast/skills/roast/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/README.md","title":"Roast Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2FREADME.md -->","isInternal":false,"tokens":415,"sizeBytes":1701},{"name":"adversarial_panel_canon.md","path":"productivity/roast/skills/roast/references/adversarial_panel_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/references/adversarial_panel_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Freferences%2Fadversarial_panel_canon.md -->","isInternal":false,"tokens":1344,"sizeBytes":5668},{"name":"cheapest_test_canon.md","path":"productivity/roast/skills/roast/references/cheapest_test_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/references/cheapest_test_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Freferences%2Fcheapest_test_canon.md -->","isInternal":false,"tokens":1143,"sizeBytes":4475},{"name":"verdict_synthesis_method.md","path":"productivity/roast/skills/roast/references/verdict_synthesis_method.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/references/verdict_synthesis_method.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2Freferences%2Fverdict_synthesis_method.md -->","isInternal":false,"tokens":1354,"sizeBytes":5336},{"name":"SKILL.md","path":"productivity/roast/skills/roast/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/skills/roast/SKILL.md","title":"roast","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2Fskills%2Froast%2FSKILL.md -->","frontmatter":{"name":"roast","description":"Use when someone asks to roast an idea, pressure-test or stress-test an idea, validate a business idea, \"convene the panel\", get a brutal second opinion before building something, or says \"/roast\". 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Use when the user asks about a Swedish learning path, YouTube clips or podcasts for Swedish, SFI videos, level assessment for svenska, or requests for Peter SFI / Lätt Svenska med Oskar / Radio Sweden på lätt svenska / Klartext-style recommendations."},"isInternal":false,"tokens":2530,"sizeBytes":11402},{"name":"example_weekly_review.md","path":"productivity/weekly-review/skills/weekly-review/assets/example_weekly_review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/skills/weekly-review/assets/example_weekly_review.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2Fskills%2Fweekly-review%2Fassets%2Fexample_weekly_review.md -->","isInternal":false,"tokens":1121,"sizeBytes":4163},{"name":"weekly_review_checklist.md","path":"productivity/weekly-review/skills/weekly-review/assets/weekly_review_checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/skills/weekly-review/assets/weekly_review_checklist.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2Fskills%2Fweekly-review%2Fassets%2Fweekly_review_checklist.md -->","isInternal":false,"tokens":660,"sizeBytes":2503},{"name":"gtd_weekly_review_canon.md","path":"productivity/weekly-review/skills/weekly-review/references/gtd_weekly_review_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/skills/weekly-review/references/gtd_weekly_review_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2Fskills%2Fweekly-review%2Freferences%2Fgtd_weekly_review_canon.md -->","isInternal":false,"tokens":1451,"sizeBytes":6384},{"name":"open_loop_psychology.md","path":"productivity/weekly-review/skills/weekly-review/references/open_loop_psychology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/skills/weekly-review/references/open_loop_psychology.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2Fskills%2Fweekly-review%2Freferences%2Fopen_loop_psychology.md -->","isInternal":false,"tokens":1387,"sizeBytes":6185},{"name":"review_cadence_design.md","path":"productivity/weekly-review/skills/weekly-review/references/review_cadence_design.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/skills/weekly-review/references/review_cadence_design.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2Fskills%2Fweekly-review%2Freferences%2Freview_cadence_design.md -->","isInternal":false,"tokens":1478,"sizeBytes":6398},{"name":"SKILL.md","path":"productivity/weekly-review/skills/weekly-review/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/skills/weekly-review/SKILL.md","title":"weekly-review","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2Fskills%2Fweekly-review%2FSKILL.md -->","frontmatter":{"name":"weekly-review","description":"Use when someone wants to run a weekly review, close open loops, audit stalled projects and commitments, get their system back to trusted, restart a lapsed review habit, or says \"/cs-weekly-review\". Walks David Allen's three-phase loop — GET CLEAR, GET CURRENT, GET CREATIVE — with deterministic scripts that inventory open loops, gate the checklist with named gaps, and score commitment health 0-100.","argument-hint":"[optional: directory or notes to review]","license":"MIT","metadata":{"version":"1.0.0","build_pattern":"Path-B ritual skill — GTD weekly-review loop preserved + deterministic scanner/gate/auditor scripts added","distinct_from":"reflect (per-conversation reflection, not a recurring cadence); capture (intake that feeds the system, not the review that maintains it); project-management sprint retros (team ceremony, not a personal trusted-system audit)"}},"isInternal":false,"tokens":1368,"sizeBytes":5813},{"name":"permission_scheme_template.json","path":"project-management/skills/atlassian-admin/assets/permission_scheme_template.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-admin/assets/permission_scheme_template.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-admin%2Fassets%2Fpermission_scheme_template.json -->","frontmatter":{"permissionScheme":{"name":"Standard Project Permission Scheme","description":"Default permission scheme for standard projects. Assigns permissions based on project roles.","version":"1.0","lastUpdated":"YYYY-MM-DD","owner":"IT Admin Team"},"roles":{"projectAdmin":{"description":"Full project administration including configuration and user management","typicalGroups":["project-leads","engineering-managers"]},"developer":{"description":"Create and manage issues, transitions, and attachments","typicalGroups":["dept-engineering","dept-product"]},"user":{"description":"View issues, add comments, and create basic issues","typicalGroups":["org-all-employees"]},"viewer":{"description":"Read-only access to project issues and boards","typicalGroups":["stakeholders","external-contractors"]}},"permissions":{"project":{"ADMINISTER_PROJECTS":{"description":"Manage project settings, roles, and permissions","grantedTo":["projectAdmin"]},"BROWSE_PROJECTS":{"description":"View the project and its issues","grantedTo":["projectAdmin","developer","user","viewer"]},"VIEW_DEV_TOOLS":{"description":"View development panel (commits, branches, PRs)","grantedTo":["projectAdmin","developer"]},"VIEW_READONLY_WORKFLOW":{"description":"View read-only workflow","grantedTo":["projectAdmin","developer","user","viewer"]}},"issues":{"CREATE_ISSUES":{"description":"Create new issues in the project","grantedTo":["projectAdmin","developer","user"]},"EDIT_ISSUES":{"description":"Edit issue fields","grantedTo":["projectAdmin","developer"]},"DELETE_ISSUES":{"description":"Delete issues permanently","grantedTo":["projectAdmin"]},"ASSIGN_ISSUES":{"description":"Assign issues to team members","grantedTo":["projectAdmin","developer"]},"ASSIGNABLE_USER":{"description":"Be assigned to issues","grantedTo":["projectAdmin","developer"]},"CLOSE_ISSUES":{"description":"Close/resolve issues","grantedTo":["projectAdmin","developer"]},"RESOLVE_ISSUES":{"description":"Set issue resolution","grantedTo":["projectAdmin","developer"]},"TRANSITION_ISSUES":{"description":"Transition issues through workflow","grantedTo":["projectAdmin","developer","user"]},"LINK_ISSUES":{"description":"Create and remove issue links","grantedTo":["projectAdmin","developer"]},"MOVE_ISSUES":{"description":"Move issues between projects","grantedTo":["projectAdmin"]},"SCHEDULE_ISSUES":{"description":"Set due dates on issues","grantedTo":["projectAdmin","developer"]},"SET_ISSUE_SECURITY":{"description":"Set security level on issues","grantedTo":["projectAdmin"]}},"comments":{"ADD_COMMENTS":{"description":"Add comments to issues","grantedTo":["projectAdmin","developer","user"]},"EDIT_ALL_COMMENTS":{"description":"Edit any comment","grantedTo":["projectAdmin"]},"EDIT_OWN_COMMENTS":{"description":"Edit own comments","grantedTo":["projectAdmin","developer","user"]},"DELETE_ALL_COMMENTS":{"description":"Delete any comment","grantedTo":["projectAdmin"]},"DELETE_OWN_COMMENTS":{"description":"Delete own comments","grantedTo":["projectAdmin","developer","user"]}},"attachments":{"CREATE_ATTACHMENTS":{"description":"Attach files to issues","grantedTo":["projectAdmin","developer","user"]},"DELETE_ALL_ATTACHMENTS":{"description":"Delete any attachment","grantedTo":["projectAdmin"]},"DELETE_OWN_ATTACHMENTS":{"description":"Delete own attachments","grantedTo":["projectAdmin","developer","user"]}},"worklogs":{"WORK_ON_ISSUES":{"description":"Log work on issues","grantedTo":["projectAdmin","developer"]},"EDIT_ALL_WORKLOGS":{"description":"Edit any worklog","grantedTo":["projectAdmin"]},"EDIT_OWN_WORKLOGS":{"description":"Edit own worklogs","grantedTo":["projectAdmin","developer"]},"DELETE_ALL_WORKLOGS":{"description":"Delete any worklog","grantedTo":["projectAdmin"]},"DELETE_OWN_WORKLOGS":{"description":"Delete own worklogs","grantedTo":["projectAdmin","developer"]}}},"projectMappings":[{"projectKey":"EXAMPLE","projectName":"Example Project","scheme":"Standard Project Permission Scheme","roleAssignments":{"projectAdmin":["project-leads"],"developer":["team-example-devs"],"user":["org-all-employees"],"viewer":["stakeholders-example"]}}],"notes":{"usage":"Copy this template and customize role assignments per project. Use group names that match your Atlassian groups.","review":"Review permission scheme assignments quarterly as part of access review.","changes":"Any changes to permission schemes should be documented and approved by IT Admin."}},"isInternal":false,"tokens":1396,"sizeBytes":5808},{"name":"security-hardening-guide.md","path":"project-management/skills/atlassian-admin/references/security-hardening-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-admin/references/security-hardening-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-admin%2Freferences%2Fsecurity-hardening-guide.md -->","isInternal":false,"tokens":1758,"sizeBytes":7891},{"name":"user-provisioning-checklist.md","path":"project-management/skills/atlassian-admin/references/user-provisioning-checklist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-admin/references/user-provisioning-checklist.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-admin%2Freferences%2Fuser-provisioning-checklist.md -->","isInternal":false,"tokens":1574,"sizeBytes":7055},{"name":"SKILL.md","path":"project-management/skills/atlassian-admin/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-admin/SKILL.md","title":"atlassian-admin","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-admin%2FSKILL.md -->","frontmatter":{"name":"atlassian-admin","description":"Atlassian Administrator for managing and organizing Atlassian products (Jira, Confluence, Bitbucket, Trello), users, permissions, security, integrations, system configuration, and org-wide governance. Use when asked to add users to Jira, change Confluence permissions, configure access control, update admin settings, manage Atlassian groups, set up SSO, install marketplace apps, review security policies, or handle any org-wide Atlassian administration task."},"isInternal":false,"tokens":2923,"sizeBytes":12975},{"name":"governance-framework.md","path":"project-management/skills/atlassian-templates/references/governance-framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-templates/references/governance-framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-templates%2Freferences%2Fgovernance-framework.md -->","isInternal":false,"tokens":2014,"sizeBytes":8900},{"name":"template-design-patterns.md","path":"project-management/skills/atlassian-templates/references/template-design-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-templates/references/template-design-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-templates%2Freferences%2Ftemplate-design-patterns.md -->","isInternal":false,"tokens":1493,"sizeBytes":6521},{"name":"SKILL.md","path":"project-management/skills/atlassian-templates/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/atlassian-templates/SKILL.md","title":"atlassian-templates","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fatlassian-templates%2FSKILL.md -->","frontmatter":{"name":"atlassian-templates","description":"Atlassian Template and Files Creator/Modifier expert for creating, modifying, and managing Jira and Confluence templates, blueprints, custom layouts, reusable components, and standardized content structures. Use when building org-wide templates, custom blueprints, page layouts, and automated content generation."},"isInternal":false,"tokens":2791,"sizeBytes":12440},{"name":"macro-cheat-sheet.md","path":"project-management/skills/confluence-expert/references/macro-cheat-sheet.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/confluence-expert/references/macro-cheat-sheet.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fconfluence-expert%2Freferences%2Fmacro-cheat-sheet.md -->","isInternal":false,"tokens":1840,"sizeBytes":7350},{"name":"space-architecture-patterns.md","path":"project-management/skills/confluence-expert/references/space-architecture-patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/confluence-expert/references/space-architecture-patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fconfluence-expert%2Freferences%2Fspace-architecture-patterns.md -->","isInternal":false,"tokens":1714,"sizeBytes":7693},{"name":"templates.md","path":"project-management/skills/confluence-expert/references/templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/confluence-expert/references/templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fconfluence-expert%2Freferences%2Ftemplates.md -->","isInternal":false,"tokens":4396,"sizeBytes":14794},{"name":"SKILL.md","path":"project-management/skills/confluence-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/confluence-expert/SKILL.md","title":"confluence-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fconfluence-expert%2FSKILL.md -->","frontmatter":{"name":"confluence-expert","description":"Atlassian Confluence expert for creating and managing spaces, knowledge bases, and documentation. Configures space permissions and hierarchies, creates page templates with macros, sets up documentation taxonomies, designs page layouts, and manages content governance. Use when users need to build or restructure a Confluence space, design page hierarchies with permission structures, author or standardise documentation templates, embed Jira reports in pages, run knowledge base audits, or establish documentation standards and collaborative workflows."},"isInternal":false,"tokens":2955,"sizeBytes":12466},{"name":"automation-examples.md","path":"project-management/skills/jira-expert/references/automation-examples.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/jira-expert/references/automation-examples.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fjira-expert%2Freferences%2Fautomation-examples.md -->","isInternal":false,"tokens":2392,"sizeBytes":9668},{"name":"AUTOMATION.md","path":"project-management/skills/jira-expert/references/AUTOMATION.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/jira-expert/references/AUTOMATION.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fjira-expert%2Freferences%2FAUTOMATION.md -->","isInternal":false,"tokens":2217,"sizeBytes":9163},{"name":"jql-examples.md","path":"project-management/skills/jira-expert/references/jql-examples.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/jira-expert/references/jql-examples.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fjira-expert%2Freferences%2Fjql-examples.md -->","isInternal":false,"tokens":2148,"sizeBytes":7820},{"name":"WORKFLOWS.md","path":"project-management/skills/jira-expert/references/WORKFLOWS.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/jira-expert/references/WORKFLOWS.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fjira-expert%2Freferences%2FWORKFLOWS.md -->","isInternal":false,"tokens":1452,"sizeBytes":6431},{"name":"SKILL.md","path":"project-management/skills/jira-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/jira-expert/SKILL.md","title":"jira-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fjira-expert%2FSKILL.md -->","frontmatter":{"name":"jira-expert","description":"Atlassian Jira expert for creating and managing projects, planning, product discovery, JQL queries, workflows, custom fields, automation, reporting, and all Jira features. Use when setting up or configuring Jira projects, writing JQL and advanced searches, creating dashboards, designing workflows, or performing technical Jira operations."},"isInternal":false,"tokens":3059,"sizeBytes":12663},{"name":"SKILL.md","path":"project-management/skills/meeting-analyzer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/meeting-analyzer/SKILL.md","title":"meeting-analyzer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fmeeting-analyzer%2FSKILL.md -->","frontmatter":{"name":"meeting-analyzer","description":"Analyzes meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this skill whenever the user uploads or points to meeting transcripts (.txt, .md, .vtt, .srt, .docx), asks about their communication habits, wants feedback on how they run meetings, requests speaking ratio analysis, mentions filler words or conflict avoidance, or wants to compare their communication across time periods. Also trigger when users mention tools like Granola, Otter, Fireflies, or Zoom transcripts. Even if the user just says \"look at my meetings\" or \"how do I come across in meetings\" — use this skill."},"isInternal":false,"tokens":2704,"sizeBytes":12245},{"name":"expected_flow_metrics.json","path":"project-management/skills/pm-skills/assets/expected_flow_metrics.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/pm-skills/assets/expected_flow_metrics.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fpm-skills%2Fassets%2Fexpected_flow_metrics.json -->","frontmatter":{"mode":"flow","as_of":"2026-06-10","counts":{"total":14,"done":11,"wip":2},"cycle_time_days":{"p50":9,"p85":14,"p95":16,"basis":"created→resolved (approximation; Jira exports rarely carry an in-progress timestamp)"},"throughput":{"done_per_week":2.08,"weeks_observed":5.3},"sle":{"days":14,"conformance_pct":90.9},"work_item_age":[{"key":"PHX-112","summary":"Realtime presence indicators","age_days":15},{"key":"PHX-113","summary":"Usage analytics dashboard","age_days":2}],"aging_wip_alerts":[{"key":"PHX-112","summary":"Realtime presence indicators","age_days":15}],"warnings":[],"forecast":{"items":20,"method":"Monte Carlo over historical weekly throughput (10k trials, seeded)","weeks":{"p50":9,"p70":10,"p85":10,"p95":10}}},"isInternal":false,"tokens":356,"sizeBytes":1021},{"name":"sample_jira_snapshot.json","path":"project-management/skills/pm-skills/assets/sample_jira_snapshot.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/pm-skills/assets/sample_jira_snapshot.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fpm-skills%2Fassets%2Fsample_jira_snapshot.json -->","frontmatter":{"_comment":"Saved output shape of mcp__atlassian__searchJiraIssuesUsingJql — feed to scripts/jira_snapshot_bridge.py. Expected flow output pinned in expected_flow_metrics.json.","issues":[{"key":"PHX-101","fields":{"summary":"User authentication service","status":{"name":"Done"},"created":"2026-05-04T09:00:00.000+0000","resolutiondate":"2026-05-08T16:00:00.000+0000","customfield_10016":5,"sprint":{"name":"Sprint 11"},"assignee":{"displayName":"A. Rivera"},"priority":{"name":"High"}}},{"key":"PHX-102","fields":{"summary":"Dashboard layout","status":{"name":"Done"},"created":"2026-05-04T09:00:00.000+0000","resolutiondate":"2026-05-12T11:00:00.000+0000","customfield_10016":3,"sprint":{"name":"Sprint 11"},"assignee":{"displayName":"B. Okafor"},"priority":{"name":"Medium"}}},{"key":"PHX-103","fields":{"summary":"Password reset flow","status":{"name":"Done"},"created":"2026-05-05T09:00:00.000+0000","resolutiondate":"2026-05-13T15:00:00.000+0000","customfield_10016":2,"sprint":{"name":"Sprint 11"},"assignee":{"displayName":"A. Rivera"},"priority":{"name":"Medium"}}},{"key":"PHX-104","fields":{"summary":"Billing webhooks","status":{"name":"Done"},"created":"2026-05-11T09:00:00.000+0000","resolutiondate":"2026-05-20T10:00:00.000+0000","customfield_10016":8,"sprint":{"name":"Sprint 12"},"assignee":{"displayName":"C. Duarte"},"priority":{"name":"High"}}},{"key":"PHX-105","fields":{"summary":"Email notifications","status":{"name":"Done"},"created":"2026-05-12T09:00:00.000+0000","resolutiondate":"2026-05-19T17:00:00.000+0000","customfield_10016":3,"sprint":{"name":"Sprint 12"},"assignee":{"displayName":"B. Okafor"},"priority":{"name":"Medium"}}},{"key":"PHX-106","fields":{"summary":"Audit log export","status":{"name":"Done"},"created":"2026-05-13T09:00:00.000+0000","resolutiondate":"2026-05-22T12:00:00.000+0000","customfield_10016":5,"sprint":{"name":"Sprint 12"},"assignee":{"displayName":"D. Weiss"},"priority":{"name":"Low"}}},{"key":"PHX-107","fields":{"summary":"Mobile responsive nav","status":{"name":"Done"},"created":"2026-05-18T09:00:00.000+0000","resolutiondate":"2026-05-27T09:30:00.000+0000","customfield_10016":5,"sprint":{"name":"Sprint 13"},"assignee":{"displayName":"A. Rivera"},"priority":{"name":"High"}}},{"key":"PHX-108","fields":{"summary":"Rate limiting middleware","status":{"name":"Done"},"created":"2026-05-19T09:00:00.000+0000","resolutiondate":"2026-05-29T14:00:00.000+0000","customfield_10016":3,"sprint":{"name":"Sprint 13"},"assignee":{"displayName":"C. Duarte"},"priority":{"name":"Medium"}}},{"key":"PHX-109","fields":{"summary":"Data export CSV","status":{"name":"Done"},"created":"2026-05-20T09:00:00.000+0000","resolutiondate":"2026-06-03T16:00:00.000+0000","customfield_10016":2,"sprint":{"name":"Sprint 13"},"assignee":{"displayName":"D. Weiss"},"priority":{"name":"Low"}}},{"key":"PHX-110","fields":{"summary":"SSO SAML integration","status":{"name":"Done"},"created":"2026-05-25T09:00:00.000+0000","resolutiondate":"2026-06-10T10:00:00.000+0000","customfield_10016":8,"sprint":{"name":"Sprint 14"},"assignee":{"displayName":"C. Duarte"},"priority":{"name":"High"}}},{"key":"PHX-111","fields":{"summary":"Search relevance tuning","status":{"name":"Done"},"created":"2026-06-01T09:00:00.000+0000","resolutiondate":"2026-06-09T11:00:00.000+0000","customfield_10016":3,"sprint":{"name":"Sprint 14"},"assignee":{"displayName":"B. Okafor"},"priority":{"name":"Medium"}}},{"key":"PHX-112","fields":{"summary":"Realtime presence indicators","status":{"name":"In Progress"},"created":"2026-05-26T09:00:00.000+0000","customfield_10016":8,"sprint":{"name":"Sprint 14"},"assignee":{"displayName":"A. Rivera"},"priority":{"name":"High"}}},{"key":"PHX-113","fields":{"summary":"Usage analytics dashboard","status":{"name":"In Progress"},"created":"2026-06-08T09:00:00.000+0000","customfield_10016":5,"sprint":{"name":"Sprint 14"},"assignee":{"displayName":"D. Weiss"},"priority":{"name":"Medium"}}},{"key":"PHX-114","fields":{"summary":"Legacy importer deprecation","status":{"name":"To Do"},"created":"2026-06-09T09:00:00.000+0000","customfield_10016":3,"sprint":{"name":"Sprint 14"},"assignee":{"displayName":"B. Okafor"},"priority":{"name":"Low"}}}]},"isInternal":false,"tokens":1678,"sizeBytes":4586},{"name":"agentic_delivery_governance.md","path":"project-management/skills/pm-skills/references/agentic_delivery_governance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/pm-skills/references/agentic_delivery_governance.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fpm-skills%2Freferences%2Fagentic_delivery_governance.md -->","isInternal":false,"tokens":1011,"sizeBytes":4281},{"name":"flow_forecasting_canon.md","path":"project-management/skills/pm-skills/references/flow_forecasting_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/pm-skills/references/flow_forecasting_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fpm-skills%2Freferences%2Fflow_forecasting_canon.md -->","isInternal":false,"tokens":1006,"sizeBytes":4029},{"name":"pm_loop_playbook.md","path":"project-management/skills/pm-skills/references/pm_loop_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/pm-skills/references/pm_loop_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fpm-skills%2Freferences%2Fpm_loop_playbook.md -->","isInternal":false,"tokens":1186,"sizeBytes":4777},{"name":"SKILL.md","path":"project-management/skills/pm-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/pm-skills/SKILL.md","title":"pm-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fpm-skills%2FSKILL.md -->","frontmatter":{"name":"pm-skills","description":"Use when coordinating project-delivery work across the 8 project-management sub-skills — sprint/velocity analytics, portfolio health, Jira/JQL, Confluence, Atlassian admin, templates, meeting analysis, team comms. Triggers on 'our sprints feel off', 'project health report', 'audit our Jira permissions', 'when will it be done', 'run the delivery loop'. Forks context to route to one sub-skill via a deterministic signal router and returns a digest; can also drive a full goal→plan→execute→verify→close delivery loop through the repo-wide agent-harness with Jira MCP data bridged into the domain's analytics tools. Distinct from product-team (what to build vs how to deliver it), business-operations (internal ops), and engineering/agent-harness (the generic loop engine this orchestrator plugs into).","context":"fork","license":"MIT","metadata":{"version":"2.11.1","author":"Alireza Rezvani","tags":["project-management","orchestrator","jira","confluence","atlassian","scrum","agile","flow-metrics","agent-harness"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2566,"sizeBytes":10430},{"name":"expected_output.json","path":"project-management/skills/scrum-master/assets/expected_output.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/scrum-master/assets/expected_output.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fscrum-master%2Fassets%2Fexpected_output.json -->","frontmatter":{"velocity_analysis":{"summary":{"total_sprints":6,"velocity_stats":{"mean":20.17,"median":20,"min":17,"max":24,"total_points":121},"commitment_analysis":{"average_commitment_ratio":0.908,"commitment_consistency":0.179,"sprints_under_committed":3,"sprints_over_committed":2},"volatility":{"volatility":"low","coefficient_of_variation":0.127}},"trend_analysis":{"trend":"stable","confidence":0.15,"relative_slope":-0.013},"forecasting":{"expected_total":121,"forecasted_totals":{"50%":115,"70%":125,"85%":135,"95%":148}},"anomalies":[{"sprint_number":5,"velocity":17,"anomaly_type":"outlier","deviation_percentage":-15.7}]},"sprint_health":{"overall_score":78.3,"health_grade":"good","dimension_scores":{"commitment_reliability":{"score":96.8,"grade":"excellent"},"scope_stability":{"score":54.8,"grade":"poor"},"blocker_resolution":{"score":51.7,"grade":"poor"},"ceremony_engagement":{"score":92.3,"grade":"excellent"},"story_completion_distribution":{"score":93.3,"grade":"excellent"},"velocity_predictability":{"score":80.5,"grade":"good"}}},"retrospective_analysis":{"summary":{"total_retrospectives":6,"average_duration":74,"average_attendance":0.933},"action_item_analysis":{"total_action_items":15,"completion_rate":0.467,"overdue_rate":0.533,"priority_analysis":{"high":{"completion_rate":0.5},"medium":{"completion_rate":0.33},"low":{"completion_rate":0.67}}},"theme_analysis":{"recurring_themes":{"process":{"frequency":1,"trend":{"direction":"decreasing"}},"team_dynamics":{"frequency":1,"trend":{"direction":"increasing"}},"technical":{"frequency":0.83,"trend":{"direction":"increasing"}},"communication":{"frequency":0.67,"trend":{"direction":"decreasing"}}}},"improvement_trends":{"team_maturity_score":{"score":75.6,"level":"performing"},"improvement_velocity":{"velocity":"moderate","velocity_score":0.62}}},"interpretation":{"strengths":["Excellent commitment reliability - team consistently delivers what they commit to","High ceremony engagement - team actively participates in scrum events","Good story completion distribution - stories are finished rather than left partially done","Low velocity volatility - predictable delivery capability"],"areas_for_improvement":["Scope instability - too much mid-sprint change (22.6% average)","Blocker resolution time - 4.7 days average is too long","Action item completion rate - only 46.7% completed","High overdue rate - 53.3% of action items become overdue"],"recommended_actions":["Strengthen backlog refinement to reduce scope changes","Implement faster blocker escalation process","Reduce number of retrospective action items and focus on follow-through","Create external dependency register to proactively manage blockers"]}},"isInternal":false,"tokens":1007,"sizeBytes":3710},{"name":"expected_velocity_output.json","path":"project-management/skills/scrum-master/assets/expected_velocity_output.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/scrum-master/assets/expected_velocity_output.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fscrum-master%2Fassets%2Fexpected_velocity_output.json -->","frontmatter":{"summary":{"total_sprints":6,"velocity_stats":{"mean":20.166666666666668,"median":20,"min":17,"max":24,"total_points":121},"commitment_analysis":{"average_commitment_ratio":0.9075307422046552,"commitment_consistency":0.17889820455801825,"sprints_under_committed":3,"sprints_over_committed":2},"scope_change_analysis":{"average_scope_change":0.22586752619361317,"scope_change_volatility":0.1828476660567787},"rolling_averages":{"3":[null,null,19.333333333333332,20.666666666666668,19.333333333333332,21],"5":[null,null,19.333333333333332,20,19.4,20.6],"8":[null,null,19.333333333333332,20,19.4,20.166666666666668]},"volatility":{"volatility":"low","coefficient_of_variation":0.13088153980052333,"standard_deviation":2.6394443859772205,"mean_velocity":20.166666666666668,"velocity_range":7,"range_ratio":0.3471074380165289,"min_velocity":17,"max_velocity":24}},"trend_analysis":{"trend":"stable","slope":0.6,"relative_slope":0.029752066115702476,"correlation":0.42527784332026836,"confidence":0.42527784332026836,"recent_sprints_analyzed":6,"average_velocity":20.166666666666668},"forecasting":{"sprints_ahead":6,"historical_sprints_used":6,"mean_velocity":20.166666666666668,"velocity_std_dev":2.6394443859772205,"forecasted_totals":{"50%":121.00756172377734,"70%":124.35398229685968,"85%":127.68925669583572,"95%":131.66775744677182},"average_per_sprint":20.166666666666668,"expected_total":121},"anomalies":[],"recommendations":["Good velocity stability. Continue current practices."]},"isInternal":false,"tokens":694,"sizeBytes":2077},{"name":"sample_sprint_data.json","path":"project-management/skills/scrum-master/assets/sample_sprint_data.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/scrum-master/assets/sample_sprint_data.json","title":"Assets Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fscrum-master%2Fassets%2Fsample_sprint_data.json -->","frontmatter":{"team_info":{"name":"Phoenix Development Team","size":5,"scrum_master":"Sarah Chen","product_owner":"Mike Rodriguez"},"sprints":[{"sprint_number":1,"sprint_name":"Sprint Alpha","start_date":"2024-01-08","end_date":"2024-01-19","planned_points":23,"completed_points":18,"added_points":3,"removed_points":2,"carry_over_points":5,"team_capacity":40,"working_days":10,"team_size":5,"stories":[{"id":"US-101","title":"User authentication system","points":8,"status":"completed","assigned_to":"John Doe","created_date":"2024-01-08","completed_date":"2024-01-16","blocked_days":0,"priority":"high"},{"id":"US-102","title":"Dashboard layout implementation","points":5,"status":"completed","assigned_to":"Jane Smith","created_date":"2024-01-08","completed_date":"2024-01-18","blocked_days":1,"priority":"medium"},{"id":"US-103","title":"API integration for user data","points":5,"status":"completed","assigned_to":"Bob Wilson","created_date":"2024-01-08","completed_date":"2024-01-19","blocked_days":0,"priority":"medium"},{"id":"US-104","title":"Advanced filtering options","points":5,"status":"in_progress","assigned_to":"Alice 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Developer","department":"Engineering","hourly_rate":95,"available_hours":40,"current_utilization":0.85,"skills":["react","node_js","typescript","aws"],"current_projects":["PROJ001","PROJ004"],"capacity_notes":"Strong full-stack capabilities"},{"id":"RES005","name":"Lisa Thompson","role":"ML Engineer","department":"Data Science","hourly_rate":115,"available_hours":40,"current_utilization":0.7,"skills":["python","tensorflow","data_pipelines","mlops"],"current_projects":["PROJ003"],"capacity_notes":"Available for additional ML initiatives"},{"id":"RES006","name":"Ahmed Hassan","role":"Solution Architect","department":"Engineering","hourly_rate":125,"available_hours":40,"current_utilization":0.95,"skills":["enterprise_architecture","cloud_strategy","security"],"current_projects":["PROJ002"],"capacity_notes":"Critical resource for architectural decisions"}],"risks":[{"id":"RISK001","title":"Third-party API dependency for mobile banking app","description":"Banking app relies on external 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Hassan","project_id":"PROJ001","created_date":"2024-12-15","target_resolution":"2025-04-30","mitigation_actions":["Engage legal and compliance teams early","Build regulatory requirements into technical design","Plan for additional security audit phase"],"impact_areas":["timeline","scope","budget"],"severity":"medium"},{"id":"RISK005","title":"Integration complexity with legacy systems","description":"Cloud migration may face unexpected integration challenges with legacy on-premise systems","category":"technical","probability":2,"impact":2,"status":"mitigated","owner":"Ahmed Hassan","project_id":"PROJ002","created_date":"2024-09-01","target_resolution":"2024-12-31","mitigation_actions":["Complete comprehensive system mapping and API inventory","Create detailed integration test suite","Establish rollback procedures for each integration phase"],"impact_areas":["timeline","quality"],"severity":"low"},{"id":"RISK006","title":"Data privacy requirements for analytics 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Specializes in portfolio management, quantitative risk analysis, resource optimization, stakeholder alignment, and executive reporting. Uses advanced methodologies including EMV analysis, Monte Carlo simulation, WSJF prioritization, and multi-dimensional health scoring. Use when a user needs help with project plans, project status reports, risk assessments, resource allocation, project roadmaps, milestone tracking, team capacity planning, portfolio health reviews, program management, or executive-level project reporting — especially for enterprise-scale initiatives with multiple workstreams, complex dependencies, or multi-million dollar budgets."},"isInternal":false,"tokens":3354,"sizeBytes":16595},{"name":"3p-updates.md","path":"project-management/skills/team-communications/references/3p-updates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/team-communications/references/3p-updates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fteam-communications%2Freferences%2F3p-updates.md -->","isInternal":false,"tokens":741,"sizeBytes":3274},{"name":"company-newsletter.md","path":"project-management/skills/team-communications/references/company-newsletter.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/team-communications/references/company-newsletter.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fteam-communications%2Freferences%2Fcompany-newsletter.md -->","isInternal":false,"tokens":753,"sizeBytes":3295},{"name":"faq-answers.md","path":"project-management/skills/team-communications/references/faq-answers.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/team-communications/references/faq-answers.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fteam-communications%2Freferences%2Ffaq-answers.md -->","isInternal":false,"tokens":476,"sizeBytes":2366},{"name":"general-comms.md","path":"project-management/skills/team-communications/references/general-comms.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/team-communications/references/general-comms.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fteam-communications%2Freferences%2Fgeneral-comms.md -->","isInternal":false,"tokens":133,"sizeBytes":602},{"name":"SKILL.md","path":"project-management/skills/team-communications/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/skills/team-communications/SKILL.md","title":"team-communications","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2Fskills%2Fteam-communications%2FSKILL.md -->","frontmatter":{"name":"team-communications","description":"Write internal company communications — 3P updates (Progress/Plans/Problems), company-wide newsletters, FAQ roundups, incident reports, leadership updates, status reports, project updates, and general internal comms. Use this skill any time the user asks to draft, edit, or format something meant for internal audiences. Trigger on keywords like \"3P\", \"weekly update\", \"newsletter\", \"FAQ\", \"internal comms\", \"status report\", \"company update\", \"team update\", \"incident report\", or any request to summarize work for leadership, teammates, or the broader company. Even casual requests like \"write my update\" or \"summarize what my team did this week\" should trigger this skill."},"isInternal":false,"tokens":971,"sizeBytes":4422},{"name":"cross_framework_mapping_ai_act.md","path":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/cross_framework_mapping_ai_act.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/cross_framework_mapping_ai_act.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2Fskills%2Feu-ai-act-specialist%2Freferences%2Fcross_framework_mapping_ai_act.md -->","isInternal":false,"tokens":2835,"sizeBytes":11031},{"name":"eu_ai_act_titles.md","path":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/eu_ai_act_titles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/eu_ai_act_titles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2Fskills%2Feu-ai-act-specialist%2Freferences%2Feu_ai_act_titles.md -->","isInternal":false,"tokens":2678,"sizeBytes":11129},{"name":"gpai_obligations.md","path":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/gpai_obligations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/gpai_obligations.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2Fskills%2Feu-ai-act-specialist%2Freferences%2Fgpai_obligations.md -->","isInternal":false,"tokens":1664,"sizeBytes":7511},{"name":"high_risk_systems_annex_iii.md","path":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/high_risk_systems_annex_iii.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/references/high_risk_systems_annex_iii.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2Fskills%2Feu-ai-act-specialist%2Freferences%2Fhigh_risk_systems_annex_iii.md -->","isInternal":false,"tokens":1713,"sizeBytes":7955},{"name":"SKILL.md","path":"ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-eu-ai-act/skills/eu-ai-act-specialist/SKILL.md","title":"eu-ai-act-specialist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2Fskills%2Feu-ai-act-specialist%2FSKILL.md -->","frontmatter":{"name":"eu-ai-act-specialist","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and deadlines? Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations. Cites Articles + Annexes for every output. NOT executive AI strategy (see chief-ai-officer-advisor). NOT a legal substitute.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"ra-qm-team","domain":"eu-ai-act-compliance","updated":"2026-05-13","python-tools":"ai_system_risk_classifier.py, conformity_assessment_planner.py, ai_act_obligation_tracker.py","frameworks":"eu-ai-act, gdpr-overlap, iso-42001-mapping, nist-ai-rmf-mapping"}},"isInternal":false,"tokens":3584,"sizeBytes":15172},{"name":"aims_controls_annex_a.md","path":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/aims_controls_annex_a.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/aims_controls_annex_a.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-iso42001%2Fskills%2Fiso42001-specialist%2Freferences%2Faims_controls_annex_a.md -->","isInternal":false,"tokens":2632,"sizeBytes":10022},{"name":"aims_implementation_guide.md","path":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/aims_implementation_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/aims_implementation_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-iso42001%2Fskills%2Fiso42001-specialist%2Freferences%2Faims_implementation_guide.md -->","isInternal":false,"tokens":2145,"sizeBytes":8548},{"name":"cross_framework_mapping_ai.md","path":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/cross_framework_mapping_ai.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/cross_framework_mapping_ai.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-iso42001%2Fskills%2Fiso42001-specialist%2Freferences%2Fcross_framework_mapping_ai.md -->","isInternal":false,"tokens":2922,"sizeBytes":9113},{"name":"iso42001_clauses.md","path":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/iso42001_clauses.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/references/iso42001_clauses.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-iso42001%2Fskills%2Fiso42001-specialist%2Freferences%2Fiso42001_clauses.md -->","isInternal":false,"tokens":2106,"sizeBytes":9091},{"name":"SKILL.md","path":"ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-iso42001/skills/iso42001-specialist/SKILL.md","title":"iso42001-specialist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-iso42001%2Fskills%2Fiso42001-specialist%2FSKILL.md -->","frontmatter":{"name":"iso42001-specialist","description":"ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see compliance-team-eu-ai-act).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"ra-qm-team","domain":"ai-management-system-compliance","updated":"2026-05-13","python-tools":"aims_gap_analyzer.py, ai_risk_register_builder.py, aims_audit_scheduler.py","frameworks":"iso-42001, iso-23894, iso-38507, nist-ai-rmf, eu-ai-act-mapping"}},"isInternal":false,"tokens":3481,"sizeBytes":13921},{"name":"receipt-fields.md","path":"ra-qm-team/skills/agent-decision-receipts/references/receipt-fields.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/agent-decision-receipts/references/receipt-fields.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fagent-decision-receipts%2Freferences%2Freceipt-fields.md -->","isInternal":false,"tokens":1174,"sizeBytes":4623},{"name":"SKILL.md","path":"ra-qm-team/skills/agent-decision-receipts/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/agent-decision-receipts/SKILL.md","title":"agent-decision-receipts","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fagent-decision-receipts%2FSKILL.md -->","frontmatter":{"name":"agent-decision-receipts","description":"Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion."},"isInternal":false,"tokens":1931,"sizeBytes":7939},{"name":"effectiveness-verification-guide.md","path":"ra-qm-team/skills/capa-officer/references/effectiveness-verification-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/capa-officer/references/effectiveness-verification-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fcapa-officer%2Freferences%2Feffectiveness-verification-guide.md -->","isInternal":false,"tokens":3083,"sizeBytes":13611},{"name":"rca-methodologies.md","path":"ra-qm-team/skills/capa-officer/references/rca-methodologies.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/capa-officer/references/rca-methodologies.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fcapa-officer%2Freferences%2Frca-methodologies.md -->","isInternal":false,"tokens":3777,"sizeBytes":15808},{"name":"SKILL.md","path":"ra-qm-team/skills/capa-officer/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/capa-officer/SKILL.md","title":"capa-officer","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fcapa-officer%2FSKILL.md -->","frontmatter":{"name":"capa-officer","description":"CAPA system management for medical device QMS. Covers root cause analysis, corrective action planning, effectiveness verification, and CAPA metrics. Use when running CAPA investigations, 5-Why analysis, fishbone diagrams, root cause determination, corrective action tracking, effectiveness verification, or CAPA program optimization.","metadata":{"triggers":["CAPA investigation","root cause analysis","5 Why analysis","fishbone diagram","corrective action","preventive action","effectiveness verification","CAPA metrics","nonconformance investigation","quality issue investigation","CAPA tracking","audit finding CAPA"]}},"isInternal":false,"tokens":3612,"sizeBytes":16134},{"name":"cross_framework_mapping_ai_act.md","path":"ra-qm-team/skills/eu-ai-act-specialist/references/cross_framework_mapping_ai_act.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/eu-ai-act-specialist/references/cross_framework_mapping_ai_act.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Feu-ai-act-specialist%2Freferences%2Fcross_framework_mapping_ai_act.md -->","isInternal":false,"tokens":2835,"sizeBytes":11031},{"name":"eu_ai_act_titles.md","path":"ra-qm-team/skills/eu-ai-act-specialist/references/eu_ai_act_titles.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/eu-ai-act-specialist/references/eu_ai_act_titles.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Feu-ai-act-specialist%2Freferences%2Feu_ai_act_titles.md -->","isInternal":false,"tokens":2678,"sizeBytes":11129},{"name":"gpai_obligations.md","path":"ra-qm-team/skills/eu-ai-act-specialist/references/gpai_obligations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/eu-ai-act-specialist/references/gpai_obligations.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Feu-ai-act-specialist%2Freferences%2Fgpai_obligations.md -->","isInternal":false,"tokens":1664,"sizeBytes":7511},{"name":"high_risk_systems_annex_iii.md","path":"ra-qm-team/skills/eu-ai-act-specialist/references/high_risk_systems_annex_iii.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/eu-ai-act-specialist/references/high_risk_systems_annex_iii.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Feu-ai-act-specialist%2Freferences%2Fhigh_risk_systems_annex_iii.md -->","isInternal":false,"tokens":1713,"sizeBytes":7955},{"name":"SKILL.md","path":"ra-qm-team/skills/eu-ai-act-specialist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/eu-ai-act-specialist/SKILL.md","title":"eu-ai-act-specialist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Feu-ai-act-specialist%2FSKILL.md -->","frontmatter":{"name":"eu-ai-act-specialist","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and deadlines? Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations. Cites Articles + Annexes for every output. NOT executive AI strategy (see chief-ai-officer-advisor). NOT a legal substitute.","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"ra-qm-team","domain":"eu-ai-act-compliance","updated":"2026-05-13","python-tools":"ai_system_risk_classifier.py, conformity_assessment_planner.py, ai_act_obligation_tracker.py","frameworks":"eu-ai-act, gdpr-overlap, iso-42001-mapping, nist-ai-rmf-mapping"}},"isInternal":false,"tokens":3584,"sizeBytes":15172},{"name":"device_cybersecurity_guidance.md","path":"ra-qm-team/skills/fda-consultant-specialist/references/device_cybersecurity_guidance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/fda-consultant-specialist/references/device_cybersecurity_guidance.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Ffda-consultant-specialist%2Freferences%2Fdevice_cybersecurity_guidance.md -->","isInternal":false,"tokens":4330,"sizeBytes":18342},{"name":"fda_capa_requirements.md","path":"ra-qm-team/skills/fda-consultant-specialist/references/fda_capa_requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/fda-consultant-specialist/references/fda_capa_requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Ffda-consultant-specialist%2Freferences%2Ffda_capa_requirements.md -->","isInternal":false,"tokens":4540,"sizeBytes":22415},{"name":"fda_submission_guide.md","path":"ra-qm-team/skills/fda-consultant-specialist/references/fda_submission_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/fda-consultant-specialist/references/fda_submission_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Ffda-consultant-specialist%2Freferences%2Ffda_submission_guide.md -->","isInternal":false,"tokens":2591,"sizeBytes":11793},{"name":"hipaa_compliance_framework.md","path":"ra-qm-team/skills/fda-consultant-specialist/references/hipaa_compliance_framework.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/fda-consultant-specialist/references/hipaa_compliance_framework.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Ffda-consultant-specialist%2Freferences%2Fhipaa_compliance_framework.md -->","isInternal":false,"tokens":4387,"sizeBytes":19254},{"name":"qsr_compliance_requirements.md","path":"ra-qm-team/skills/fda-consultant-specialist/references/qsr_compliance_requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/fda-consultant-specialist/references/qsr_compliance_requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Ffda-consultant-specialist%2Freferences%2Fqsr_compliance_requirements.md -->","isInternal":false,"tokens":5133,"sizeBytes":21839},{"name":"SKILL.md","path":"ra-qm-team/skills/fda-consultant-specialist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/fda-consultant-specialist/SKILL.md","title":"fda-consultant-specialist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Ffda-consultant-specialist%2FSKILL.md -->","frontmatter":{"name":"fda-consultant-specialist","description":"FDA regulatory consultant for medical device companies. Provides 510(k)/PMA/De Novo pathway guidance, QMSR (21 CFR 820, which incorporates ISO 13485:2016 by reference since 2026-02-02; formerly QSR) compliance, HIPAA assessments, and device cybersecurity. Use when user mentions FDA submission, 510(k), PMA, De Novo, QMSR, QSR, ISO 13485 for FDA, premarket, predicate device, substantial equivalence, HIPAA medical device, or FDA cybersecurity."},"isInternal":false,"tokens":2930,"sizeBytes":12111},{"name":"dpia_methodology.md","path":"ra-qm-team/skills/gdpr-dsgvo-expert/references/dpia_methodology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/gdpr-dsgvo-expert/references/dpia_methodology.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fgdpr-dsgvo-expert%2Freferences%2Fdpia_methodology.md -->","isInternal":false,"tokens":2561,"sizeBytes":10999},{"name":"gdpr_audit_playbook.md","path":"ra-qm-team/skills/gdpr-dsgvo-expert/references/gdpr_audit_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/gdpr-dsgvo-expert/references/gdpr_audit_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fgdpr-dsgvo-expert%2Freferences%2Fgdpr_audit_playbook.md -->","isInternal":false,"tokens":2527,"sizeBytes":10677},{"name":"gdpr_compliance_guide.md","path":"ra-qm-team/skills/gdpr-dsgvo-expert/references/gdpr_compliance_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/gdpr-dsgvo-expert/references/gdpr_compliance_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fgdpr-dsgvo-expert%2Freferences%2Fgdpr_compliance_guide.md -->","isInternal":false,"tokens":2025,"sizeBytes":9114},{"name":"german_bdsg_requirements.md","path":"ra-qm-team/skills/gdpr-dsgvo-expert/references/german_bdsg_requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/gdpr-dsgvo-expert/references/german_bdsg_requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fgdpr-dsgvo-expert%2Freferences%2Fgerman_bdsg_requirements.md -->","isInternal":false,"tokens":2118,"sizeBytes":8866},{"name":"SKILL.md","path":"ra-qm-team/skills/gdpr-dsgvo-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/gdpr-dsgvo-expert/SKILL.md","title":"gdpr-dsgvo-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fgdpr-dsgvo-expert%2FSKILL.md -->","frontmatter":{"name":"gdpr-dsgvo-expert","description":"GDPR and German DSGVO compliance automation. Scans codebases for privacy risks, generates DPIA documentation, tracks data subject rights requests with Art. 12(3) one-month deadlines. Use when running GDPR compliance assessments, privacy audits, data protection planning, DPIA generation, or data subject rights (DSAR) management (e.g., 'check this service for GDPR risks', 'track an access request deadline'). Final compliance determinations route to the DPO or legal counsel."},"isInternal":false,"tokens":1969,"sizeBytes":8487},{"name":"incident-response.md","path":"ra-qm-team/skills/information-security-manager-iso27001/references/incident-response.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/information-security-manager-iso27001/references/incident-response.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Finformation-security-manager-iso27001%2Freferences%2Fincident-response.md -->","isInternal":false,"tokens":2562,"sizeBytes":11273},{"name":"iso27001-controls.md","path":"ra-qm-team/skills/information-security-manager-iso27001/references/iso27001-controls.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/information-security-manager-iso27001/references/iso27001-controls.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Finformation-security-manager-iso27001%2Freferences%2Fiso27001-controls.md -->","isInternal":false,"tokens":2078,"sizeBytes":9667},{"name":"risk-assessment-guide.md","path":"ra-qm-team/skills/information-security-manager-iso27001/references/risk-assessment-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/information-security-manager-iso27001/references/risk-assessment-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Finformation-security-manager-iso27001%2Freferences%2Frisk-assessment-guide.md -->","isInternal":false,"tokens":2121,"sizeBytes":8440},{"name":"SKILL.md","path":"ra-qm-team/skills/information-security-manager-iso27001/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/information-security-manager-iso27001/SKILL.md","title":"information-security-manager-iso27001","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Finformation-security-manager-iso27001%2FSKILL.md -->","frontmatter":{"name":"information-security-manager-iso27001","description":"ISO 27001 ISMS implementation and cybersecurity governance for HealthTech and MedTech companies. Use when designing an ISMS, running security risk assessments, implementing controls, pursuing ISO 27001 certification, preparing security audits, responding to security incidents, or verifying compliance. 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NOT EU AI Act compliance (see compliance-team-eu-ai-act).","license":"MIT","metadata":{"version":"1.0.0","author":"Alireza Rezvani","category":"ra-qm-team","domain":"ai-management-system-compliance","updated":"2026-05-13","python-tools":"aims_gap_analyzer.py, ai_risk_register_builder.py, aims_audit_scheduler.py","frameworks":"iso-42001, iso-23894, iso-38507, nist-ai-rmf, eu-ai-act-mapping"}},"isInternal":false,"tokens":3481,"sizeBytes":13921},{"name":"clinical-evidence-requirements.md","path":"ra-qm-team/skills/mdr-745-specialist/references/clinical-evidence-requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/mdr-745-specialist/references/clinical-evidence-requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fmdr-745-specialist%2Freferences%2Fclinical-evidence-requirements.md -->","isInternal":false,"tokens":1996,"sizeBytes":9408},{"name":"mdr-classification-guide.md","path":"ra-qm-team/skills/mdr-745-specialist/references/mdr-classification-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/mdr-745-specialist/references/mdr-classification-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fmdr-745-specialist%2Freferences%2Fmdr-classification-guide.md -->","isInternal":false,"tokens":2178,"sizeBytes":8948},{"name":"technical-documentation-templates.md","path":"ra-qm-team/skills/mdr-745-specialist/references/technical-documentation-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/mdr-745-specialist/references/technical-documentation-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fmdr-745-specialist%2Freferences%2Ftechnical-documentation-templates.md -->","isInternal":false,"tokens":2312,"sizeBytes":10364},{"name":"SKILL.md","path":"ra-qm-team/skills/mdr-745-specialist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/mdr-745-specialist/SKILL.md","title":"mdr-745-specialist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fmdr-745-specialist%2FSKILL.md -->","frontmatter":{"name":"mdr-745-specialist","description":"EU MDR 2017/745 compliance specialist for medical device classification, technical documentation, clinical evidence, and post-market surveillance. Covers Annex VIII classification rules, Annex II/III technical files, Annex XIV clinical evaluation, Art. 86 PSUR schedules, and EUDAMED integration. Use when classifying a medical device under MDR, building or gap-checking a technical file, planning clinical evaluation or PMS/PSUR cadence, or preparing for notified body review (e.g., 'what class is my device under MDR', 'review my PSUR schedule').","metadata":{"triggers":["MDR compliance","EU MDR","medical device classification","Annex VIII","technical documentation","clinical evaluation","PMCF","EUDAMED","UDI","notified body"]}},"isInternal":false,"tokens":2430,"sizeBytes":10438},{"name":"iso13485_audit_playbook.md","path":"ra-qm-team/skills/qms-audit-expert/references/iso13485_audit_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/qms-audit-expert/references/iso13485_audit_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fqms-audit-expert%2Freferences%2Fiso13485_audit_playbook.md -->","isInternal":false,"tokens":2519,"sizeBytes":10164},{"name":"iso13485-audit-guide.md","path":"ra-qm-team/skills/qms-audit-expert/references/iso13485-audit-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/qms-audit-expert/references/iso13485-audit-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fqms-audit-expert%2Freferences%2Fiso13485-audit-guide.md -->","isInternal":false,"tokens":2437,"sizeBytes":10936},{"name":"nonconformity-classification.md","path":"ra-qm-team/skills/qms-audit-expert/references/nonconformity-classification.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/qms-audit-expert/references/nonconformity-classification.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fqms-audit-expert%2Freferences%2Fnonconformity-classification.md -->","isInternal":false,"tokens":1531,"sizeBytes":6894},{"name":"SKILL.md","path":"ra-qm-team/skills/qms-audit-expert/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/qms-audit-expert/SKILL.md","title":"qms-audit-expert","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fqms-audit-expert%2FSKILL.md -->","frontmatter":{"name":"qms-audit-expert","description":"ISO 13485 internal audit expertise for medical device QMS. 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Provides quality system governance, management review leadership, regulatory compliance oversight, and quality performance monitoring per ISO 13485 Clause 5.5.2. Use when leading management reviews, setting quality policy and objectives, monitoring quality KPIs and cost of quality, or exercising QMR governance and regulatory oversight responsibilities.","metadata":{"triggers":["management review","quality policy","quality objectives","QMR responsibilities","quality system effectiveness","quality KPIs","cost of quality","quality performance","management accountability","regulatory oversight","quality culture","quality governance"]}},"isInternal":false,"tokens":4031,"sizeBytes":18747},{"name":"iso13485-clause-requirements.md","path":"ra-qm-team/skills/quality-manager-qms-iso13485/references/iso13485-clause-requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/quality-manager-qms-iso13485/references/iso13485-clause-requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fquality-manager-qms-iso13485%2Freferences%2Fiso13485-clause-requirements.md -->","isInternal":false,"tokens":5178,"sizeBytes":23690},{"name":"qms-process-templates.md","path":"ra-qm-team/skills/quality-manager-qms-iso13485/references/qms-process-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/quality-manager-qms-iso13485/references/qms-process-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fquality-manager-qms-iso13485%2Freferences%2Fqms-process-templates.md -->","isInternal":false,"tokens":5505,"sizeBytes":19951},{"name":"SKILL.md","path":"ra-qm-team/skills/quality-manager-qms-iso13485/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/quality-manager-qms-iso13485/SKILL.md","title":"quality-manager-qms-iso13485","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fquality-manager-qms-iso13485%2FSKILL.md -->","frontmatter":{"name":"quality-manager-qms-iso13485","description":"ISO 13485 Quality Management System implementation and maintenance for medical device organizations. Provides QMS design, documentation control, internal auditing, CAPA management, and certification support. Use when working with medical device quality systems, preparing for ISO 13485 audits, managing regulatory compliance documentation, setting up corrective actions, or building audit preparation programs. Useful for quality management, audit preparation, regulatory compliance, medical device documentation, and corrective action workflows.","metadata":{"triggers":["ISO 13485","QMS implementation","quality management system","document control","internal audit","management review","quality manual","CAPA process","process validation","design control","supplier qualification","quality records"]}},"isInternal":false,"tokens":4097,"sizeBytes":17907},{"name":"SKILL.md","path":"ra-qm-team/skills/ra-qm-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/ra-qm-skills/SKILL.md","title":"ra-qm-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fra-qm-skills%2FSKILL.md -->","frontmatter":{"name":"ra-qm-skills","description":"Router/index for the 15 regulatory & quality-management skills bundled in this plugin (ISO 13485 QMS, EU MDR 2017/745, FDA submissions under QMSR, ISO 14971 risk, CAPA, document control, ISO 27001/ISMS, ISO 42001 AIMS, EU AI Act, GDPR/DSGVO, SOC 2, auditing). Use when a compliance request doesn't obviously match one skill and you need to pick the right one (e.g., 'prepare us for an ISO 13485 audit', 'is my AI system high-risk under the AI Act').","license":"MIT","metadata":{"version":"2.9.0","author":"Alireza Rezvani","tags":["regulatory","quality-management","iso-13485","mdr","fda","iso-27001","gdpr"],"agents":["claude-code","codex-cli","openclaw"]}},"isInternal":false,"tokens":935,"sizeBytes":3372},{"name":"eu-mdr-submission-guide.md","path":"ra-qm-team/skills/regulatory-affairs-head/references/eu-mdr-submission-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/regulatory-affairs-head/references/eu-mdr-submission-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fregulatory-affairs-head%2Freferences%2Feu-mdr-submission-guide.md -->","isInternal":false,"tokens":709,"sizeBytes":3272},{"name":"fda-submission-guide.md","path":"ra-qm-team/skills/regulatory-affairs-head/references/fda-submission-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/regulatory-affairs-head/references/fda-submission-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fregulatory-affairs-head%2Freferences%2Ffda-submission-guide.md -->","isInternal":false,"tokens":1001,"sizeBytes":4442},{"name":"global-regulatory-pathways.md","path":"ra-qm-team/skills/regulatory-affairs-head/references/global-regulatory-pathways.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/regulatory-affairs-head/references/global-regulatory-pathways.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fregulatory-affairs-head%2Freferences%2Fglobal-regulatory-pathways.md -->","isInternal":false,"tokens":2241,"sizeBytes":9806},{"name":"iso-regulatory-requirements.md","path":"ra-qm-team/skills/regulatory-affairs-head/references/iso-regulatory-requirements.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/regulatory-affairs-head/references/iso-regulatory-requirements.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fregulatory-affairs-head%2Freferences%2Fiso-regulatory-requirements.md -->","isInternal":false,"tokens":3195,"sizeBytes":14171},{"name":"SKILL.md","path":"ra-qm-team/skills/regulatory-affairs-head/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/regulatory-affairs-head/SKILL.md","title":"regulatory-affairs-head","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fregulatory-affairs-head%2FSKILL.md -->","frontmatter":{"name":"regulatory-affairs-head","description":"Senior Regulatory Affairs Manager for HealthTech and MedTech companies. Prepares FDA 510(k), De Novo, and PMA submission packages; analyzes regulatory pathways for new medical devices; drafts responses to FDA deficiency letters and Notified Body queries; develops CE marking technical documentation under EU MDR 2017/745; coordinates multi-market approval strategies across FDA, EU, Health Canada, PMDA, and NMPA; and maintains regulatory intelligence on evolving standards. Use when users need to plan or execute FDA submissions, navigate 510(k) or PMA approval processes, achieve CE marking, prepare pre-submission meeting materials, write regulatory strategy documents, respond to agency queries, or manage compliance documentation for medical device market access.","metadata":{"triggers":["regulatory strategy","FDA submission","EU MDR","510(k)","PMA approval","CE marking","regulatory pathway","market access","clinical evidence","regulatory intelligence","submission planning","notified body"]}},"isInternal":false,"tokens":4713,"sizeBytes":20232},{"name":"iso14971-implementation-guide.md","path":"ra-qm-team/skills/risk-management-specialist/references/iso14971-implementation-guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/risk-management-specialist/references/iso14971-implementation-guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Frisk-management-specialist%2Freferences%2Fiso14971-implementation-guide.md -->","isInternal":false,"tokens":3632,"sizeBytes":15551},{"name":"risk-analysis-methods.md","path":"ra-qm-team/skills/risk-management-specialist/references/risk-analysis-methods.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/risk-management-specialist/references/risk-analysis-methods.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Frisk-management-specialist%2Freferences%2Frisk-analysis-methods.md -->","isInternal":false,"tokens":3173,"sizeBytes":13359},{"name":"risk-assessment-templates.md","path":"ra-qm-team/skills/risk-management-specialist/references/risk-assessment-templates.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/risk-management-specialist/references/risk-assessment-templates.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Frisk-management-specialist%2Freferences%2Frisk-assessment-templates.md -->","isInternal":false,"tokens":595,"sizeBytes":1993},{"name":"SKILL.md","path":"ra-qm-team/skills/risk-management-specialist/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/risk-management-specialist/SKILL.md","title":"risk-management-specialist","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Frisk-management-specialist%2FSKILL.md -->","frontmatter":{"name":"risk-management-specialist","description":"Medical device risk management specialist implementing ISO 14971 throughout product lifecycle. Provides risk analysis, risk evaluation, risk control, and post-production information analysis. Use when user mentions risk management, ISO 14971, risk analysis, FMEA, fault tree analysis, hazard identification, risk control, risk matrix, benefit-risk analysis, residual risk, risk acceptability, or post-market risk."},"isInternal":false,"tokens":3662,"sizeBytes":16844},{"name":"evidence_collection_guide.md","path":"ra-qm-team/skills/soc2-compliance/references/evidence_collection_guide.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/soc2-compliance/references/evidence_collection_guide.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fsoc2-compliance%2Freferences%2Fevidence_collection_guide.md -->","isInternal":false,"tokens":2337,"sizeBytes":11737},{"name":"soc2_audit_playbook.md","path":"ra-qm-team/skills/soc2-compliance/references/soc2_audit_playbook.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/soc2-compliance/references/soc2_audit_playbook.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fsoc2-compliance%2Freferences%2Fsoc2_audit_playbook.md -->","isInternal":false,"tokens":2149,"sizeBytes":9480},{"name":"trust_service_criteria.md","path":"ra-qm-team/skills/soc2-compliance/references/trust_service_criteria.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/soc2-compliance/references/trust_service_criteria.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fsoc2-compliance%2Freferences%2Ftrust_service_criteria.md -->","isInternal":false,"tokens":3670,"sizeBytes":17764},{"name":"type1_vs_type2.md","path":"ra-qm-team/skills/soc2-compliance/references/type1_vs_type2.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/soc2-compliance/references/type1_vs_type2.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fsoc2-compliance%2Freferences%2Ftype1_vs_type2.md -->","isInternal":false,"tokens":2375,"sizeBytes":10465},{"name":"SKILL.md","path":"ra-qm-team/skills/soc2-compliance/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/skills/soc2-compliance/SKILL.md","title":"soc2-compliance","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fskills%2Fsoc2-compliance%2FSKILL.md -->","frontmatter":{"name":"soc2-compliance","description":"Use when the user asks to prepare for SOC 2 audits, map Trust Service Criteria, build control matrices, collect audit evidence, perform gap analysis, or assess SOC 2 Type I vs Type II readiness."},"isInternal":false,"tokens":3991,"sizeBytes":18896},{"name":"protocol_synopsis_template.md","path":"research-ops/skills/clinical-research/assets/protocol_synopsis_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/clinical-research/assets/protocol_synopsis_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2Fassets%2Fprotocol_synopsis_template.md -->","isInternal":false,"tokens":489,"sizeBytes":1950},{"name":"endpoint_and_power.md","path":"research-ops/skills/clinical-research/references/endpoint_and_power.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/clinical-research/references/endpoint_and_power.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2Freferences%2Fendpoint_and_power.md -->","isInternal":false,"tokens":752,"sizeBytes":3110},{"name":"study_design_canon.md","path":"research-ops/skills/clinical-research/references/study_design_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/clinical-research/references/study_design_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2Freferences%2Fstudy_design_canon.md -->","isInternal":false,"tokens":719,"sizeBytes":3078},{"name":"trial_operations.md","path":"research-ops/skills/clinical-research/references/trial_operations.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/clinical-research/references/trial_operations.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2Freferences%2Ftrial_operations.md -->","isInternal":false,"tokens":662,"sizeBytes":2957},{"name":"SKILL.md","path":"research-ops/skills/clinical-research/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/clinical-research/SKILL.md","title":"clinical-research","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fclinical-research%2FSKILL.md -->","frontmatter":{"name":"clinical-research","description":"Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO / GO-WITH-CONDITIONS / REDESIGN / NO-GO phase-gate decision. Every output is an ESTIMATE plus a named human owner (clinician / biostatistician / regulatory owner) — never clinical fact, never a finished protocol. Distinct from ra-qm-team, which handles the regulatory/QM submission (ISO 13485, EU MDR, FDA 510(k)/PMA/QSR), not the study design.","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["research-ops","clinical-research","study-design","endpoint","sample-size","power","phase-gate","biostatistics"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2610,"sizeBytes":10974},{"name":"evals.json","path":"research-ops/skills/interview-mapper/assets/evals/evals.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/assets/evals/evals.json","title":"Evals Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Fassets%2Fevals%2Fevals.json -->","frontmatter":{"skill_name":"interview-mapper","evals":[{"id":1,"prompt":"Here is a transcript of an interview with a museum employee (file transcript.txt). Analyze it — what the role is, the processes, the risks, how they feel about the work. Support every conclusion with a quote.","expected_output":"Mapping via the org-mapping lens: 6 blocks, each cell (of 40 codes) with a verified quote and line number; disputed cells flagged; proofreading log.","files":["fixtures/org-mapping-vmdi/transcript.txt"],"lens":"org-mapping-vmdi","gold":"fixtures/org-mapping-vmdi/gold.md","gold_claims":"fixtures/org-mapping-vmdi/claims.json"},{"id":2,"prompt":"Analyze this custdev interview with a customer — what their problem is, what they've already tried, whether the pain is real. Don't make things up.","expected_output":"Mapping via the CustDev lens: facts vs opinions separated, strength of pain, readiness signals, hypothesis confirmed/refuted; quotes verified; rejected quotes shown.","files":["fixtures/custdev/transcript.txt"],"lens":"custdev","gold":"fixtures/custdev/gold.md","gold_claims":"fixtures/custdev/claims.json"},{"id":3,"prompt":"I already have extracted and clustered observations (nuggets) from 6 interviews — file mappings/nuggets.json. Build cross-interview insights — what's common, where they diverge, what's critical.","expected_output":"Nuggets → clusters → insight cards; each with prevalence (X of N), verified evidence from different interviews, tensions, counter-evidence; a pattern only with triangulation ≥k; watchlist separately. Input mappings/nuggets.json is already structured observations (nuggets in S5/S6 format, cell/quote/line/verified/severity/valence/cluster already assigned), NOT raw interview transcripts; synthesis starts directly at S6.5 (`score_insights.py`), without S1–S4.","files":["fixtures/mappings/nuggets.json"]},{"id":4,"lens":"exit","prompt":"I have a transcript of an exit interview with a lab employee who is resigning — her resignation letter says \"relocating to be with family\", but the conversation turned out to be candid. Analyze what actually happened: where the real point of no return was, what the final straw was, whether she raised the issue with management before, and whether she could have been retained.","expected_output":"Mapping across all Layer 1 cells (X1–X7): the official reason (\"relocation\") diverges from the real one (devaluation of her expertise); the point of no return is the meeting about the reorganization of her position; the trigger is the cut to the reagents budget; prior signals to management went unanswered. Layer 2 concludes PREVENTABLE, flagging the instability of the reason category (A1) and the pattern's systemic nature (A4), plus a recorded self-contradiction from the respondent about when the problems began.","files":["fixtures/exit/transcript.txt"],"gold":"fixtures/exit/gold.md","gold_claims":"fixtures/exit/claims.json"},{"id":5,"lens":"usability","prompt":"I have a transcript of a think-aloud session — a user performing a task in a mobile banking app out loud (file transcript.txt). They need to dispute an unfamiliar charge and lower the limit on online purchases. Analyze where they stumbled, what they expected to see versus what they actually got, and whether they completed the task unaided. Support every conclusion with a quote.","expected_output":"Mapping across the layers of a think-aloud usability session: Layer 1 (U1–U7 — task, first action, sticking points, verbalized mental model, errors/recovery, completion, spontaneous reactions) with verified quotes and line numbers; Layer 2 (A1–A6 — problem type findability/comprehensibility/trust, barrier severity, expectation-reality gap, isolated vs systemic case, fix priority, key insight), unstable analytical cells flagged.","files":["fixtures/usability/transcript.txt"],"gold":"fixtures/usability/gold.md","gold_claims":"fixtures/usability/claims.json"},{"id":6,"lens":"winloss","prompt":"Here is a transcript of an interview with the procurement director of a wholesale company — we recently lost a deal to them on a warehouse inventory system; they chose a competitor. Analyze what actually influenced the choice: who they compared us against, what the decisive moment was, who made the decision, and how truthful the reason the client gave for rejecting us really is.","expected_output":"Mapping via the win/loss interview template: Layer 1 (W1–W7 — outcome, alternatives, criteria, decisive moment, decision-making roles, sales process, price) and Layer 2 (A1–A6 — key differentiator, reason category, sales weak point, reversibility of outcome, credibility of the stated explanation, key insight), each cell with a verified quote and line number; unstable cells flagged as disputed due to the gap between the official and real reason for the loss.","files":["fixtures/winloss/transcript.txt"],"gold":"fixtures/winloss/gold.md","gold_claims":"fixtures/winloss/claims.json"},{"id":7,"lens":"candidate","prompt":"Here is a transcript of an interview for a Senior Backend Developer position on the payments team (file transcript.txt). Assess the candidate — does their experience match the role profile, how verifiable are their cases, how do they explain a past failure. Support every conclusion with a verbatim quote and line number.","expected_output":"Mapping via the candidate interview lens: Layer 1 (K1–K7) — claimed experience, STAR episodes (one strongly verifiable, one weakly verifiable), motivation, expectations of the role, reaction to failure, candidate's questions, conditions — each cell with a verified quote and line number; Layer 2 (A1–A6) — verifiability of episodes, attribution of outcomes, locus of responsibility for failure, and fit with the position, with unstable cells flagged.","files":["fixtures/candidate/transcript.txt"],"gold":"fixtures/candidate/gold.md","gold_claims":"fixtures/candidate/claims.json"},{"id":8,"lens":"focus-group","prompt":"Here is a transcript of a focus group on a new subscription tier for a ready-meal delivery service (file transcript.txt, 5 participants + moderator). Analyze who reacted how, where there was genuine consensus versus where people simply agreed after hearing someone else's opinion, who set the tone of the discussion, and whether there was any real divergence of positions.","expected_output":"Mapping via the focus-group lens (coding unit — utterance+speaker): Layer 1 (G1–G7 — composition, topic, individual positions before group influence, agreement/disagreement map, instances of opinion shift, dominance, spontaneous consensus) and Layer 2 (A1–A6 — consensus vs conformity, minority voice, opinion-leader influence, fault line, method limitations, key insight), each cell with a verified quote and line; latent cells flagged as disputed.","files":["fixtures/focus-group/transcript.txt"],"gold":"fixtures/focus-group/gold.md","gold_claims":"fixtures/focus-group/claims.json"},{"id":9,"lens":"team-retro","prompt":"I have a transcript of a team retro after a sprint on the \"Express-30\" feature (30-minute delivery) — a facilitator and five team members discussing what worked, what didn't, and what to try next. Analyze it: what the team decided to keep, which episodes failed and why, where opinions genuinely diverged, and which agreements were left without an owner.","expected_output":"Mapping via the team-retro template (group format, utterance+speaker): Layer 1 (T1–T7 — context, keep, stop with episodes, try with owners, forks, cross-role friction, external blockers) with quote, speaker, and line; Layer 2 (A1–A6 — attribution of causes, team agreement, reproducibility of success, unresolved conflict, priority, key insight) with unstable cells flagged; action items listed separately with owner, and any left unowned.","files":["fixtures/team-retro/transcript.txt"],"gold":"fixtures/team-retro/gold.md","gold_claims":"fixtures/team-retro/claims.json"},{"id":10,"lens":"intercept","prompt":"I have a short transcript of a conversation at a trade-show booth — right after a visitor tried our demo, we intercepted them for literally a minute; they were rushing to a meeting. Analyze what they actually felt in the moment, and back it up with quotes.","expected_output":"Mapping via the intercept lens: Layer 1 (I1–I6) with facts and verified quotes by line (intercept context, micro-episode, immediate reaction, willingness to respond, prior knowledge, intent) and Layer 2 (A1–A5), where valence and key insight are flagged as disputed due to the gap between the in-the-moment reaction and subsequent rationalization, requiring human adjudication.","files":["fixtures/intercept/transcript.txt"],"gold":"fixtures/intercept/gold.md","gold_claims":"fixtures/intercept/claims.json"},{"id":11,"lens":"conflict-mediation","prompt":"I have an interview with one of the co-founders of a small web-development studio ahead of mediation — he's in conflict with his partner over equity, the hiring of the partner's wife into a project role, and an incident with a nearly-lost key client. Analyze the transcript and build the picture: what he's demanding, what's really behind the demand, who he blames, what his red lines are, and what he'll do if they can't reach an agreement.","expected_output":"Mapping of one side of the conflict: operational cells (position, interest, account of events, blame attribution, settlement attempts, BATNA, red lines, attitude toward the other side) with verbatim quotes and line numbers; an analytical layer with the position↔interest gap, a hypothesis about interest compatibility (flagged as requiring verification by a human mediator after interviewing the other side), and a settlement-readiness assessment flagged as unstable.","files":["fixtures/conflict-mediation/transcript.txt"],"gold":"fixtures/conflict-mediation/gold.md","gold_claims":"fixtures/conflict-mediation/claims.json"},{"id":12,"lens":"ethnographic","prompt":"An observer went to the warehouse of an auto-parts online store and recorded a contextual-observation session with a senior order picker during actual order assembly — here is the transcript (transcript.txt) interleaved with the observer's bracketed notes. Analyze what's actually happening at the workstation: what homegrown workarounds the employee uses, where her account of the process diverges from what's visible on the recording, and how much the observer's presence affected her. Support every conclusion with a verbatim quote or observation and line number.","expected_output":"Mapping across cells N1–N7 (environment and artifacts, observed sequence, workarounds, running commentary, say-vs-do gaps, interruptions, social context) with verified quotes and lines; Layer 2 (A1–A5) with conclusions in ALL CAPS, unstable cells flagged, and an explicit caveat about the Hawthorne effect and the single-observation limitation.","files":["fixtures/ethnographic/transcript.txt"],"gold":"fixtures/ethnographic/gold.md","gold_claims":"fixtures/ethnographic/claims.json"},{"id":13,"lens":"change-readiness","prompt":"Here is a transcript of an interview with a hospital department head ahead of rolling out a unified EHR system to replace fragmented scheduling (file transcript.txt). Analyze his real position, who else is for and against, and what he personally stands to lose or gain from this change. Support every conclusion with a quote.","expected_output":"Mapping via the change-readiness lens: Layer 1 (R1–R7) with verified quotes and line numbers, Layer 2 (A1–A6) with conclusions in ALL CAPS; the gap between the public position (\"fully in favor\") and a likely hidden interest (preserving informal control over scheduling) recorded as a hypothesis; coalition map and unstable cells flagged separately.","files":["fixtures/change-readiness/transcript.txt"],"gold":"fixtures/change-readiness/gold.md","gold_claims":"fixtures/change-readiness/claims.json"},{"id":14,"lens":"jtbd","prompt":"I have a transcript of an interview with the owner of a coffee-shop chain about how they moved from manual shift tracking in Excel and WhatsApp to a payroll service — I need to reconstruct the decision timeline: what the trigger was, what alternatives were compared, what tipped the scale, and what kept them from deciding sooner.","expected_output":"Mapping across operational cells (job statement, trigger, job map, prior solution, desired outcomes, adjacent jobs) with verbatim quotes and lines, plus analysis of the forces of progress (push/pull/anxiety/habit), the key barrier, and the choice criterion; the forces-of-progress cell and the question of the counterfactual outcome flagged as unstable, with date uncertainty noted.","files":["fixtures/jtbd/transcript.txt"],"gold":"fixtures/jtbd/gold.md","gold_claims":"fixtures/jtbd/claims.json"},{"id":15,"lens":"expert","prompt":"I have a transcript of an interview with a clinical pharmacologist — an expert on antibiotic resistance in hospitals — whom a regional health board asked to comment on a draft protocol (mandatory culture before antibiotics, an antimicrobial stewardship service). I need to map his claims, evidence, recommendations, and risks, separately rate confidence for each claim, and explicitly flag where he goes beyond his expertise or has a conflict of interest.","expected_output":"Mapping across 6 Layer 1 cells (expertise profile, key claims typed as fact/opinion/prediction, recommendations, evidence and precedents, limitations and risks, open questions) and 6 Layer 2 cells (confidence per claim, points of consensus and disagreement, disputed/unverifiable statements, decision value, key insight), each cell with a verbatim quote and line number; the expert's conflict of interest (paid lectures for the manufacturer of a drug featured in his own protocol) and his overreach beyond his expertise (opinion on the cardiology department's budget) explicitly flagged.","files":["fixtures/expert/transcript.txt"],"gold":"fixtures/expert/gold.md","gold_claims":"fixtures/expert/claims.json"},{"id":16,"lens":"brand-positioning","prompt":"I have a transcript of an interview with a regular customer of the \"Bodrost\" coffee chain, in which he compares the brand to competitors \"Coffee Cult\" and \"BlackCat\" and muses about a possible rebrand — analyze how the brand is perceived and whether renaming it would be a good idea.","expected_output":"Mapping across 7 operational cells (associations, what the name conveys/hides, name alternatives, references, visual identity, recognition/audience, renaming process) and 5 analytical conclusions (core meaning, positioning gap, renaming risk, fault line in opinions, key insight), with quotes and line numbers; the brand core flagged as unstable due to the respondent's self-contradiction.","files":["fixtures/brand-positioning/transcript.txt"],"gold":"fixtures/brand-positioning/gold.md","gold_claims":"fixtures/brand-positioning/claims.json"},{"id":17,"lens":"visitor-experience","prompt":"I have a transcript of an interview with a visitor to the \"Luminous\" optics-and-light museum — she went with her niece (file transcript.txt). Analyze the entire visit journey: how she found out about the museum, what she expected, what she liked, what disappointed her, and whether she'll come back. Support every conclusion with a quote.","expected_output":"Mapping via the visitor-experience lens: Layer 1 (V1–V8 — visit context, path to visit, delight points, friction points, content comprehension, social layer, unmet demand, value and intent) with verified quotes and line numbers; Layer 2 (A1–A6 — eNPS, emotional arc, moment of truth, key barrier, visit metaphor, key insight), unstable analytical cells flagged, including the expectation-vs-reality gap.","files":["fixtures/visitor-experience/transcript.txt"],"gold":"fixtures/visitor-experience/gold.md","gold_claims":"fixtures/visitor-experience/claims.json"}]},"isInternal":false,"tokens":3942,"sizeBytes":17346},{"name":"gold.json","path":"research-ops/skills/interview-mapper/assets/evals/gold/gold.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/assets/evals/gold/gold.json","title":"Gold Skill","category":"anthropic-skill","format":"json","content":"<!-- Skill 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Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Fassets%2Fexample-outputs%2Fjourney-map.md -->","isInternal":false,"tokens":293,"sizeBytes":1217},{"name":"opportunity-prioritization.md","path":"research-ops/skills/interview-mapper/assets/example-outputs/opportunity-prioritization.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/assets/example-outputs/opportunity-prioritization.md","title":"Example-outputs Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Fassets%2Fexample-outputs%2Fopportunity-prioritization.md 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/api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Freferences%2Fethics.md -->","isInternal":false,"tokens":985,"sizeBytes":4444},{"name":"intake.md","path":"research-ops/skills/interview-mapper/references/intake.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/references/intake.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Freferences%2Fintake.md -->","isInternal":false,"tokens":1432,"sizeBytes":5885},{"name":"pipeline.md","path":"research-ops/skills/interview-mapper/references/pipeline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/references/pipeline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Freferences%2Fpipeline.md -->","isInternal":false,"tokens":1983,"sizeBytes":7572},{"name":"reliability.md","path":"research-ops/skills/interview-mapper/references/reliability.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/references/reliability.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Freferences%2Freliability.md -->","isInternal":false,"tokens":1502,"sizeBytes":5767},{"name":"rubric.md","path":"research-ops/skills/interview-mapper/references/rubric.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/references/rubric.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Freferences%2Frubric.md -->","isInternal":false,"tokens":1085,"sizeBytes":4198},{"name":"synthesis.md","path":"research-ops/skills/interview-mapper/references/synthesis.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/references/synthesis.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via 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available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2FSKILL.md -->","frontmatter":{"name":"interview-mapper","description":"Maps a single interview transcript into a verbatim-grounded, lens-coded structure and checks whether analytic conclusions hold across independent re-runs. Use when the user wants to code, map, interpret, or make sense of an interview transcript, depth interview, custdev/JTBD/expert/usability/exit/win-loss/focus-group session, or wants cross-interview synthesis (insight cards, patterns) built up from coded transcripts — even if they don't name a method. Every conclusion must carry a verbatim quote verified against the source text; unstable conclusions are flagged for a human, never resolved by a single silent pass. Not for generating new interviews, not for plain audio transcription, and not for research-method or sample-size planning above the transcript (see product-research)."},"isInternal":false,"tokens":1958,"sizeBytes":8279},{"name":"brand-positioning.md","path":"research-ops/skills/interview-mapper/templates/brand-positioning.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/brand-positioning.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fbrand-positioning.md -->","isInternal":false,"tokens":555,"sizeBytes":2235},{"name":"candidate.md","path":"research-ops/skills/interview-mapper/templates/candidate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/candidate.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fcandidate.md -->","isInternal":false,"tokens":711,"sizeBytes":3096},{"name":"change-readiness.md","path":"research-ops/skills/interview-mapper/templates/change-readiness.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/change-readiness.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fchange-readiness.md -->","isInternal":false,"tokens":811,"sizeBytes":3798},{"name":"conflict-mediation.md","path":"research-ops/skills/interview-mapper/templates/conflict-mediation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/conflict-mediation.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fconflict-mediation.md -->","isInternal":false,"tokens":754,"sizeBytes":3381},{"name":"custdev.md","path":"research-ops/skills/interview-mapper/templates/custdev.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/custdev.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fcustdev.md -->","isInternal":false,"tokens":519,"sizeBytes":2119},{"name":"ethnographic.md","path":"research-ops/skills/interview-mapper/templates/ethnographic.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/ethnographic.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fethnographic.md -->","isInternal":false,"tokens":776,"sizeBytes":3563},{"name":"exit.md","path":"research-ops/skills/interview-mapper/templates/exit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/exit.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fexit.md -->","isInternal":false,"tokens":652,"sizeBytes":2813},{"name":"expert.md","path":"research-ops/skills/interview-mapper/templates/expert.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/expert.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fexpert.md -->","isInternal":false,"tokens":449,"sizeBytes":1969},{"name":"focus-group.md","path":"research-ops/skills/interview-mapper/templates/focus-group.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/focus-group.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Ffocus-group.md -->","isInternal":false,"tokens":787,"sizeBytes":3430},{"name":"intercept.md","path":"research-ops/skills/interview-mapper/templates/intercept.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/intercept.md","title":"Templates 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-->","isInternal":false,"tokens":545,"sizeBytes":2254},{"name":"org-mapping-vmdi.md","path":"research-ops/skills/interview-mapper/templates/org-mapping-vmdi.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/org-mapping-vmdi.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Forg-mapping-vmdi.md -->","isInternal":false,"tokens":1673,"sizeBytes":6533},{"name":"team-retro.md","path":"research-ops/skills/interview-mapper/templates/team-retro.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/team-retro.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via 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Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fvisitor-experience.md -->","isInternal":false,"tokens":613,"sizeBytes":2470},{"name":"winloss.md","path":"research-ops/skills/interview-mapper/templates/winloss.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/interview-mapper/templates/winloss.md","title":"Templates Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Finterview-mapper%2Ftemplates%2Fwinloss.md -->","isInternal":false,"tokens":614,"sizeBytes":2724},{"name":"market_research_brief_template.md","path":"research-ops/skills/market-research/assets/market_research_brief_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/market-research/assets/market_research_brief_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fmarket-research%2Fassets%2Fmarket_research_brief_template.md -->","isInternal":false,"tokens":374,"sizeBytes":1638},{"name":"market_sizing_canon.md","path":"research-ops/skills/market-research/references/market_sizing_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/market-research/references/market_sizing_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fmarket-research%2Freferences%2Fmarket_sizing_canon.md -->","isInternal":false,"tokens":604,"sizeBytes":2650},{"name":"segmentation_and_ci.md","path":"research-ops/skills/market-research/references/segmentation_and_ci.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/market-research/references/segmentation_and_ci.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fmarket-research%2Freferences%2Fsegmentation_and_ci.md -->","isInternal":false,"tokens":637,"sizeBytes":2888},{"name":"survey_methodology.md","path":"research-ops/skills/market-research/references/survey_methodology.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/market-research/references/survey_methodology.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fmarket-research%2Freferences%2Fsurvey_methodology.md -->","isInternal":false,"tokens":607,"sizeBytes":2631},{"name":"SKILL.md","path":"research-ops/skills/market-research/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/market-research/SKILL.md","title":"market-research","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fmarket-research%2FSKILL.md -->","frontmatter":{"name":"market-research","description":"Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number), planning a survey sample size with finite-population correction and per-segment minimums, or scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria. Outputs always show the method and the assumptions. For market-research analysts and product-marketing at the sizing/survey/segmentation moment. Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — this is the evidence-building methodology, not live-campaign optimization.","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["research-ops","market-research","tam-sam-som","market-sizing","survey","sampling","segmentation","competitive-intelligence"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2384,"sizeBytes":10294},{"name":"research_plan_template.md","path":"research-ops/skills/product-research/assets/research_plan_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/product-research/assets/research_plan_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fproduct-research%2Fassets%2Fresearch_plan_template.md -->","isInternal":false,"tokens":382,"sizeBytes":1546},{"name":"repository_and_synthesis.md","path":"research-ops/skills/product-research/references/repository_and_synthesis.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/product-research/references/repository_and_synthesis.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fproduct-research%2Freferences%2Frepository_and_synthesis.md -->","isInternal":false,"tokens":545,"sizeBytes":2626},{"name":"research_methods_canon.md","path":"research-ops/skills/product-research/references/research_methods_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/product-research/references/research_methods_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fproduct-research%2Freferences%2Fresearch_methods_canon.md -->","isInternal":false,"tokens":603,"sizeBytes":2607},{"name":"sampling_and_saturation.md","path":"research-ops/skills/product-research/references/sampling_and_saturation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/product-research/references/sampling_and_saturation.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fproduct-research%2Freferences%2Fsampling_and_saturation.md -->","isInternal":false,"tokens":633,"sizeBytes":2536},{"name":"SKILL.md","path":"research-ops/skills/product-research/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/product-research/SKILL.md","title":"product-research","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fproduct-research%2FSKILL.md -->","frontmatter":{"name":"product-research","description":"Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["research-ops","product-research","ux-research","jtbd","usability","saturation","insight-synthesis","research-repository"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2528,"sizeBytes":11177},{"name":"rd_program_budget_template.md","path":"research-ops/skills/research-finance/assets/rd_program_budget_template.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/research-finance/assets/rd_program_budget_template.md","title":"Assets Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fresearch-finance%2Fassets%2Frd_program_budget_template.md -->","isInternal":false,"tokens":523,"sizeBytes":1792},{"name":"burn_and_portfolio.md","path":"research-ops/skills/research-finance/references/burn_and_portfolio.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/research-finance/references/burn_and_portfolio.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fresearch-finance%2Freferences%2Fburn_and_portfolio.md -->","isInternal":false,"tokens":606,"sizeBytes":2776},{"name":"indirect_rate_modeling.md","path":"research-ops/skills/research-finance/references/indirect_rate_modeling.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/research-finance/references/indirect_rate_modeling.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fresearch-finance%2Freferences%2Findirect_rate_modeling.md -->","isInternal":false,"tokens":595,"sizeBytes":2459},{"name":"rd_program_finance_canon.md","path":"research-ops/skills/research-finance/references/rd_program_finance_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/research-finance/references/rd_program_finance_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fresearch-finance%2Freferences%2Frd_program_finance_canon.md -->","isInternal":false,"tokens":701,"sizeBytes":2833},{"name":"SKILL.md","path":"research-ops/skills/research-finance/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/research-finance/SKILL.md","title":"research-finance","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fresearch-finance%2FSKILL.md -->","frontmatter":{"name":"research-finance","description":"Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["research-ops","research-finance","rd-budget","burn-rate","runway","fa-rate","capitalize-vs-expense","portfolio"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2544,"sizeBytes":10682},{"name":"SKILL.md","path":"research-ops/skills/research-ops-skills/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/skills/research-ops-skills/SKILL.md","title":"research-ops-skills","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2Fskills%2Fresearch-ops-skills%2FSKILL.md -->","frontmatter":{"name":"research-ops-skills","description":"Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on \"design this clinical study\", \"what sample size\", \"R&D budget\", \"burn rate\", \"capitalize or expense\", \"TAM SAM SOM\", \"market sizing\", \"survey design\", \"segment the market\", \"plan user interviews\", \"usability test\", \"synthesize research insights\". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).","context":"fork","license":"MIT","metadata":{"version":"2.9.0","author":"claude-code-skills","tags":["research-ops","clinical-research","research-finance","market-research","product-research","rd","orchestrator"],"compatible_tools":["claude-code","codex-cli","cursor","antigravity","opencode","gemini-cli"]}},"isInternal":false,"tokens":2689,"sizeBytes":11218},{"name":"full-catalog.md","path":"research/deep-research/skills/deep-research/references/full-catalog.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/deep-research/skills/deep-research/references/full-catalog.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdeep-research%2Fskills%2Fdeep-research%2Freferences%2Ffull-catalog.md -->","isInternal":false,"tokens":218,"sizeBytes":980},{"name":"SKILL.md","path":"research/deep-research/skills/deep-research/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/deep-research/skills/deep-research/SKILL.md","title":"deep-research","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdeep-research%2Fskills%2Fdeep-research%2FSKILL.md -->","frontmatter":{"name":"deep-research","description":"Run a disciplined, multi-source research investigation for a high-stakes question or decision — fan-out web search across many channels, parallel sub-agents, source triangulation (each claim backed by ≥3 independent sources), an adversarial review pass, and every source saved to its own file with verbatim quotes for reuse. Use when a low-quality answer is expensive: strategy work, comparing N products/methods/markets, validating a hypothesis with external data, or mapping how a field works. NOT for quick fact-checks (answer directly), structured 12-dimension competitor scoring (use competitive-teardown), or fast topic overviews where the decision risk is low (use the research router instead)."},"isInternal":false,"tokens":1731,"sizeBytes":7834},{"name":"SKILL.md","path":"research/deepread/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/deepread/SKILL.md","title":"deepread","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdeepread%2FSKILL.md -->","frontmatter":{"name":"deepread","description":"Use when the user asks to deeply read a book, article, PDF, or document set; extract claims and evidence; build a knowledge map; or learn through Feynman explanation and recall. Covers quick, deep, map, Feynman, and whole-book reading modes."},"isInternal":false,"tokens":1728,"sizeBytes":8198},{"name":"conversation_hook_quality.md","path":"research/dossier/skills/dossier/references/conversation_hook_quality.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/dossier/skills/dossier/references/conversation_hook_quality.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdossier%2Fskills%2Fdossier%2Freferences%2Fconversation_hook_quality.md -->","isInternal":false,"tokens":1756,"sizeBytes":7681},{"name":"hypothesis_testing_discipline.md","path":"research/dossier/skills/dossier/references/hypothesis_testing_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/dossier/skills/dossier/references/hypothesis_testing_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdossier%2Fskills%2Fdossier%2Freferences%2Fhypothesis_testing_discipline.md -->","isInternal":false,"tokens":2008,"sizeBytes":8835},{"name":"subject_type_source_matrix.md","path":"research/dossier/skills/dossier/references/subject_type_source_matrix.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/dossier/skills/dossier/references/subject_type_source_matrix.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdossier%2Fskills%2Fdossier%2Freferences%2Fsubject_type_source_matrix.md -->","isInternal":false,"tokens":2036,"sizeBytes":8885},{"name":"SKILL.md","path":"research/dossier/skills/dossier/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/dossier/skills/dossier/SKILL.md","title":"dossier","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdossier%2Fskills%2Fdossier%2FSKILL.md -->","frontmatter":{"name":"dossier","description":"Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network and reputation signals, red flags, conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica) as workhorses; optional BYOK MCPs enhance coverage. Use when the user asks for background research, diligence, or meeting prep on a specific entity (e.g., 'prep me for a meeting with [person/company]', 'due diligence on [company]'). Honors sensitivity exclusions for journalism + personal-vetting contexts.","license":"MIT","metadata":{"source_spec":"megaprompts/12-dossier-megaprompt.md","build_pattern":"Path B (direct conversion)","research_pack_convention":"Agent Integrity Rules verbatim per PR #657 audit; hypothesis-testing variant","version":"1.0.0"}},"isInternal":false,"tokens":3945,"sizeBytes":16838},{"name":"docx_9_sections.md","path":"research/grants/skills/grants/references/docx_9_sections.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/grants/skills/grants/references/docx_9_sections.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fgrants%2Fskills%2Fgrants%2Freferences%2Fdocx_9_sections.md -->","isInternal":false,"tokens":2948,"sizeBytes":10958},{"name":"nih_mechanism_matching.md","path":"research/grants/skills/grants/references/nih_mechanism_matching.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/grants/skills/grants/references/nih_mechanism_matching.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fgrants%2Fskills%2Fgrants%2Freferences%2Fnih_mechanism_matching.md -->","isInternal":false,"tokens":2317,"sizeBytes":8507},{"name":"reporter_post_patterns.md","path":"research/grants/skills/grants/references/reporter_post_patterns.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/grants/skills/grants/references/reporter_post_patterns.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fgrants%2Fskills%2Fgrants%2Freferences%2Freporter_post_patterns.md -->","isInternal":false,"tokens":1978,"sizeBytes":7652},{"name":"SKILL.md","path":"research/grants/skills/grants/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/grants/skills/grants/SKILL.md","title":"grants","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fgrants%2Fskills%2Fgrants%2FSKILL.md -->","frontmatter":{"name":"grants","description":"NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.","license":"MIT","metadata":{"source_spec":"megaprompts/08-grants-megaprompt.md","build_pattern":"Path B (direct conversion)","research_pack_convention":"Agent Integrity Rules verbatim per PR #657 audit","version":"1.0.0"}},"isInternal":false,"tokens":3707,"sizeBytes":14806},{"name":"docx_8_sections.md","path":"research/litreview/skills/litreview/references/docx_8_sections.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/litreview/skills/litreview/references/docx_8_sections.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Flitreview%2Fskills%2Flitreview%2Freferences%2Fdocx_8_sections.md -->","isInternal":false,"tokens":3100,"sizeBytes":12172},{"name":"framework_selection.md","path":"research/litreview/skills/litreview/references/framework_selection.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/litreview/skills/litreview/references/framework_selection.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Flitreview%2Fskills%2Flitreview%2Freferences%2Fframework_selection.md -->","isInternal":false,"tokens":2145,"sizeBytes":9235},{"name":"search_budget_allocation.md","path":"research/litreview/skills/litreview/references/search_budget_allocation.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/litreview/skills/litreview/references/search_budget_allocation.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Flitreview%2Fskills%2Flitreview%2Freferences%2Fsearch_budget_allocation.md -->","isInternal":false,"tokens":2479,"sizeBytes":10326},{"name":"SKILL.md","path":"research/litreview/skills/litreview/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/litreview/skills/litreview/SKILL.md","title":"litreview","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Flitreview%2Fskills%2Flitreview%2FSKILL.md -->","frontmatter":{"name":"litreview","description":"Searches academic literature through free, keyless PubMed and OpenAlex APIs, optionally augments results with Consensus MCP when connected, builds a PICO, SPIDER, decomposition, or hybrid search plan, and produces a formatted Word research-orientation guide. Uses brief intake and post-reconnaissance checkpoints to confirm the framework, sub-areas, and depth (5, 10, or 20 queries) before spending the search budget. The output is a launching pad, not a finished review. Use when the user requests a literature review, starts a paper or literature-oriented research project, or needs structured research on a topic. Do NOT use for a single paper lookup or a quick paper list; use a plain PubMed, OpenAlex, or Consensus query instead.","license":"MIT","metadata":{"source_spec":"megaprompts/09-litreview-megaprompt.md","build_pattern":"Path B (direct conversion)","research_pack_convention":"Agent Integrity Rules verbatim per PR #657 audit; sibling of pulse","version":"1.1.0"}},"isInternal":false,"tokens":4379,"sizeBytes":18180},{"name":"async_action_discipline.md","path":"research/notebooklm/skills/notebooklm/references/async_action_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/notebooklm/skills/notebooklm/references/async_action_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fnotebooklm%2Fskills%2Fnotebooklm%2Freferences%2Fasync_action_discipline.md -->","isInternal":false,"tokens":2297,"sizeBytes":9646},{"name":"browser_automation_canon.md","path":"research/notebooklm/skills/notebooklm/references/browser_automation_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/notebooklm/skills/notebooklm/references/browser_automation_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fnotebooklm%2Fskills%2Fnotebooklm%2Freferences%2Fbrowser_automation_canon.md -->","isInternal":false,"tokens":1820,"sizeBytes":8171},{"name":"studio_output_custom_prompts.md","path":"research/notebooklm/skills/notebooklm/references/studio_output_custom_prompts.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/notebooklm/skills/notebooklm/references/studio_output_custom_prompts.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fnotebooklm%2Fskills%2Fnotebooklm%2Freferences%2Fstudio_output_custom_prompts.md -->","isInternal":false,"tokens":2566,"sizeBytes":11528},{"name":"SKILL.md","path":"research/notebooklm/skills/notebooklm/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/notebooklm/skills/notebooklm/SKILL.md","title":"notebooklm","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fnotebooklm%2Fskills%2Fnotebooklm%2FSKILL.md -->","frontmatter":{"name":"notebooklm","description":"Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.","license":"MIT","metadata":{"source_spec":"megaprompts/03-notebooklm-megaprompt.md","build_pattern":"Path B (direct conversion)","shape":"browser-automation (distinct from research-pack convention)","version":"1.0.0"}},"isInternal":false,"tokens":3758,"sizeBytes":16256},{"name":"cpc_classification_canon.md","path":"research/patent/skills/patent/references/cpc_classification_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/patent/skills/patent/references/cpc_classification_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpatent%2Fskills%2Fpatent%2Freferences%2Fcpc_classification_canon.md -->","isInternal":false,"tokens":2032,"sizeBytes":8666},{"name":"legal_disclaimer_discipline.md","path":"research/patent/skills/patent/references/legal_disclaimer_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/patent/skills/patent/references/legal_disclaimer_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpatent%2Fskills%2Fpatent%2Freferences%2Flegal_disclaimer_discipline.md -->","isInternal":false,"tokens":1703,"sizeBytes":8022},{"name":"sub_use_case_routing.md","path":"research/patent/skills/patent/references/sub_use_case_routing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/patent/skills/patent/references/sub_use_case_routing.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpatent%2Fskills%2Fpatent%2Freferences%2Fsub_use_case_routing.md -->","isInternal":false,"tokens":2497,"sizeBytes":11017},{"name":"SKILL.md","path":"research/patent/skills/patent/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/patent/skills/patent/SKILL.md","title":"patent","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpatent%2Fskills%2Fpatent%2FSKILL.md -->","frontmatter":{"name":"patent","description":"Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.","license":"MIT","metadata":{"source_spec":"megaprompts/11-patent-megaprompt.md","build_pattern":"Path B (direct conversion)","research_pack_convention":"Agent Integrity Rules verbatim per PR #657 audit; sub-use-case routing variant","version":"1.0.0"}},"isInternal":false,"tokens":3843,"sizeBytes":16541},{"name":"cross_platform_synthesis.md","path":"research/pulse/skills/pulse/references/cross_platform_synthesis.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/pulse/skills/pulse/references/cross_platform_synthesis.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpulse%2Fskills%2Fpulse%2Freferences%2Fcross_platform_synthesis.md -->","isInternal":false,"tokens":2062,"sizeBytes":9058},{"name":"parallel_execution_discipline.md","path":"research/pulse/skills/pulse/references/parallel_execution_discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/pulse/skills/pulse/references/parallel_execution_discipline.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpulse%2Fskills%2Fpulse%2Freferences%2Fparallel_execution_discipline.md -->","isInternal":false,"tokens":2222,"sizeBytes":8601},{"name":"research_pack_conventions.md","path":"research/pulse/skills/pulse/references/research_pack_conventions.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/pulse/skills/pulse/references/research_pack_conventions.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpulse%2Fskills%2Fpulse%2Freferences%2Fresearch_pack_conventions.md -->","isInternal":false,"tokens":1972,"sizeBytes":8651},{"name":"SKILL.md","path":"research/pulse/skills/pulse/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/pulse/skills/pulse/SKILL.md","title":"pulse","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpulse%2Fskills%2Fpulse%2FSKILL.md -->","frontmatter":{"name":"pulse","description":"Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.","license":"MIT","metadata":{"source_spec":"megaprompts/01-pulse-megaprompt.md","build_pattern":"Path B (direct conversion)","research_pack_convention":"Agent Integrity Rules block preserved verbatim per PR #657 audit","version":"1.0.0"}},"isInternal":false,"tokens":3703,"sizeBytes":15122},{"name":"deterministic_classification_canon.md","path":"research/research/skills/research/references/deterministic_classification_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/research/skills/research/references/deterministic_classification_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fresearch%2Fskills%2Fresearch%2Freferences%2Fdeterministic_classification_canon.md -->","isInternal":false,"tokens":2265,"sizeBytes":10088},{"name":"fallback_workflow_canon.md","path":"research/research/skills/research/references/fallback_workflow_canon.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/research/skills/research/references/fallback_workflow_canon.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fresearch%2Fskills%2Fresearch%2Freferences%2Ffallback_workflow_canon.md -->","isInternal":false,"tokens":2607,"sizeBytes":12041},{"name":"hybrid_router_architecture.md","path":"research/research/skills/research/references/hybrid_router_architecture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/research/skills/research/references/hybrid_router_architecture.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fresearch%2Fskills%2Fresearch%2Freferences%2Fhybrid_router_architecture.md -->","isInternal":false,"tokens":2283,"sizeBytes":10666},{"name":"SKILL.md","path":"research/research/skills/research/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/research/skills/research/SKILL.md","title":"research","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fresearch%2Fskills%2Fresearch%2FSKILL.md -->","frontmatter":{"name":"research","description":"Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research, deepread for evidence-first reading of supplied documents) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Use when the user makes any research request that doesn't obviously match a more-specific specialist skill (e.g., \"research [topic]\", \"look into [topic]\", \"what do we know about [topic]\", \"investigate [topic]\", \"find me information on [topic]\", \"do some research on [topic]\", \"I need to understand [topic]\"). Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log."},"isInternal":false,"tokens":4094,"sizeBytes":17423},{"name":"applied_domain_weaving.md","path":"research/syllabus/skills/syllabus/references/applied_domain_weaving.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/syllabus/skills/syllabus/references/applied_domain_weaving.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fsyllabus%2Fskills%2Fsyllabus%2Freferences%2Fapplied_domain_weaving.md -->","isInternal":false,"tokens":1832,"sizeBytes":8232},{"name":"audience_calibration.md","path":"research/syllabus/skills/syllabus/references/audience_calibration.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/syllabus/skills/syllabus/references/audience_calibration.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fsyllabus%2Fskills%2Fsyllabus%2Freferences%2Faudience_calibration.md -->","isInternal":false,"tokens":2289,"sizeBytes":10240},{"name":"bundled_script_pattern.md","path":"research/syllabus/skills/syllabus/references/bundled_script_pattern.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/syllabus/skills/syllabus/references/bundled_script_pattern.md","title":"References Skill","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fsyllabus%2Fskills%2Fsyllabus%2Freferences%2Fbundled_script_pattern.md -->","isInternal":false,"tokens":1719,"sizeBytes":7280},{"name":"SKILL.md","path":"research/syllabus/skills/syllabus/SKILL.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/syllabus/skills/syllabus/SKILL.md","title":"syllabus","category":"anthropic-skill","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fsyllabus%2Fskills%2Fsyllabus%2FSKILL.md -->","frontmatter":{"name":"syllabus","description":"Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.","license":"MIT","metadata":{"source_spec":"megaprompts/10-syllabus-megaprompt.md","build_pattern":"Path B (direct conversion)","research_pack_convention":"Agent Integrity Rules verbatim per PR #657 audit; bundled-JS-DOCX-generator variant","version":"1.0.0"}},"isInternal":false,"tokens":2968,"sizeBytes":12570},{"name":"README.md","path":"agents/personas/README.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agents/personas/README.md","title":"Subagent: readme","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agents%2Fpersonas%2FREADME.md -->","isInternal":false,"tokens":646,"sizeBytes":2713},{"name":"content-strategist.md","path":"docs/agents/content-strategist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/content-strategist.md","title":"Subagent: content-strategist","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcontent-strategist.md -->","frontmatter":{"title":"Content Strategist — AI Coding Agent & Codex Skill","description":"Builds content engines that rank, convert, and compound. Thinks in systems — topic clusters, not individual posts. Every piece earns its place or. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":994,"sizeBytes":4442},{"name":"cs-aeo.md","path":"docs/agents/cs-aeo.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-aeo.md","title":"Subagent: cs-aeo","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-aeo.md -->","frontmatter":{"title":"AEO Agent — Answer Engine Optimization Specialist — AI Coding Agent & Codex Skill","description":"Answer Engine Optimization (AEO) specialist agent. Use when content needs to be optimized for citation by AI language models (ChatGPT, Perplexity. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1500,"sizeBytes":6029},{"name":"cs-agent-deployer.md","path":"docs/agents/cs-agent-deployer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-agent-deployer.md","title":"Subagent: cs-agent-deployer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-agent-deployer.md -->","frontmatter":{"title":"cs-agent-deployer — Phase 4 specialist (the recurring loop) — AI Coding Agent & Codex Skill","description":"Phase-4 specialist for making a Claude Managed Agent run without you. Turns a graded agent into a recurring POSIX-cron scheduled deployment. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":510,"sizeBytes":2061},{"name":"cs-agent-grader.md","path":"docs/agents/cs-agent-grader.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-agent-grader.md","title":"Subagent: cs-agent-grader","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-agent-grader.md -->","frontmatter":{"title":"cs-agent-grader — Phase 3 specialist (the loop) — AI Coding Agent & Codex Skill","description":"Phase-3 specialist for the bounded grade→iterate loop when building a Claude Managed Agent. Defines a CMA outcome (required rubric, max_iterations. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":510,"sizeBytes":2005},{"name":"cs-agent-interviewer.md","path":"docs/agents/cs-agent-interviewer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-agent-interviewer.md","title":"Subagent: cs-agent-interviewer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-agent-interviewer.md -->","frontmatter":{"title":"cs-agent-interviewer — Phase 1 specialist — AI Coding Agent & Codex Skill","description":"Phase-1 specialist for building a Claude Managed Agent — interviews the founder through the six intake slots (job, trigger, inputs, actions. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":452,"sizeBytes":1852},{"name":"cs-agent-launcher-orchestrator.md","path":"docs/agents/cs-agent-launcher-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-agent-launcher-orchestrator.md","title":"Subagent: cs-agent-launcher-orchestrator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-agent-launcher-orchestrator.md -->","frontmatter":{"title":"cs-agent-launcher-orchestrator — the session-goal router — AI Coding Agent & Codex Skill","description":"Session-goal router for building Claude Managed Agents. Reads ./my-agent/goal.json, routes deterministically to a phase skill (interview →. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":608,"sizeBytes":2341},{"name":"cs-agile-product-owner.md","path":"docs/agents/cs-agile-product-owner.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-agile-product-owner.md","title":"Subagent: cs-agile-product-owner","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-agile-product-owner.md -->","frontmatter":{"title":"Agile Product Owner Agent — AI Coding Agent & Codex Skill","description":"Agile product owner agent for epic breakdown, sprint planning, backlog refinement, and INVEST-compliant user story generation. Use when preparing. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":4200,"sizeBytes":18318},{"name":"cs-ai-act-compliance.md","path":"docs/agents/cs-ai-act-compliance.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-ai-act-compliance.md","title":"Subagent: cs-ai-act-compliance","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-ai-act-compliance.md -->","frontmatter":{"title":"EU AI Act Compliance Agent — AI Coding Agent & Codex Skill","description":"EU AI Act (Regulation (EU) 2024/1689) Article-cited compliance operator. Three decisions: AI system risk tier (Article 5 / 6+ Annex III / 50 /. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2269,"sizeBytes":8980},{"name":"cs-aims-iso42001.md","path":"docs/agents/cs-aims-iso42001.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-aims-iso42001.md","title":"Subagent: cs-aims-iso42001","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-aims-iso42001.md -->","frontmatter":{"title":"AIMS ISO 42001 Specialist Agent — AI Coding Agent & Codex Skill","description":"ISO/IEC 42001:2023 AI Management System (AIMS) implementation + internal audit operator. Three decisions: AIMS gaps against Clauses 4-10, AI risk. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2039,"sizeBytes":8045},{"name":"cs-andreessen.md","path":"docs/agents/cs-andreessen.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-andreessen.md","title":"Subagent: cs-andreessen","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-andreessen.md -->","frontmatter":{"title":"Andreessen Agent — AI Coding Agent & Codex Skill","description":"Marc Andreessen-mode operator. Runs on a fixed anti-sycophancy operating prompt — leads with the strongest counterargument, never validates premises. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1487,"sizeBytes":5983},{"name":"cs-arquiteto.md","path":"docs/agents/cs-arquiteto.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-arquiteto.md","title":"Subagent: cs-arquiteto","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-arquiteto.md -->","frontmatter":{"title":"Company Architect (cs-arquiteto) — AI Coding Agent & Codex Skill","description":"Company Architect — a senior chief of staff who builds a business from scratch as an OKF (Open Knowledge Format) bundle: a tree of. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":627,"sizeBytes":2641},{"name":"cs-backend-engineer.md","path":"docs/agents/cs-backend-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-backend-engineer.md","title":"Subagent: cs-backend-engineer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-backend-engineer.md -->","frontmatter":{"title":"cs-backend-engineer — Backend Orchestrator — AI Coding Agent & Codex Skill","description":"Backend-engineering orchestrator. Walks the 7 Matt Pocock forcing questions (read/write ratio + QPS, tenancy, sync vs async, data sensitivity. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1355,"sizeBytes":5332},{"name":"cs-book-to-skill.md","path":"docs/agents/cs-book-to-skill.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-book-to-skill.md","title":"Subagent: cs-book-to-skill","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-book-to-skill.md -->","frontmatter":{"title":"Book-to-Skill Converter Agent — AI Coding Agent & Codex Skill","description":"Book-to-skill converter persona. Interrogates whether a source is worth converting before spending a generation pass on it, then drives extract →. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1171,"sizeBytes":4941},{"name":"cs-caio-advisor.md","path":"docs/agents/cs-caio-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-caio-advisor.md","title":"Subagent: cs-caio-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-caio-advisor.md -->","frontmatter":{"title":"Chief AI Officer Advisor Agent — AI Coding Agent & Codex Skill","description":"Eval-demanding Chief AI Officer advisor for model build-vs-buy decisions, AI risk classification under EU AI Act + US state laws, AI cost economics. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2971,"sizeBytes":11685},{"name":"cs-capture.md","path":"docs/agents/cs-capture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-capture.md","title":"Subagent: cs-capture","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-capture.md -->","frontmatter":{"title":"Capture Agent — AI Coding Agent & Codex Skill","description":"Brain-dump organizer persona. Catches unstructured streams of mixed thoughts/tasks/ideas and transforms them into a 4-section actionable system with. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1430,"sizeBytes":5566},{"name":"cs-cco-advisor.md","path":"docs/agents/cs-cco-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cco-advisor.md","title":"Subagent: cs-cco-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cco-advisor.md -->","frontmatter":{"title":"Chief Customer Officer Advisor Agent — AI Coding Agent & Codex Skill","description":"Retention-obsessed Chief Customer Officer advisor for honest retention decomposition (GRR vs NRR), customer segmentation (differential investment). Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2824,"sizeBytes":11338},{"name":"cs-cdo-advisor.md","path":"docs/agents/cs-cdo-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cdo-advisor.md","title":"Subagent: cs-cdo-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cdo-advisor.md -->","frontmatter":{"title":"Chief Data Officer Advisor Agent — AI Coding Agent & Codex Skill","description":"Decision-driven Chief Data Officer advisor for AI training data rights, data product strategy (warehouse/lakehouse/mesh + build-vs-buy), B2B. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2444,"sizeBytes":9900},{"name":"cs-ceo-advisor.md","path":"docs/agents/cs-ceo-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-ceo-advisor.md","title":"Subagent: cs-ceo-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-ceo-advisor.md -->","frontmatter":{"title":"CEO Advisor Agent — AI Coding Agent & Codex Skill","description":"Strategic leadership advisor for CEOs covering vision, strategy, board management, investor relations, and organizational culture. Use when a founder. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":3815,"sizeBytes":16973},{"name":"cs-cfo-advisor.md","path":"docs/agents/cs-cfo-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cfo-advisor.md","title":"Subagent: cs-cfo-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cfo-advisor.md -->","frontmatter":{"title":"CFO Advisor Agent — AI Coding Agent & Codex Skill","description":"Numerate-skeptic CFO advisor for unit economics, runway, fundraising, dilution, and board-grade financial decisions. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1743,"sizeBytes":6845},{"name":"cs-chief-of-staff.md","path":"docs/agents/cs-chief-of-staff.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-chief-of-staff.md","title":"Subagent: cs-chief-of-staff","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-chief-of-staff.md -->","frontmatter":{"title":"Chief of Staff Agent — AI Coding Agent & Codex Skill","description":"Routing-and-synthesis chief of staff for orchestrating the virtual boardroom, logging decisions, and surfacing stale ones. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1741,"sizeBytes":6871},{"name":"cs-chro-advisor.md","path":"docs/agents/cs-chro-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-chro-advisor.md","title":"Subagent: cs-chro-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-chro-advisor.md -->","frontmatter":{"title":"CHRO Advisor Agent — AI Coding Agent & Codex Skill","description":"People-systems CHRO advisor for hiring strategy, comp bands, leveling ladders, org design, and retention. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1490,"sizeBytes":5831},{"name":"cs-ciso-advisor.md","path":"docs/agents/cs-ciso-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-ciso-advisor.md","title":"Subagent: cs-ciso-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-ciso-advisor.md -->","frontmatter":{"title":"CISO Advisor Agent — AI Coding Agent & Codex Skill","description":"Risk-paranoid CISO advisor for threat modeling, compliance, incident response, and security architecture. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1570,"sizeBytes":6136},{"name":"cs-ciso-iso27001.md","path":"docs/agents/cs-ciso-iso27001.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-ciso-iso27001.md","title":"Subagent: cs-ciso-iso27001","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-ciso-iso27001.md -->","frontmatter":{"title":"ISO 27001 ISMS Auditor Agent — AI Coding Agent & Codex Skill","description":"ISO/IEC 27001:2022 ISMS audit + implementation persona. Sample-driven; samples real records, not curated demos. Coordinates with SOC 2 (75% overlap). Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2202,"sizeBytes":8636},{"name":"cs-claude-coach.md","path":"docs/agents/cs-claude-coach.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-claude-coach.md","title":"Subagent: cs-claude-coach","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-claude-coach.md -->","frontmatter":{"title":"cs-claude-coach — Power-User Coach Persona — AI Coding Agent & Codex Skill","description":"Use proactively after any user message in a Claude.ai or Claude Code session where the user is learning to prompt better or has explicitly activated. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":694,"sizeBytes":2919},{"name":"cs-claude-code-rollout.md","path":"docs/agents/cs-claude-code-rollout.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-claude-code-rollout.md","title":"Subagent: cs-claude-code-rollout","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-claude-code-rollout.md -->","frontmatter":{"title":"Claude Code Rollout — AI Coding Agent & Codex Skill","description":"Use when a team or organization is rolling out Claude Code, or auditing one already in use — shared and managed settings, permission rules, MCP. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":703,"sizeBytes":2933},{"name":"cs-close-controller.md","path":"docs/agents/cs-close-controller.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-close-controller.md","title":"Subagent: cs-close-controller","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-close-controller.md -->","frontmatter":{"title":"Close Controller — AI Coding Agent & Codex Skill","description":"Use when someone is running, planning or trying to shorten a month-end or quarter-end close, reconciling a bank statement or sub-ledger to the. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":742,"sizeBytes":3098},{"name":"cs-cmo-advisor.md","path":"docs/agents/cs-cmo-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cmo-advisor.md","title":"Subagent: cs-cmo-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cmo-advisor.md -->","frontmatter":{"title":"CMO Advisor Agent — AI Coding Agent & Codex Skill","description":"Narrative-first CMO advisor for ICP definition, positioning, message house, channel mix, and category creation. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1493,"sizeBytes":6088},{"name":"cs-commercial-orchestrator.md","path":"docs/agents/cs-commercial-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-commercial-orchestrator.md","title":"Subagent: cs-commercial-orchestrator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-commercial-orchestrator.md -->","frontmatter":{"title":"cs-commercial-orchestrator — Margin-protective Commercial lead — AI Coding Agent & Codex Skill","description":"Margin-protective Commercial lead. Routes per-deal-and-packaging inquiries (pricing / deal / partner / channel / policy / RFP / forecast) to the. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1391,"sizeBytes":5660},{"name":"cs-compliance-officer.md","path":"docs/agents/cs-compliance-officer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-compliance-officer.md","title":"Subagent: cs-compliance-officer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-compliance-officer.md -->","frontmatter":{"title":"Compliance Officer Agent (Multi-Framework Orchestrator) — AI Coding Agent & Codex Skill","description":"Multi-framework compliance officer orchestrating cross-framework programs. Routes per-framework deep work to specialist skills (ISO 42001, EU AI Act. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2910,"sizeBytes":12272},{"name":"cs-content-creator.md","path":"docs/agents/cs-content-creator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-content-creator.md","title":"Subagent: cs-content-creator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-content-creator.md -->","frontmatter":{"title":"Content Creator Agent — AI Coding Agent & Codex Skill","description":"Long-form marketing content producer orchestrating the content-production skill (research → brief → draft → optimize → gate). Use when content must. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2654,"sizeBytes":11242},{"name":"cs-coo-advisor.md","path":"docs/agents/cs-coo-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-coo-advisor.md","title":"Subagent: cs-coo-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-coo-advisor.md -->","frontmatter":{"title":"COO Advisor Agent — AI Coding Agent & Codex Skill","description":"Execution-OS COO advisor for operating cadence, OKRs, scorecards, DRI clarity, and scaling playbooks. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1581,"sizeBytes":6046},{"name":"cs-cpo-advisor.md","path":"docs/agents/cs-cpo-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cpo-advisor.md","title":"Subagent: cs-cpo-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cpo-advisor.md -->","frontmatter":{"title":"CPO Advisor Agent — AI Coding Agent & Codex Skill","description":"JTBD-driven CPO advisor for product vision, portfolio strategy, PMF, North Star metrics, and roadmap focus. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1534,"sizeBytes":6028},{"name":"cs-cqm-iso13485.md","path":"docs/agents/cs-cqm-iso13485.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cqm-iso13485.md","title":"Subagent: cs-cqm-iso13485","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cqm-iso13485.md -->","frontmatter":{"title":"ISO 13485 QMS Auditor Agent — AI Coding Agent & Codex Skill","description":"ISO 13485:2016 QMS audit persona — Design Control + CAPA + Process Validation focused. Coordinates with ISO 14971 (risk file), MDR 745 (technical. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2346,"sizeBytes":8992},{"name":"cs-cro-advisor.md","path":"docs/agents/cs-cro-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cro-advisor.md","title":"Subagent: cs-cro-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cro-advisor.md -->","frontmatter":{"title":"CRO Advisor Agent — AI Coding Agent & Codex Skill","description":"Pipeline-paranoid CRO advisor for revenue forecasting, sales motion, NRR, ramp time, and pipeline coverage. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1456,"sizeBytes":5726},{"name":"cs-cto-advisor.md","path":"docs/agents/cs-cto-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-cto-advisor.md","title":"Subagent: cs-cto-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-cto-advisor.md -->","frontmatter":{"title":"CTO Advisor Agent — AI Coding Agent & Codex Skill","description":"Technical leadership advisor for CTOs covering technology strategy, team scaling, architecture decisions, and engineering excellence. Use when a CTO. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":4135,"sizeBytes":18001},{"name":"cs-deep-learning-tutor.md","path":"docs/agents/cs-deep-learning-tutor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-deep-learning-tutor.md","title":"Subagent: cs-deep-learning-tutor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-deep-learning-tutor.md -->","frontmatter":{"title":"Deep Learning Tutor — AI Coding Agent & Codex Skill","description":"Study companion for the Deep Learning textbook (Goodfellow, Bengio & Courville, 2016). Plans a prerequisite-closed reading path, answers chapter. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":952,"sizeBytes":4050},{"name":"cs-deep-research.md","path":"docs/agents/cs-deep-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-deep-research.md","title":"Subagent: cs-deep-research","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-deep-research.md -->","frontmatter":{"title":"Deep Research Agent — AI Coding Agent & Codex Skill","description":"Rigor-first meta-research persona for high-stakes questions. Reframes the question into 2-4 falsifiable hypotheses, writes a plan, discovers. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1086,"sizeBytes":4544},{"name":"cs-deep-work.md","path":"docs/agents/cs-deep-work.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-deep-work.md","title":"Subagent: cs-deep-work","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-deep-work.md -->","frontmatter":{"title":"Deep Work Agent — AI Coding Agent & Codex Skill","description":"Plans a deep work day the Cal Newport way — audits a task list deep vs shallow against a 30-50% shallow budget, builds an energy-first time-blocked. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1339,"sizeBytes":5273},{"name":"cs-demand-gen-specialist.md","path":"docs/agents/cs-demand-gen-specialist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-demand-gen-specialist.md","title":"Subagent: cs-demand-gen-specialist","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-demand-gen-specialist.md -->","frontmatter":{"title":"Demand Generation Specialist Agent — AI Coding Agent & Codex Skill","description":"Demand generation and acquisition-funnel specialist orchestrating the marketing-demand-acquisition, paid-ads, and email-sequence skills. Use when. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":3344,"sizeBytes":13662},{"name":"cs-dossier.md","path":"docs/agents/cs-dossier.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-dossier.md","title":"Subagent: cs-dossier","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-dossier.md -->","frontmatter":{"title":"Dossier Agent — AI Coding Agent & Codex Skill","description":"Decision-grade entity research persona. Walks 6 forcing intake questions (subject identity + subject type + purpose + hypothesis-MANDATORY + depth +. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1344,"sizeBytes":5269},{"name":"cs-dpo-gdpr.md","path":"docs/agents/cs-dpo-gdpr.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-dpo-gdpr.md","title":"Subagent: cs-dpo-gdpr","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-dpo-gdpr.md -->","frontmatter":{"title":"GDPR DPO Auditor Agent — AI Coding Agent & Codex Skill","description":"GDPR / DSGVO Data Protection Officer audit persona. Lawful-basis-discipline + DPIA-quality + Schrems-II-transfer-aware. Coordinates with ISO 27001. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2447,"sizeBytes":9363},{"name":"cs-engineering-lead.md","path":"docs/agents/cs-engineering-lead.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-engineering-lead.md","title":"Subagent: cs-engineering-lead","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-engineering-lead.md -->","frontmatter":{"title":"Engineering Lead — AI Coding Agent & Codex Skill","description":"Engineering Team Lead agent for coordinating QA, security, data engineering, ML, and frontend/backend teams. Orchestrates engineering-team skills for. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":896,"sizeBytes":3843},{"name":"cs-eval-gatekeeper.md","path":"docs/agents/cs-eval-gatekeeper.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-eval-gatekeeper.md","title":"Subagent: cs-eval-gatekeeper","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-eval-gatekeeper.md -->","frontmatter":{"title":"Eval Gatekeeper — AI Coding Agent & Codex Skill","description":"Use when someone wants to know whether an agent, prompt, model or tool change made their agent worse, is setting up a regression eval suite or CI. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2506,"sizeBytes":9641},{"name":"cs-financial-analyst.md","path":"docs/agents/cs-financial-analyst.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-financial-analyst.md","title":"Subagent: cs-financial-analyst","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-financial-analyst.md -->","frontmatter":{"title":"Financial Analyst — AI Coding Agent & Codex Skill","description":"Financial Analyst agent for DCF valuation, financial modeling, budgeting, forecasting, and SaaS metrics (ARR, MRR, churn, CAC, LTV, NRR). 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2952,"sizeBytes":11939},{"name":"cs-general-counsel-advisor.md","path":"docs/agents/cs-general-counsel-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-general-counsel-advisor.md","title":"Subagent: cs-general-counsel-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-general-counsel-advisor.md -->","frontmatter":{"title":"General Counsel Advisor Agent — AI Coding Agent & Codex Skill","description":"Risk-paranoid General Counsel advisor for contract review, IP strategy, term sheet decoding, and regulatory landscape mapping. Not legal advice. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2482,"sizeBytes":10171},{"name":"cs-grants.md","path":"docs/agents/cs-grants.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-grants.md","title":"Subagent: cs-grants","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-grants.md -->","frontmatter":{"title":"Grants Agent — AI Coding Agent & Codex Skill","description":"NIH grant research persona for clinical researchers. Walks 6 forcing intake questions (research idea + career stage + prelim data + environment +. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1187,"sizeBytes":4533},{"name":"cs-grill-master.md","path":"docs/agents/cs-grill-master.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-grill-master.md","title":"Subagent: cs-grill-master","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-grill-master.md -->","frontmatter":{"title":"Grill Master Agent — AI Coding Agent & Codex Skill","description":"Relentless plan-and-design interrogator. Walks decision trees one branch at a time, asks one question per turn with recommended answer + rationale. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":729,"sizeBytes":3169},{"name":"cs-handoff-author.md","path":"docs/agents/cs-handoff-author.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-handoff-author.md","title":"Subagent: cs-handoff-author","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-handoff-author.md -->","frontmatter":{"title":"Handoff Author Agent — AI Coding Agent & Codex Skill","description":"Conversation-handoff author. Compacts the current session into a markdown handoff for a fresh agent. Tailors content to next-session focus. Refuses. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1218,"sizeBytes":4871},{"name":"cs-inbox-setup.md","path":"docs/agents/cs-inbox-setup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-inbox-setup.md","title":"Subagent: cs-inbox-setup","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-inbox-setup.md -->","frontmatter":{"title":"Inbox-Setup Agent — AI Coding Agent & Codex Skill","description":"One-time email-triage onboarding persona. Conducts an 8-section interactive interview (~25-31 grill-me questions) to build a personalized knowledge. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2619,"sizeBytes":10606},{"name":"cs-inbox-triage.md","path":"docs/agents/cs-inbox-triage.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-inbox-triage.md","title":"Subagent: cs-inbox-triage","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-inbox-triage.md -->","frontmatter":{"title":"Inbox-Triage Agent — AI Coding Agent & Codex Skill","description":"Recurring email-triage execution persona. Reads the 7-file KB produced by inbox-setup, classifies recent emails via the user's taxonomy, researches. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2656,"sizeBytes":10363},{"name":"cs-interview-mapper.md","path":"docs/agents/cs-interview-mapper.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-interview-mapper.md","title":"Subagent: cs-interview-mapper","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-interview-mapper.md -->","frontmatter":{"title":"cs-interview-mapper — Transcript-level interview analyst — AI Coding Agent & Codex Skill","description":"Transcript-level interview analyst. Refuses to accept a conclusion without a verbatim quote checked against the source, refuses to call a cross-run. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":750,"sizeBytes":3069},{"name":"cs-landing.md","path":"docs/agents/cs-landing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-landing.md","title":"Subagent: cs-landing","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-landing.md -->","frontmatter":{"title":"Landing Agent — AI Coding Agent & Codex Skill","description":"Premium HTML landing page generator persona. Walks 3-4 forcing intake questions (product+pitch, audience register, brand overrides, tone) before. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2545,"sizeBytes":9996},{"name":"cs-linkedin-editor.md","path":"docs/agents/cs-linkedin-editor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-linkedin-editor.md","title":"Subagent: cs-linkedin-editor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-linkedin-editor.md -->","frontmatter":{"title":"LinkedIn Editor Agent — AI Coding Agent & Codex Skill","description":"Drafts, edits, and lints LinkedIn posts to a publishable standard — hook that survives the ~140-character mobile fold, one idea, real numbers, no. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1278,"sizeBytes":5417},{"name":"cs-litreview.md","path":"docs/agents/cs-litreview.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-litreview.md","title":"Subagent: cs-litreview","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-litreview.md -->","frontmatter":{"title":"Litreview Agent — AI Coding Agent & Codex Skill","description":"Academic literature orientation persona. Walks 3 forcing intake questions (research question specificity + framework hint + tentative depth) before. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2752,"sizeBytes":10905},{"name":"cs-markdown-html-orchestrator.md","path":"docs/agents/cs-markdown-html-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-markdown-html-orchestrator.md","title":"Subagent: cs-markdown-html-orchestrator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-markdown-html-orchestrator.md -->","frontmatter":{"title":"cs-markdown-html-orchestrator — Density-first markdown-to-HTML converter — AI Coding Agent & Codex Skill","description":"Density-first markdown-to-HTML converter. Routes long markdown files (≥ 100 lines per Shihipar's threshold) to one of three converter sub-skills. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1517,"sizeBytes":6385},{"name":"cs-meeting-discipline.md","path":"docs/agents/cs-meeting-discipline.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-meeting-discipline.md","title":"Subagent: cs-meeting-discipline","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-meeting-discipline.md -->","frontmatter":{"title":"Meeting Discipline Agent — AI Coding Agent & Codex Skill","description":"Enforces personal meeting hygiene end to end. Before a meeting it runs the cost gate (attendees x minutes x rate, optionally + 23-minute refocus. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":904,"sizeBytes":3932},{"name":"cs-notebooklm.md","path":"docs/agents/cs-notebooklm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-notebooklm.md","title":"Subagent: cs-notebooklm","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-notebooklm.md -->","frontmatter":{"title":"NotebookLM Agent — AI Coding Agent & Codex Skill","description":"NotebookLM browser-automation persona. Walks 2-4 forcing intake questions (Q1 action: read / add source / Studio output / create new; Q2-Q4 branch. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1278,"sizeBytes":5000},{"name":"cs-pm-orchestrator.md","path":"docs/agents/cs-pm-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-pm-orchestrator.md","title":"Subagent: cs-pm-orchestrator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-pm-orchestrator.md -->","frontmatter":{"title":"PM Orchestrator — AI Coding Agent & Codex Skill","description":"Flow-first delivery lead. Routes project-management inquiries (sprint/velocity, portfolio health, Jira/JQL, Confluence, Atlassian admin, templates. 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Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":7826,"sizeBytes":34238},{"name":"cs-product-orchestrator.md","path":"docs/agents/cs-product-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-product-orchestrator.md","title":"Subagent: cs-product-orchestrator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-product-orchestrator.md -->","frontmatter":{"title":"Product Orchestrator — AI Coding Agent & Codex Skill","description":"Outcome-first product lead. Routes product inquiries (prioritization, OKRs, UX research, design systems, competitive, analytics, experiments. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1077,"sizeBytes":4411},{"name":"cs-product-strategist.md","path":"docs/agents/cs-product-strategist.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-product-strategist.md","title":"Subagent: cs-product-strategist","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-product-strategist.md -->","frontmatter":{"title":"Product Strategist Agent — AI Coding Agent & Codex Skill","description":"Product strategy agent for quarterly OKR planning, competitive landscape analysis, product vision development, and strategy pivot evaluation. Use. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":5170,"sizeBytes":22882},{"name":"cs-project-manager.md","path":"docs/agents/cs-project-manager.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-project-manager.md","title":"Subagent: cs-project-manager","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-project-manager.md -->","frontmatter":{"title":"Project Manager Agent — AI Coding Agent & Codex Skill","description":"Project Manager agent for sprint planning, Jira/Confluence workflows, Scrum ceremonies, and stakeholder reporting. Orchestrates project-management. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":6702,"sizeBytes":29923},{"name":"cs-pulse.md","path":"docs/agents/cs-pulse.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-pulse.md","title":"Subagent: cs-pulse","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-pulse.md -->","frontmatter":{"title":"Pulse Agent — AI Coding Agent & Codex Skill","description":"Multi-source recency research persona. Walks 2–4 forcing intake questions one at a time (topic specificity, angle, time window, platform scope), runs. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2819,"sizeBytes":11093},{"name":"cs-quality-regulatory.md","path":"docs/agents/cs-quality-regulatory.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-quality-regulatory.md","title":"Subagent: cs-quality-regulatory","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-quality-regulatory.md -->","frontmatter":{"title":"Quality Regulatory — AI Coding Agent & Codex Skill","description":"Quality & Regulatory agent for ISO 13485 QMS, MDR compliance, FDA submissions, GDPR/DSGVO, and ISMS audits. Orchestrates ra-qm-team skills. Spawn. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1064,"sizeBytes":4275},{"name":"cs-reflect.md","path":"docs/agents/cs-reflect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-reflect.md","title":"Subagent: cs-reflect","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-reflect.md -->","frontmatter":{"title":"Reflect Agent — AI Coding Agent & Codex Skill","description":"Mid-conversation reflection persona. Halts the current thread, re-reads full conversation from original goal forward, runs 5-dimension analysis. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1291,"sizeBytes":5561},{"name":"cs-research-ops-orchestrator.md","path":"docs/agents/cs-research-ops-orchestrator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-research-ops-orchestrator.md","title":"Subagent: cs-research-ops-orchestrator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-research-ops-orchestrator.md -->","frontmatter":{"title":"cs-research-ops-orchestrator — Evidence-first R&D operations lead — AI Coding Agent & Codex Skill","description":"Evidence-first R&D operations lead. Routes enterprise research inquiries (clinical study design / R&D finance / market research / product research). Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1561,"sizeBytes":6521},{"name":"cs-research.md","path":"docs/agents/cs-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-research.md","title":"Subagent: cs-research","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-research.md -->","frontmatter":{"title":"Research Agent — AI Coding Agent & Codex Skill","description":"Hybrid research router + fallback persona. Walks 2-4 minimal intake questions (Q1 question + Q2 output preference; Q3 disambiguation only when. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1399,"sizeBytes":5933},{"name":"cs-roast-judge.md","path":"docs/agents/cs-roast-judge.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-roast-judge.md","title":"Subagent: cs-roast-judge","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-roast-judge.md -->","frontmatter":{"title":"Roast Judge Agent — AI Coding Agent & Codex Skill","description":"Convenes a 5-angle adversarial panel (Critic, Champion, Analyst, Investigator, Customer) on a business idea, then acts as the Judge to deliver one GO. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1223,"sizeBytes":4702},{"name":"cs-scraping-architect.md","path":"docs/agents/cs-scraping-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-scraping-architect.md","title":"Subagent: cs-scraping-architect","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-scraping-architect.md -->","frontmatter":{"title":"Scraping Architect — AI Coding Agent & Codex Skill","description":"Use when the user wants to scrape a website, crawl docs, extract data from PDFs/Excel/CSV/HTML, parse an API response into a dataset, or debug a. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":906,"sizeBytes":3781},{"name":"cs-senior-engineer.md","path":"docs/agents/cs-senior-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-senior-engineer.md","title":"Subagent: cs-senior-engineer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-senior-engineer.md -->","frontmatter":{"title":"Senior Engineer — AI Coding Agent & Codex Skill","description":"Senior Engineer agent for architecture decisions, code review, DevOps, and API design. Orchestrates engineering and engineering-team skills for. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1126,"sizeBytes":4873},{"name":"cs-skill-author.md","path":"docs/agents/cs-skill-author.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-skill-author.md","title":"Subagent: cs-skill-author","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-skill-author.md -->","frontmatter":{"title":"Skill Author Agent — AI Coding Agent & Codex Skill","description":"Skill-author persona. Forcing-question interrogator before any new-skill commit. Runs Matt Pocock's 6-item review checklist as a 6-question gate. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2186,"sizeBytes":8998},{"name":"cs-skill-doctor.md","path":"docs/agents/cs-skill-doctor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-skill-doctor.md","title":"Subagent: cs-skill-doctor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-skill-doctor.md -->","frontmatter":{"title":"Skill Doctor — AI Coding Agent & Codex Skill","description":"Use when someone wants their agent setup graded from real conversation history, asks which of their installed skills actually fire, wonders whether. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":755,"sizeBytes":3118},{"name":"cs-soc2-auditor.md","path":"docs/agents/cs-soc2-auditor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-soc2-auditor.md","title":"Subagent: cs-soc2-auditor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-soc2-auditor.md -->","frontmatter":{"title":"SOC 2 Type II Auditor Agent — AI Coding Agent & Codex Skill","description":"SOC 2 Type II auditor persona — observation-period discipline + AICPA TSC focused. Coordinates with ISO 27001 (75% overlap, the canonical cross-walk. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2178,"sizeBytes":8769},{"name":"cs-spinning-up-deep-rl.md","path":"docs/agents/cs-spinning-up-deep-rl.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-spinning-up-deep-rl.md","title":"Subagent: cs-spinning-up-deep-rl","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-spinning-up-deep-rl.md -->","frontmatter":{"title":"Spinning Up in Deep RL — Knowledge Agent — AI Coding Agent & Codex Skill","description":"Answers from the knowledge base compiled from Spinning Up in Deep RL by Joshua Achiam (OpenAI). Loads the master frameworks first and reads a single. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":502,"sizeBytes":2052},{"name":"cs-syllabus.md","path":"docs/agents/cs-syllabus.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-syllabus.md","title":"Subagent: cs-syllabus","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-syllabus.md -->","frontmatter":{"title":"Syllabus Agent — AI Coding Agent & Codex Skill","description":"Course supplementary reading list persona. Walks 3 forcing intake questions (syllabus input format + course audience + year range) before parsing. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1258,"sizeBytes":4903},{"name":"cs-ux-researcher.md","path":"docs/agents/cs-ux-researcher.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-ux-researcher.md","title":"Subagent: cs-ux-researcher","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-ux-researcher.md -->","frontmatter":{"title":"UX Researcher Agent — AI Coding Agent & Codex Skill","description":"UX research agent for research planning, persona generation, journey mapping, and usability test analysis. Use when product decisions need user. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":5760,"sizeBytes":25926},{"name":"cs-vpe-advisor.md","path":"docs/agents/cs-vpe-advisor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-vpe-advisor.md","title":"Subagent: cs-vpe-advisor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-vpe-advisor.md -->","frontmatter":{"title":"VP of Engineering Advisor Agent — AI Coding Agent & Codex Skill","description":"Throughput-first VP of Engineering advisor for delivery throughput (DORA 4 metrics), engineering hiring funnel, eng team structure (squad/tribe +. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2539,"sizeBytes":10328},{"name":"cs-webinar-marketer.md","path":"docs/agents/cs-webinar-marketer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-webinar-marketer.md","title":"Subagent: cs-webinar-marketer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-webinar-marketer.md -->","frontmatter":{"title":"cs-webinar-marketer — Webinar & Virtual Event Specialist — AI Coding Agent & Codex Skill","description":"Webinar & virtual-event marketing specialist agent. Use when planning, promoting, running, or rescuing a webinar, virtual event, live demo, workshop. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1748,"sizeBytes":7379},{"name":"cs-weekly-review.md","path":"docs/agents/cs-weekly-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-weekly-review.md","title":"Subagent: cs-weekly-review","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-weekly-review.md -->","frontmatter":{"title":"Weekly Review Agent — AI Coding Agent & Codex Skill","description":"Walks a user through a complete GTD weekly review — GET CLEAR (collect, process inboxes to zero, empty your head), GET CURRENT (next actions. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1414,"sizeBytes":5795},{"name":"cs-wiki-ingestor.md","path":"docs/agents/cs-wiki-ingestor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-wiki-ingestor.md","title":"Subagent: cs-wiki-ingestor","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-wiki-ingestor.md -->","frontmatter":{"title":"wiki-ingestor — AI Coding Agent & Codex Skill","description":"Dispatched sub-agent that ingests a new source into an LLM Wiki vault. Reads the source, proposes TL;DR and key claims, identifies which. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1125,"sizeBytes":4444},{"name":"cs-wiki-librarian.md","path":"docs/agents/cs-wiki-librarian.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-wiki-librarian.md","title":"Subagent: cs-wiki-librarian","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-wiki-librarian.md -->","frontmatter":{"title":"wiki-librarian — AI Coding Agent & Codex Skill","description":"Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":954,"sizeBytes":3795},{"name":"cs-wiki-linter.md","path":"docs/agents/cs-wiki-linter.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-wiki-linter.md","title":"Subagent: cs-wiki-linter","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-wiki-linter.md -->","frontmatter":{"title":"wiki-linter — AI Coding Agent & Codex Skill","description":"Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1039,"sizeBytes":4179},{"name":"cs-workflow-architect.md","path":"docs/agents/cs-workflow-architect.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-workflow-architect.md","title":"Subagent: cs-workflow-architect","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-workflow-architect.md -->","frontmatter":{"title":"Workflow Architect Agent — AI Coding Agent & Codex Skill","description":"Workflow-architect persona. Opens every workflow-creation session with the intake question set, infers-and-proposes when the user is vague (never. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1485,"sizeBytes":6253},{"name":"cs-workspace-admin.md","path":"docs/agents/cs-workspace-admin.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/cs-workspace-admin.md","title":"Subagent: cs-workspace-admin","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fcs-workspace-admin.md -->","frontmatter":{"title":"Workspace Admin — AI Coding Agent & Codex Skill","description":"Google Workspace administration agent using the gws CLI. Orchestrates workspace setup, Gmail/Drive/Sheets/Calendar automation, security audits, and. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2098,"sizeBytes":9185},{"name":"devils-advocate.md","path":"docs/agents/devils-advocate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/devils-advocate.md","title":"Subagent: devils-advocate","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fdevils-advocate.md -->","frontmatter":{"title":"Devil's Advocate Agent — AI Coding Agent & Codex Skill","description":"Adversarial reviewer for executive plans, proposals, and decisions. Returns exactly three specific concerns, each severity-rated CRITICAL / HIGH /. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1402,"sizeBytes":6259},{"name":"devops-engineer.md","path":"docs/agents/devops-engineer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/devops-engineer.md","title":"Subagent: devops-engineer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fdevops-engineer.md -->","frontmatter":{"title":"DevOps Engineer — AI Coding Agent & Codex Skill","description":"Builds infrastructure that scales without babysitting. Automates everything worth automating. Monitors before it breaks. Treats clicking in consoles. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1192,"sizeBytes":5405},{"name":"experiment-runner.md","path":"docs/agents/experiment-runner.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/experiment-runner.md","title":"Subagent: experiment-runner","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fexperiment-runner.md -->","frontmatter":{"title":"Experiment Runner Agent — AI Coding Agent & Codex Skill","description":"Runs one iteration of an autoresearch experiment loop. Reads experiment state from .autoresearch/{domain}/{name}/, makes exactly ONE change to the. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":918,"sizeBytes":3932},{"name":"finance-lead.md","path":"docs/agents/finance-lead.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/finance-lead.md","title":"Subagent: finance-lead","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Ffinance-lead.md -->","frontmatter":{"title":"Finance Lead — AI Coding Agent & Codex Skill","description":"Startup CFO who builds models that survive contact with reality. Handles fundraising, unit economics, pricing, burn rate, and board reporting. Speaks. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1207,"sizeBytes":5399},{"name":"growth-marketer.md","path":"docs/agents/growth-marketer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/growth-marketer.md","title":"Subagent: growth-marketer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fgrowth-marketer.md -->","frontmatter":{"title":"Growth Marketer Agent Personality — AI Coding Agent & Codex Skill","description":"Growth marketing specialist for bootstrapped startups and indie hackers. Builds content engines, optimizes funnels, runs launch sequences, and finds. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":2182,"sizeBytes":9907},{"name":"harness-runner.md","path":"docs/agents/harness-runner.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/harness-runner.md","title":"Subagent: harness-runner","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fharness-runner.md -->","frontmatter":{"title":"Harness Runner — AI Coding Agent & Codex Skill","description":"Drives one agent-harness loop iteration to completion — reads the plan and state files, executes exactly one task with the task skill's own tools. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":567,"sizeBytes":2378},{"name":"hub-coordinator.md","path":"docs/agents/hub-coordinator.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/hub-coordinator.md","title":"Subagent: hub-coordinator","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fhub-coordinator.md -->","frontmatter":{"title":"Hub Coordinator Agent — AI Coding Agent & Codex Skill","description":"Coordinator for AgentHub multi-agent collaboration sessions. Dispatches N parallel subagents in isolated git worktrees via the Agent tool, monitors. Agent-native orchestrator for Claude Code, Codex, Gemini CLI."},"isInternal":false,"tokens":1194,"sizeBytes":4823},{"name":"index.md","path":"docs/agents/index.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/index.md","title":"Subagent: index","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Findex.md -->","frontmatter":{"title":"AI Coding Agents — Agent-Native Orchestrators & Codex Skills","description":"106 agent-native orchestrators for Claude Code, Codex CLI, and Gemini CLI — multi-skill AI agents across engineering, product, marketing, and more."},"isInternal":false,"tokens":3893,"sizeBytes":13842},{"name":"karpathy-reviewer.md","path":"docs/agents/karpathy-reviewer.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/agents/karpathy-reviewer.md","title":"Subagent: karpathy-reviewer","category":"subagent-persona","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fagents%2Fkarpathy-reviewer.md -->","frontmatter":{"title":"karpathy-reviewer — AI Coding Agent & Codex Skill","description":"Reviews staged git changes against Karpathy's 4 coding principles. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":964,"sizeBytes":4020},{"name":"cs-capacity-plan.md","path":"docs/commands/cs-capacity-plan.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-capacity-plan.md","title":"Command: /cs-capacity-plan","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-capacity-plan.md -->","frontmatter":{"title":"/cs-capacity-plan — Slash Command for AI Coding Agents","description":"Model headcount + tooling capacity for ops teams (CX/Support/CS/BizOps/IT ops/Finance ops) using Erlang-C queueing math. Sizes the team around the. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":508,"sizeBytes":1956},{"name":"cs-capture.md","path":"docs/commands/cs-capture.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-capture.md","title":"Command: /cs-capture","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-capture.md -->","frontmatter":{"title":"/cs-capture — Slash Command for AI Coding Agents","description":"/cs-capture <dump-text-or-path> — Explicit invocation of the brain-dump organizer. Captures an unstructured stream of thoughts/tasks/ideas and. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":626,"sizeBytes":2336},{"name":"cs-channel-econ.md","path":"docs/commands/cs-channel-econ.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-channel-econ.md","title":"Command: /cs-channel-econ","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-channel-econ.md -->","frontmatter":{"title":"/cs-channel-econ — Slash Command for AI Coding Agents","description":"Direct vs partner-led channel economics — fully-loaded cost-to-serve, channel ROI, optimal channel mix. NOT partnership structure (sibling. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":489,"sizeBytes":2065},{"name":"cs-claude-coach.md","path":"docs/commands/cs-claude-coach.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-claude-coach.md","title":"Command: /cs-claude-coach","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-claude-coach.md -->","frontmatter":{"title":"/cs-claude-coach — Slash Command for AI Coding Agents","description":"Activate the claude-coach skill — personal Claude power-user coaching for the rest of the conversation.. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":505,"sizeBytes":1995},{"name":"cs-claude-rollout.md","path":"docs/commands/cs-claude-rollout.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-claude-rollout.md","title":"Command: /cs-claude-rollout","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-claude-rollout.md -->","frontmatter":{"title":"/cs-claude-rollout — Slash Command for AI Coding Agents","description":"Full Claude Code team-rollout audit - settings across scopes, MCP/plugin inventory, CLAUDE.md layering, and adoption stage.. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":353,"sizeBytes":1426},{"name":"cs-clinical-research.md","path":"docs/commands/cs-clinical-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-clinical-research.md","title":"Command: /cs-clinical-research","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-clinical-research.md -->","frontmatter":{"title":"/cs-clinical-research — Slash Command for AI Coding Agents","description":"Clinical study design. Select and classify endpoints, estimate sample size / power (means / proportions / survival), and score a study plan for a GO. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":444,"sizeBytes":1923},{"name":"cs-commercial-policy.md","path":"docs/commands/cs-commercial-policy.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-commercial-policy.md","title":"Command: /cs-commercial-policy","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-commercial-policy.md -->","frontmatter":{"title":"/cs-commercial-policy — Slash Command for AI Coding Agents","description":"Discount matrix designer + T&C library + exception policy. New ground — designs the policy that deal-desk applies per deal. Direct invocation of the. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1289,"sizeBytes":4975},{"name":"cs-design-system.md","path":"docs/commands/cs-design-system.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-design-system.md","title":"Command: /cs-design-system","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-design-system.md -->","frontmatter":{"title":"/cs-design-system — Slash Command for AI Coding Agents","description":"Run the one-time markdown-html design-system onboarding wizard. Captures brand primary/accent (HEX) + heading/body Google Fonts + design style. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":726,"sizeBytes":2870},{"name":"cs-dl-diagnose.md","path":"docs/commands/cs-dl-diagnose.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-dl-diagnose.md","title":"Command: /cs-dl-diagnose","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-dl-diagnose.md -->","frontmatter":{"title":"/cs-dl-diagnose — Slash Command for AI Coding Agents","description":"/cs-dl-diagnose — Diagnose a training run against Chapter 11's decision tree: read training error before deciding anything, and never diagnose a NaN. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":568,"sizeBytes":2275},{"name":"cs-dossier.md","path":"docs/commands/cs-dossier.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-dossier.md","title":"Command: /cs-dossier","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-dossier.md -->","frontmatter":{"title":"/cs-dossier — Slash Command for AI Coding Agents","description":"/cs-dossier <entity> — Decision-grade entity research with mandatory hypothesis-testing. 6-Q grill-me intake (Q4 hypothesis MANDATORY) → ≥30%. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1652,"sizeBytes":6705},{"name":"cs-engineer-grill.md","path":"docs/commands/cs-engineer-grill.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-engineer-grill.md","title":"Command: /cs-engineer-grill","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-engineer-grill.md -->","frontmatter":{"title":"/cs-engineer-grill — Slash Command for AI Coding Agents","description":"Cross-role engineering grill — Matt Pocock 7 questions per role × 3 roles (fullstack / frontend / backend) = up to 21 forcing questions, one per. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1260,"sizeBytes":4835},{"name":"cs-eval-gate.md","path":"docs/commands/cs-eval-gate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-eval-gate.md","title":"Command: /cs-eval-gate","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-eval-gate.md -->","frontmatter":{"title":"/cs-eval-gate — Slash Command for AI Coding Agents","description":"Just the merge gate - paired statistical comparison of a candidate eval run against baseline, with a PASS / WARN / BLOCK exit code.. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":413,"sizeBytes":1640},{"name":"cs-fable-goal.md","path":"docs/commands/cs-fable-goal.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-fable-goal.md","title":"Command: /cs-fable-goal","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-fable-goal.md -->","frontmatter":{"title":"/cs-fable-goal — Slash Command for AI Coding Agents","description":"/cs-fable-goal — Turn a ramble about something you want made into one polished, autonomous /goal prompt (copy-paste ready). Extracts. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":481,"sizeBytes":2076},{"name":"cs-flux-review.md","path":"docs/commands/cs-flux-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-flux-review.md","title":"Command: /cs-flux-review","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-flux-review.md -->","frontmatter":{"title":"/cs-flux-review — Slash Command for AI Coding Agents","description":"Just the flux gate - mark material fluctuations by your threshold rule and return every explanation that is missing, boilerplate, unquantified or. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":351,"sizeBytes":1498},{"name":"cs-forgetting-audit.md","path":"docs/commands/cs-forgetting-audit.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-forgetting-audit.md","title":"Command: /cs-forgetting-audit","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-forgetting-audit.md -->","frontmatter":{"title":"/cs-forgetting-audit — Slash Command for AI Coding Agents","description":"Run only the blocking forgetting gate on a memory design or store — what leaves, and on what rule.. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":631,"sizeBytes":2632},{"name":"cs-frontend-review.md","path":"docs/commands/cs-frontend-review.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-frontend-review.md","title":"Command: /cs-frontend-review","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-frontend-review.md -->","frontmatter":{"title":"/cs-frontend-review — Slash Command for AI Coding Agents","description":"Frontend engineering review — walks the 7 Matt Pocock forcing questions (device, LCP target, rendering, bundle budget, SEO vs auth, design system. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":975,"sizeBytes":3847},{"name":"cs-grill-commercial.md","path":"docs/commands/cs-grill-commercial.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-grill-commercial.md","title":"Command: /cs-grill-commercial","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-commercial.md -->","frontmatter":{"title":"/cs-grill-commercial — Slash Command for AI Coding Agents","description":"Matt Pocock-style docs-anchored grilling for a Commercial plan, deal, pricing decision, or forecast. Walks the user's plan against the SaaS pricing. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":938,"sizeBytes":3773},{"name":"cs-grill-me.md","path":"docs/commands/cs-grill-me.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-grill-me.md","title":"Command: /cs-grill-me","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-me.md -->","frontmatter":{"title":"/cs-grill-me — Slash Command for AI Coding Agents","description":"/cs-grill-me <path-to-plan> — Start a relentless interrogation of a plan or design. Walks decision tree one branch at a time. One question per turn. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":723,"sizeBytes":2878},{"name":"cs-grill-product.md","path":"docs/commands/cs-grill-product.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-grill-product.md","title":"Command: /cs-grill-product","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-grill-product.md -->","frontmatter":{"title":"/cs-grill-product — Slash Command for AI Coding Agents","description":"Matt Pocock-style interrogation of a product plan against the product canon (Torres, Cagan Transformed, Reinertsen/WSJF, Amplitude North Star. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":814,"sizeBytes":3223},{"name":"cs-harness.md","path":"docs/commands/cs-harness.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-harness.md","title":"Command: /cs-harness","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-harness.md -->","frontmatter":{"title":"/cs-harness — Slash Command for AI Coding Agents","description":"Compile a goal into a verified agent-harness loop for a domain and drive it to close — /cs-harness <domain> <goal>. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":610,"sizeBytes":2421},{"name":"cs-human-gate.md","path":"docs/commands/cs-human-gate.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-human-gate.md","title":"Command: /cs-human-gate","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-human-gate.md -->","frontmatter":{"title":"/cs-human-gate — Slash Command for AI Coding Agents","description":"/cs-human-gate — Get real human review on an artifact and prove it happened. Builds a single-file review page, collects batched feedback as. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1197,"sizeBytes":4536},{"name":"cs-inbox-setup.md","path":"docs/commands/cs-inbox-setup.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-inbox-setup.md","title":"Command: /cs-inbox-setup","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-inbox-setup.md -->","frontmatter":{"title":"/cs-inbox-setup — Slash Command for AI Coding Agents","description":"/cs-inbox-setup — Interactive 8-section interview that builds a personalized 7-file email-triage knowledge base. ~25-31 grill-me questions, one at a. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1616,"sizeBytes":6349},{"name":"cs-internal-comms.md","path":"docs/commands/cs-internal-comms.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-internal-comms.md","title":"Command: /cs-internal-comms","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-internal-comms.md -->","frontmatter":{"title":"/cs-internal-comms — Slash Command for AI Coding Agents","description":"Internal-only change-management comms using ADKAR (Prosci) + Kotter's 8-step. NOT marketing (external) and NOT executive narrative strategy. Direct. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":908,"sizeBytes":3718},{"name":"cs-interview.md","path":"docs/commands/cs-interview.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-interview.md","title":"Command: /cs-interview","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-interview.md -->","frontmatter":{"title":"/cs-interview — Slash Command for AI Coding Agents","description":"Phase 1 — interview the founder into a validated CMA build sheet (primitives table + v1/v2 deferrals + eval plan) via the interview skill. No API key. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":357,"sizeBytes":1393},{"name":"cs-knowledge-ops.md","path":"docs/commands/cs-knowledge-ops.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-knowledge-ops.md","title":"Command: /cs-knowledge-ops","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-knowledge-ops.md -->","frontmatter":{"title":"/cs-knowledge-ops — Slash Command for AI Coding Agents","description":"Company SOP + runbook authoring with 5W2H completeness checks. NOT personal PKM (that's llm-wiki). NOT engineering-specific runbooks. Direct. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":417,"sizeBytes":1663},{"name":"cs-landing.md","path":"docs/commands/cs-landing.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-landing.md","title":"Command: /cs-landing","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-landing.md -->","frontmatter":{"title":"/cs-landing — Slash Command for AI Coding Agents","description":"/cs-landing <product-or-brief> — Generate a premium single-file HTML landing page with GSAP 3D animations, scroll-triggered reveals, and. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1456,"sizeBytes":5722},{"name":"cs-launch.md","path":"docs/commands/cs-launch.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-launch.md","title":"Command: /cs-launch","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-launch.md -->","frontmatter":{"title":"/cs-launch — Slash Command for AI Coding Agents","description":"Main entry / resume for building a Claude Managed Agent. Runs the agent-launcher-orchestrator skill from the current session goal — reads. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":407,"sizeBytes":1529},{"name":"cs-linkedin-analyze.md","path":"docs/commands/cs-linkedin-analyze.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin-analyze.md","title":"Command: /cs-linkedin-analyze","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-analyze.md -->","frontmatter":{"title":"/cs-linkedin-analyze — Slash Command for AI Coding Agents","description":"/cs-linkedin-analyze — Read your own exported LinkedIn post data, report medians and outlier bands rather than misleading means, test candidate. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":924,"sizeBytes":3819},{"name":"cs-linkedin-outreach.md","path":"docs/commands/cs-linkedin-outreach.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin-outreach.md","title":"Command: /cs-linkedin-outreach","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-outreach.md -->","frontmatter":{"title":"/cs-linkedin-outreach — Slash Command for AI Coding Agents","description":"/cs-linkedin-outreach — Build a weekly commenting roster inside a real time budget, and write one outreach message at a time that refuses to be a. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":856,"sizeBytes":3436},{"name":"cs-linkedin-plan.md","path":"docs/commands/cs-linkedin-plan.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin-plan.md","title":"Command: /cs-linkedin-plan","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-plan.md -->","frontmatter":{"title":"/cs-linkedin-plan — Slash Command for AI Coding Agents","description":"/cs-linkedin-plan — Build the positioning brief (objective, audience, 2-4 proof-backed pillars, exclusion list), size a weekly cadence against the. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":742,"sizeBytes":3043},{"name":"cs-linkedin-post.md","path":"docs/commands/cs-linkedin-post.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin-post.md","title":"Command: /cs-linkedin-post","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-post.md -->","frontmatter":{"title":"/cs-linkedin-post — Slash Command for AI Coding Agents","description":"/cs-linkedin-post — Pick the format the material actually supports, draft to the ~140-character mobile fold, and lint 0-100 across mechanics, hook. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":831,"sizeBytes":3325},{"name":"cs-linkedin-profile.md","path":"docs/commands/cs-linkedin-profile.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin-profile.md","title":"Command: /cs-linkedin-profile","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-profile.md -->","frontmatter":{"title":"/cs-linkedin-profile — Slash Command for AI Coding Agents","description":"/cs-linkedin-profile — Audit a LinkedIn profile 0-100, rank every fix by points per hour, score the headline on five dimensions against the. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":727,"sizeBytes":3005},{"name":"cs-linkedin-repurpose.md","path":"docs/commands/cs-linkedin-repurpose.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin-repurpose.md","title":"Command: /cs-linkedin-repurpose","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin-repurpose.md -->","frontmatter":{"title":"/cs-linkedin-repurpose — Slash Command for AI Coding Agents","description":"/cs-linkedin-repurpose — Split an article, talk transcript, README, or write-up into standalone LinkedIn units, score each on whether it survives. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":745,"sizeBytes":3076},{"name":"cs-linkedin.md","path":"docs/commands/cs-linkedin.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-linkedin.md","title":"Command: /cs-linkedin","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-linkedin.md -->","frontmatter":{"title":"/cs-linkedin — Slash Command for AI Coding Agents","description":"/cs-linkedin — Route any organic LinkedIn goal to the right lane (profile / strategy / content / engagement / analytics) after gating it against. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":906,"sizeBytes":3655},{"name":"cs-litreview.md","path":"docs/commands/cs-litreview.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-litreview.md","title":"Command: /cs-litreview","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-litreview.md -->","frontmatter":{"title":"/cs-litreview — Slash Command for AI Coding Agents","description":"/cs-litreview <research-question> — Academic literature orientation. Grill-me intake (question + framework + depth), free-lane recon (PubMed. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":591,"sizeBytes":2549},{"name":"cs-md-document.md","path":"docs/commands/cs-md-document.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-md-document.md","title":"Command: /cs-md-document","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-md-document.md -->","frontmatter":{"title":"/cs-md-document — Slash Command for AI Coding Agents","description":"Convert long-form markdown (specs, RFCs, reports, plans, explainers) into a single-file interactive HTML document. Runs the md-document pipeline. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1085,"sizeBytes":4008},{"name":"cs-meeting-actions.md","path":"docs/commands/cs-meeting-actions.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-meeting-actions.md","title":"Command: /cs-meeting-actions","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-meeting-actions.md -->","frontmatter":{"title":"/cs-meeting-actions — Slash Command for AI Coding Agents","description":"/cs-meeting-actions — Turn raw meeting notes into an owned action-item checklist: extracts checkboxes, ACTION:/TODO: lines, '@name will …' and 'Name. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":822,"sizeBytes":3362},{"name":"cs-memory.md","path":"docs/commands/cs-memory.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-memory.md","title":"Command: /cs-memory","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-memory.md -->","frontmatter":{"title":"/cs-memory — Slash Command for AI Coding Agents","description":"Inspect, trace, and adopt the tiered agent-memory store (status | why | contested | adopt | forget). 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":443,"sizeBytes":1766},{"name":"cs-notebooklm.md","path":"docs/commands/cs-notebooklm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-notebooklm.md","title":"Command: /cs-notebooklm","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-notebooklm.md -->","frontmatter":{"title":"/cs-notebooklm — Slash Command for AI Coding Agents","description":"/cs-notebooklm — NotebookLM browser automation. Action-routing intake (Q1: read / add source / Studio output / create new) + per-action Q2-Q4. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1281,"sizeBytes":4891},{"name":"cs-pm-loop.md","path":"docs/commands/cs-pm-loop.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-pm-loop.md","title":"Command: /cs-pm-loop","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pm-loop.md -->","frontmatter":{"title":"/cs-pm-loop — Slash Command for AI Coding Agents","description":"Drive a project-delivery goal through a bounded agentic loop — Jira MCP snapshot → flow/sprint analytics bridge → routed sub-skill execution →. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":740,"sizeBytes":2987},{"name":"cs-pm.md","path":"docs/commands/cs-pm.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-pm.md","title":"Command: /cs-pm","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-pm.md -->","frontmatter":{"title":"/cs-pm — Slash Command for AI Coding Agents","description":"Top-level project-management router. Classifies a PM inquiry across 8 lanes (sprint/flow, portfolio health, Jira, Confluence, admin, templates. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":616,"sizeBytes":2714},{"name":"cs-product.md","path":"docs/commands/cs-product.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-product.md","title":"Command: /cs-product","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-product.md -->","frontmatter":{"title":"/cs-product — Slash Command for AI Coding Agents","description":"Top-level product-team router. Classifies a product inquiry across 16 lanes (prioritization, OKRs, UX, design system, competitive, analytics. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":561,"sizeBytes":2382},{"name":"cs-research.md","path":"docs/commands/cs-research.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-research.md","title":"Command: /cs-research","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-research.md -->","frontmatter":{"title":"/cs-research — Slash Command for AI Coding Agents","description":"/cs-research <question> — Default research entry point. Hybrid router: classifies question deterministically and either delegates to specialist. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1787,"sizeBytes":7299},{"name":"cs-rfp-respond.md","path":"docs/commands/cs-rfp-respond.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-rfp-respond.md","title":"Command: /cs-rfp-respond","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-rfp-respond.md -->","frontmatter":{"title":"/cs-rfp-respond — Slash Command for AI Coding Agents","description":"Structured RFP/RFI/RFQ response with win-theme injection and proof-point matrix. NOT free-form proposal authoring (that's. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":470,"sizeBytes":1965},{"name":"cs-roast.md","path":"docs/commands/cs-roast.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-roast.md","title":"Command: /cs-roast","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-roast.md -->","frontmatter":{"title":"/cs-roast — Slash Command for AI Coding Agents","description":"/cs-roast — Convene a 5-angle adversarial panel (Critic, Champion, Analyst, Investigator, Customer) on an idea, then a Judge delivers one GO /. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":1067,"sizeBytes":4040},{"name":"cs-run-without-you.md","path":"docs/commands/cs-run-without-you.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-run-without-you.md","title":"Command: /cs-run-without-you","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-run-without-you.md -->","frontmatter":{"title":"/cs-run-without-you — Slash Command for AI Coding Agents","description":"Phase 4 — make the agent run without you. Turn a graded agent into a recurring POSIX-cron scheduled deployment (optionally self-grading each firing). 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":631,"sizeBytes":2518},{"name":"cs-skill-doctor.md","path":"docs/commands/cs-skill-doctor.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-skill-doctor.md","title":"Command: /cs-skill-doctor","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-skill-doctor.md -->","frontmatter":{"title":"/cs-skill-doctor — Slash Command for AI Coding Agents","description":"Grade the agent setup from real local session history — rubric-scored, evidence-gated, rendered as one local shareable report.. Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":637,"sizeBytes":2552},{"name":"cs-spinning-up-deep-rl.md","path":"docs/commands/cs-spinning-up-deep-rl.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-spinning-up-deep-rl.md","title":"Command: /cs-spinning-up-deep-rl","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-spinning-up-deep-rl.md -->","frontmatter":{"title":"/cs-spinning-up-deep-rl — Slash Command for AI Coding Agents","description":"/cs-spinning-up-deep-rl [topic | framework | chNN] — query the knowledge base compiled from Spinning Up in Deep RL by Joshua Achiam (OpenAI). Use. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":453,"sizeBytes":1900},{"name":"cs-webinar.md","path":"docs/commands/cs-webinar.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/cs-webinar.md","title":"Command: /cs-webinar","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fcs-webinar.md -->","frontmatter":{"title":"/cs-webinar — Slash Command for AI Coding Agents","description":"/cs-webinar — Webinar & virtual-event marketing workflow. Plan a webinar from scratch (sized backward from the business goal), rescue one whose. 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Slash command for Claude Code, Codex CLI, Gemini CLI."},"isInternal":false,"tokens":631,"sizeBytes":2385},{"name":"sprint-health.md","path":"docs/commands/sprint-health.md","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/docs/commands/sprint-health.md","title":"Command: /sprint-health","category":"command-prompt","format":"markdown","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=docs%2Fcommands%2Fsprint-health.md -->","frontmatter":{"title":"/sprint-health — Slash Command for AI Coding Agents","description":"Sprint health scoring and velocity analysis for agile teams. Usage: /sprint-health <analyze|velocity> [options]. 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Every converter reads this config via config_loader.py before rendering.","argument-hint":"[--defaults | --show | --reset | --set key=value | --scope global|project]"},"isInternal":false,"tokens":738,"sizeBytes":2972},{"name":"marketplace.json","path":".claude-plugin/marketplace.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.claude-plugin/marketplace.json","title":"Claude Plugin Marketplace Catalog","category":"marketplace","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.claude-plugin%2Fmarketplace.json -->","isInternal":false,"tokens":12247,"sizeBytes":50098},{"name":"plugin.json","path":".codex-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.codex-plugin/plugin.json","title":"claude-code-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=.codex-plugin%2Fplugin.json -->","frontmatter":{"name":"claude-code-skills","version":"2.14.1","description":"398 production-ready skills across 20 domains — engineering, marketing, product, compliance, C-level advisory, research, business operations, and more. 766 Python tools, 877 reference guides, 123 agents (cs-* + personas), 157 slash commands, 104 marketplace plugins. The largest open-source skills library for AI coding agents.","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://alirezarezvani.github.io/claude-skills/","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","keywords":["openai-codex","codex-plugin","claude-code","agent-skills","engineering","marketing","product","compliance","devops","security","ai-agents"],"skills":"./.codex/skills/","interface":{"type":"cli","composerIcon":"./assets/icon.png","displayName":"Claude Code Skills","shortDescription":"398 production-ready skills for AI coding agents across 20 domains","longDescription":"The largest open-source skills library for AI coding agents. 398 skills covering engineering (architecture, DevOps, security, AI/ML, agent tooling), marketing (SEO, AEO, CRO, content), product management, C-level advisory, regulatory compliance (ISO 13485, SOC 2, GDPR), project management, research and research operations, business operations, commercial, finance, and personal productivity. Includes 766 stdlib-only Python CLI tools, 877 reference guides, 123 orchestration agents, and 157 slash commands. Works with Codex, Claude Code, Gemini CLI, Cursor, Hermes Agent, Mistral Vibe, and 7 more tools.","developerName":"Alireza Rezvani","category":"Coding","capabilities":["Read","Write"],"websiteURL":"https://alirezarezvani.github.io/claude-skills/","defaultPrompt":["Design an AWS architecture for my project","Run a security pen test on this codebase","Create a product requirements document","Audit this page for accessibility (WCAG 2.2)"],"brandColor":"#0969da"}},"isInternal":false,"tokens":572,"sizeBytes":2198},{"name":"plugin.json","path":"agent-launcher/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/agent-launcher/.claude-plugin/plugin.json","title":"agent-launcher-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=agent-launcher%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"agent-launcher-skills","description":"Turn Anthropic's launch-your-agent reference skill into a full domain plugin for building Claude Managed Agents (CMA). Every session starts with a goal (./my-agent/goal.json, surfaced by an opt-in AGENT_LAUNCHER_SESSION=1 SessionStart hook and driven by /cs-goal); a deterministic loop_compiler.py compiles that goal into a grade->iterate loop (CMA user.define_outcome self-grading, bounded by max_iterations), a recurring cron scheduled-deployment loop (run without you), or a single-pass interview->stage->launch workflow. 6 skills: agent-launcher-orchestrator (context: fork goal router) + interview (build sheet: primitives table + v1/v2 deferrals + eval plan) + stage-launch (validated env/agent/session/kickoff payloads + resumable BYOK curl launch script that never prints the key) + grade-iterate (outcome/rubric + verdict reader + held-back eval scaffold) + run-without-you (POSIX-cron deployment + NEXT-DIRECTIONS) + wrap-up (primitive inventory + regenerated overview HTML + next upgrades). 18 stdlib-only deterministic scaffolder tools (no network/API calls; live launches emitted as BYOK curl), 4 agents (orchestrator + interviewer + grader + deployer), 8 commands, opt-in SessionStart/SessionEnd hooks, 5 shared references, 4 assets. Validators enforce CMA limits (<=20 skills/session, <=8 memory stores, <=20 roster / 25 threads / depth-1 multiagent, max_iterations 1..20, <=20 creds/vault, <=1000 deployments/org). Inspired by anthropics/launch-your-agent (Apache-2.0); independent re-implementation, not a fork.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/agent-launcher","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/agent-launcher-orchestrator","./skills/interview","./skills/stage-launch","./skills/grade-iterate","./skills/run-without-you","./skills/wrap-up"]},"isInternal":false,"tokens":533,"sizeBytes":2080},{"name":"plugin.json","path":"business-growth/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-growth/.claude-plugin/plugin.json","title":"business-growth-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-growth%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"business-growth-skills","description":"4 business & growth skills plus a router: customer success manager (health scoring, churn), sales engineer (RFP analysis, PoC planning), revenue operations (pipeline, forecast accuracy, GTM), and contract & proposal writer. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/business-growth","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":192,"sizeBytes":684},{"name":"plugin.json","path":"business-operations/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/business-operations/.claude-plugin/plugin.json","title":"business-operations-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=business-operations%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"business-operations-skills","description":"6 BizOps skills + 1 orchestrator: process-mapper (BPMN + bottleneck + cycle-time), vendor-management (SLA + risk + scorecard), capacity-planner (Erlang-C queueing math for ops teams), internal-comms (ADKAR + Kotter 8-step change comms), knowledge-ops (SOP + runbook authoring with 5W2H validation, context: fork), procurement-optimizer (UNSPSC-aligned spend categorization + supplier consolidation). Orchestrator skill uses context: fork to route inquiries to the right sub-skill via Matt Pocock grill discipline. 18 stdlib-only Python tools, 24+ reference docs each citing ≥7 authoritative sources, asset templates per skill. Distinct from business-growth (external sales) and c-level-advisor (strategic).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/business-operations","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/business-operations-skills","./skills/process-mapper","./skills/vendor-management","./skills/capacity-planner","./skills/internal-comms","./skills/knowledge-ops","./skills/procurement-optimizer"]},"isInternal":false,"tokens":351,"sizeBytes":1325},{"name":"plugin.json","path":"c-level-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/.claude-plugin/plugin.json","title":"c-level-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"c-level-skills","description":"33 C-level advisory skills (persona layer: install the separate companion c-level-agents plugin for 13 cs-* persona agents + 21 /c-level-agents:* slash commands). Complete virtual board of directors with CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO advisors plus General Counsel, Chief Data Officer, Chief AI Officer, Chief Customer Officer, and VP of Engineering (delivery throughput DORA analyzer, eng hiring funnel calculator, eng team structure designer), executive mentor, founder coach, Chief of Staff router, board meetings, decision logger, board deck builder, scenario war room, competitive intel, org health diagnostic, M&A playbook, international expansion, culture architect, change management, strategic alignment, and the founder-mode plugin (office-hours, boardroom, brief/decide/execute/post-mortem pipeline, cross-model consensus, decision freeze).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":310,"sizeBytes":1243},{"name":"plugin.json","path":"c-level-advisor/arquiteto-de-empresa/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/arquiteto-de-empresa/.claude-plugin/plugin.json","title":"arquiteto-de-empresa","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Farquiteto-de-empresa%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"arquiteto-de-empresa","description":"Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md/log.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, and generates conformant markdown concepts. 3 stdlib tools: scaffold_bundle (bundle scaffolding), okf_linter (validates type/reserved files/links), index_generator (regenerates the index.md files). Standalone-installable; also bundled in c-level-skills.","version":"2.14.1","author":{"name":"leoal","url":"https://github.com/alirezarezvani/claude-skills"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/arquiteto-de-empresa","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":284,"sizeBytes":1095},{"name":"plugin.json","path":"c-level-advisor/chief-ai-officer-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/chief-ai-officer-advisor/.claude-plugin/plugin.json","title":"chief-ai-officer-advisor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fchief-ai-officer-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"chief-ai-officer-advisor","description":"Chief AI Officer advisory: model build-vs-buy calculator (API vs fine-tune vs build with 3-year TCO across 6 paths + breakeven balancing economics with practical feasibility), AI risk classifier (EU AI Act tier with 7 Article citations + US state patchwork: NYC LL 144, CO AI Act, IL HB 53, CA SB 1001, IL BIPA + industry overlays for FDA AI/ML, CFPB Circular 2023-03, NYDFS Reg 23, NAIC, ECOA, Fed SR 11-7), AI cost economics (API vs self-hosted breakeven with 2026 pricing across A100/H100, utilization reality, hidden costs). 4 in-depth references each citing 5+ authoritative sources. Stdlib-only. Standalone-installable; also bundled in c-level-skills. Strategic only - does not duplicate engineering AI/ML skills.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/chief-ai-officer-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":327,"sizeBytes":1131},{"name":"plugin.json","path":"c-level-advisor/chief-customer-officer-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/chief-customer-officer-advisor/.claude-plugin/plugin.json","title":"chief-customer-officer-advisor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fchief-customer-officer-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"chief-customer-officer-advisor","description":"Chief Customer Officer advisory for startups: retention decomposition analyzer (honest GRR vs NRR + 7-category churn taxonomy), customer segmentation designer (4-tier framework + ICP fit scoring + kill list), CS coverage calculator (pooled vs named CSM models + ratio math + 12-month hiring plan). 4 in-depth references: retention decomposition, customer segmentation strategy, CS coverage model, CS team org evolution (CSM vs Support vs AM vs IM vs CS Ops). Stdlib-only. Standalone-installable; also bundled in c-level-skills. Strategic only - does not duplicate business-growth tactical CS skills.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/chief-customer-officer-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":263,"sizeBytes":1023},{"name":"plugin.json","path":"c-level-advisor/chief-data-officer-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/chief-data-officer-advisor/.claude-plugin/plugin.json","title":"chief-data-officer-advisor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fchief-data-officer-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"chief-data-officer-advisor","description":"Chief Data Officer advisory: AI training data audit (origin x class x use-case matrix with GDPR Art. 6 + EU AI Act citations -> GO/MITIGATE/NO-GO per source), data product strategy picker (warehouse vs lakehouse vs mesh + 6-layer build-vs-buy + 12-month sequencing), data asset valuator (strategic value 0-10 + M&A multiplier with carve-out penalties + 3 ranked productization paths). 4 references answering one decision each: training rights, data product strategy, customer-data-as-asset, data team org evolution. Stdlib-only. Standalone-installable; also bundled in c-level-skills. Strategic only - does not duplicate engineering data skills.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/chief-data-officer-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":280,"sizeBytes":1061},{"name":"plugin.json","path":"c-level-advisor/executive-mentor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/executive-mentor/.claude-plugin/plugin.json","title":"executive-mentor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fexecutive-mentor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"executive-mentor","description":"Adversarial thinking partner for founders and executives. Stress-tests plans, prepares for board meetings, navigates hard decisions, and forces honest post-mortems.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/executive-mentor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":161,"sizeBytes":560},{"name":"plugin.json","path":"c-level-advisor/general-counsel-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/general-counsel-advisor/.claude-plugin/plugin.json","title":"general-counsel-advisor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fgeneral-counsel-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"general-counsel-advisor","description":"General Counsel advisory for startups: contract risk scanner (12 founder-killer patterns: auto-renew traps, uncapped indemnity, vague IP, MFN pricing, missing DPA, one-sided venue, broad non-solicit, perpetual license-back, etc.) and term sheet analyzer (0-100 founder-friendliness score across 12 dimensions: liquidation preference, anti-dilution, option pool, board, vesting, drag-along, protective provisions, info rights, dividends, valuation). 3 in-depth references: contracts playbook (7 startup contract types), IP + regulatory landscape (HIPAA, GDPR, FDA, fintech, EU AI Act + SOC 2 to ISO sequencing), term sheet decoder. Stdlib-only. Standalone-installable; also bundled in c-level-skills. NOT a substitute for licensed counsel.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/general-counsel-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":301,"sizeBytes":1148},{"name":"plugin.json","path":"c-level-advisor/vpe-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-advisor/vpe-advisor/.claude-plugin/plugin.json","title":"vpe-advisor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-advisor%2Fvpe-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"vpe-advisor","description":"VP of Engineering advisory: delivery throughput analyzer (DORA 4 metrics + cycle-time bottleneck identification), eng hiring funnel calculator (7-stage conversion + pipeline gap + weakest-stage fixes), eng team structure designer (squad/tribe model + manager-trigger + director-trigger + span-of-control). 4 in-depth references: DORA framework, eng hiring funnel, eng team structure (Conway's Law), production discipline (on-call, incidents, deployment, SLOs). Stdlib-only. Standalone-installable; also bundled in c-level-skills. NOT a CTO skill — VPE owns how the team ships, CTO owns what to build.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-advisor/vpe-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":266,"sizeBytes":991},{"name":"plugin.json","path":"c-level-agents/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/c-level-agents/.claude-plugin/plugin.json","title":"c-level-agents","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=c-level-agents%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"c-level-agents","description":"Founder-mode executive team plugin: 13 cs-* C-suite agents (CFO, CMO, CRO, CPO, COO, CHRO, CISO, Chief of Staff, General Counsel, Chief Data Officer, Chief AI Officer, Chief Customer Officer, VP of Engineering) plus 21 /c-level-agents:* slash commands for forcing-question office hours (incl. /c-level-agents:vpe-review), multi-role boardroom deliberation, strategic sprint pipeline, and meta routing. Wraps the 33 c-level skills (including vpe-advisor with delivery throughput DORA analyzer + eng hiring funnel calculator + eng team structure designer) with cognitive gearing and artifact handoffs.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/c-level-agents","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":266,"sizeBytes":975},{"name":"plugin.json","path":"commercial/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/commercial/.claude-plugin/plugin.json","title":"commercial-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=commercial%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"commercial-skills","description":"7 Commercial skills + 1 orchestrator: pricing-strategist (Van Westendorp WTP + packaging + model picker), deal-desk (margin + discount routing + redline scoring), partnerships-architect (5-tier classifier + joint GTM + revshare modeler), channel-economics (cost-to-serve + ROI + channel mix optimizer), commercial-policy (data-backed discount matrix + exception flow + policy linter), rfp-responder (Shipley-method structured RFP/RFI/RFQ response + win-theme + winrate predictor; context: fork for heavy intake), commercial-forecaster (4Q-weighted bookings + cohort NRR/GRR + funnel-confidence with mandatory assumption disclosure). Orchestrator skill uses context: fork. 21 stdlib-only Python tools, 28+ reference docs. Distinct from business-growth (sales execution), c-level-advisor/cro-advisor (strategic CRO), finance (close-and-report).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/commercial","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/commercial-skills","./skills/pricing-strategist","./skills/deal-desk","./skills/partnerships-architect","./skills/channel-economics","./skills/commercial-policy","./skills/rfp-responder","./skills/commercial-forecaster"]},"isInternal":false,"tokens":383,"sizeBytes":1471},{"name":"plugin.json","path":"compliance-os/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/compliance-os/.claude-plugin/plugin.json","title":"compliance-os","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=compliance-os%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"compliance-os","description":"Compliance OS — meta-orchestrator for multi-framework compliance programs. Configure-then-operate four stdlib Python tools: framework_selector.py (input: company profile across industry/geography/AI/medical/financial/headcount; output: applicable frameworks ranked across all 9 supported: ISO 27001, 13485, 42001, 14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR), cross_framework_mapper.py (input: 1+ framework control libraries; output: unified control matrix with overlap percentage + mapping confidence + unified evidence requirements per merged control), audit_simulator.py (input: framework scope; output: mock internal audit with 8-15 finding scenarios across 5 severity levels + interview questions per control), evidence_pool_generator.py (input: enabled framework configs; output: consolidated evidence checklist with reuse map). 4 in-depth references citing ISO 19011, IIA Standards, AICPA AT-C, NIST CSF, COSO ERM. Plus 3 cs-* persona agents (cs-compliance-officer, cs-aims-iso42001, cs-ai-act-compliance) + 3 slash commands (/compliance-os:compliance-readiness, /compliance-os:aims-audit, /compliance-os:ai-act-readiness). Reuses the 14 existing ra-qm-team skills and the 2 new compliance-team-* plugins.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/compliance-os","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/compliance-os","./skills/compliance-readiness","./skills/aims-audit","./skills/ai-act-readiness","./skills/iso27001-audit-prep","./skills/iso13485-audit-prep","./skills/gdpr-audit-prep","./skills/soc2-audit-prep","./skills/fda-qsr-audit-prep"]},"isInternal":false,"tokens":511,"sizeBytes":1877},{"name":"plugin.json","path":"engineering-team/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/.claude-plugin/plugin.json","title":"engineering-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"engineering-skills","description":"32 production-ready engineering skills: architecture, frontend, backend, fullstack, QA, DevOps, security, AI/ML, data engineering, Playwright, self-improving agent, security suite (adversarial-reviewer, ai-security, cloud-security, incident-response, red-team, threat-detection), Stripe integration, TDD guide, Google Workspace CLI, a11y audit, Snowflake development, and more. v2.8.1 augments senior-fullstack / senior-frontend / senior-backend with karpathy-coder + Matt Pocock discipline: each ships a 7-question forcing-question library, 4 customization profiles (JSON, swappable), a deterministic decision engine, a composition map into POWERFUL specialists, plus cs-fullstack-engineer / cs-frontend-engineer / cs-backend-engineer orchestrator agents (context: fork) invokable by other agents via /cs-fullstack-review, /cs-frontend-review, /cs-backend-review, /cs-engineer-grill. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":346,"sizeBytes":1335},{"name":"plugin.json","path":"engineering-team/a11y-audit/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/a11y-audit/.claude-plugin/plugin.json","title":"a11y-audit","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fa11y-audit%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"a11y-audit","description":"WCAG 2.2 accessibility audit and fix skill for React, Next.js, Vue, Angular, Svelte, and HTML. Static scanner detecting 20+ violation types, contrast checker with suggest mode, framework-specific fix patterns, CI-friendly exit codes.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team/a11y-audit","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":183,"sizeBytes":618},{"name":"plugin.json","path":"engineering-team/google-workspace-cli/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/google-workspace-cli/.claude-plugin/plugin.json","title":"google-workspace-cli","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fgoogle-workspace-cli%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"google-workspace-cli","version":"2.14.1","description":"Google Workspace administration via the gws CLI (github.com/googleworkspace/cli, install: npm i -g @googleworkspace/cli). Authenticate and automate Gmail, Drive, Sheets, Calendar, Docs, Chat, and Tasks. 5 Python tools, 3 reference guides, a local catalog of 43 recipe command templates, and 10 persona bundles. Verify generated commands against gws --help.","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"],"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team/google-workspace-cli"},"isInternal":false,"tokens":208,"sizeBytes":761},{"name":"plugin.json","path":"engineering-team/playwright-pro/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/playwright-pro/.claude-plugin/plugin.json","title":"pw","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fplaywright-pro%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"pw","description":"Production-grade Playwright testing toolkit. Generate tests from specs, fix flaky failures, migrate from Cypress/Selenium, with optional (manually enabled) TestRail/BrowserStack integrations. 55+ ready-to-use templates, 3 specialized agents, smart reporting that plugs into your existing workflow.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team/playwright-pro","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":185,"sizeBytes":678},{"name":"plugin.json","path":"engineering-team/self-improving-agent/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/self-improving-agent/.claude-plugin/plugin.json","title":"si","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fself-improving-agent%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"si","version":"2.14.1","description":"Self-Improving Agent: curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills. Provides /si:memory-review, /si:promote, /si:extract, /si:memory-status, and /si:remember slash commands.","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"],"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team/self-improving-agent"},"isInternal":false,"tokens":188,"sizeBytes":622},{"name":"plugin.json","path":"engineering-team/snowflake-development/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/snowflake-development/.claude-plugin/plugin.json","title":"snowflake-development","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering-team%2Fsnowflake-development%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"snowflake-development","description":"Snowflake SQL, data pipelines (Dynamic Tables, Streams+Tasks), Cortex AI functions, Snowpark Python, and dbt integration. Includes query helper script, 3 reference guides, and troubleshooting.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team/snowflake-development","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":168,"sizeBytes":599},{"name":"plugin.json","path":"engineering/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/.claude-plugin/plugin.json","title":"engineering-advanced-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"engineering-advanced-skills","description":"42 advanced engineering skills: agent designer, agent workflow designer, RAG architect, database designer + schema designer + SQL assistant, migration architect, observability designer, dependency auditor, changelog generator (with semantic version bumper and hotfix/rollback procedures), API design reviewer, API test suite builder, CI/CD pipeline builder, MCP server builder, skill security auditor, skill tester, performance profiler, focused-fix, browser-automation, full-page-screenshot, git-worktree-manager, monorepo-navigator, codebase-onboarding, interview-system-designer, runbook-generator, spec-driven-workflow, secrets-vault-manager, env-secrets-manager, pr-review-expert, self-eval, tc-tracker (task context tracker with lifecycle and handoff format), feature-flags-architect, kubernetes-operator, chaos-engineering, ship-gate (pre-production 8-category audit with deploy-intent intercept), slo-architect (SLO designer, error-budget calculator with multi-window burn-rate alerts, SLO reviewer per Google SRE Workbook), tech-debt-tracker, boost-asio-pro (async C++ networking with Boost.Asio), minimalist (YAGNI-first efficiency ladder), strict-api (verify every API before calling it), agent-regression-evals (repeated-trial eval gate with paired statistics and flake detection), and coding-agent-rollout (team settings, MCP and CLAUDE.md governance with adoption tracking). Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills","./boost-asio-pro","./minimalist","./strict-api"]},"isInternal":false,"tokens":454,"sizeBytes":1915},{"name":"plugin.json","path":"engineering/agent-harness/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-harness/.claude-plugin/plugin.json","title":"agent-harness","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-harness%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"agent-harness","description":"Turn any domain folder of skills into a bounded agentic loop: a manifest builder inventories a domain's skills/tools/checks, a goal compiler turns a goal into a verifiable task plan (refusing vague goals with forcing questions), and a JSON-backed loop controller drives execute->verify->close with retry caps, controller-run verification (no verification theater), human escalation on exhausted budgets, and a close gate that refuses while any task is unverified. Ships 3 stdlib Python tools, 18 committed per-domain harness manifests + JSON schema, 3 references citing the 2024-2026 agent-harness canon, harness-runner agent + /cs-harness command. Use when an agent should pick up a goal and drive it to a verified close across a domain.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/agent-harness","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/agent-harness"]},"isInternal":false,"tokens":283,"sizeBytes":1130},{"name":"plugin.json","path":"engineering/agent-memory/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-memory/.claude-plugin/plugin.json","title":"agent-memory","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-memory%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"agent-memory","description":"A four-tier memory ladder for Claude Code where promotion is earned by recurrence, not asserted by confidence. L0 raw transcripts are never injected; L1 candidate atoms are gitignored and recalled on lexical relevance per prompt; L2 project context loads once per session; L3 stable persona is always loaded. Promotion from L1 to L2 requires at least three distinct sessions spanning at least two distinct calendar days (a stated claim needs two sessions, still spread across days; a deterministically verified claim is the only single-observation path), and L2 to L3 requires two distinct projects and thirty days. Two gates refuse rather than guess: a claim whose text was altered by the seventeen-pattern redaction pass never promotes on evidence alone, and a claim with an open contradiction freezes until a human resolves it, found by reverse join because the newer atom carries no flag. Three hooks run the loop unattended and every one fails open. Nothing reaches a committed CLAUDE.md without an explicit human adopt that backs both files up first. Ships five stdlib scripts, three hooks, a cs-memory-curator agent, a /cs-memory command, a JSON schema, a sixty-nine-check example validator, and a design document with its open decisions ranked by what they gate.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/agent-memory","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/agent-memory"]},"isInternal":false,"tokens":380,"sizeBytes":1667},{"name":"plugin.json","path":"engineering/agent-regression-evals/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agent-regression-evals/.claude-plugin/plugin.json","title":"agent-regression-evals","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagent-regression-evals%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"agent-regression-evals","description":"Prove an agent, prompt, model or tool change did not make the agent worse. Three deterministic stdlib scripts: a trajectory checker that grades tool-call paths (strict / unordered / subset / superset match modes, argument matching, forbidden tools that block in every mode, call ceilings); a flake detector that classifies each case as stable or flaky from repeated trials and reports pass@k and pass^k with Wilson intervals; and a paired regression gate that averages trials per case, tests per-case differences with a t-based CI and an exact one-sided McNemar test, and blocks the merge on a significant drop, a critical-case regression, a dropped case, or a quarantine entry without owner and expiry. Ships cs-eval-gatekeeper agent, /cs-agent-evals and /cs-eval-gate commands, 3 references, and a CI job example.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/agent-regression-evals","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/agent-regression-evals"]},"isInternal":false,"tokens":315,"sizeBytes":1242},{"name":"plugin.json","path":"engineering/agenthub/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/agenthub/.claude-plugin/plugin.json","title":"agenthub","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fagenthub%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"agenthub","description":"Multi-agent collaboration plugin for Claude Code. Spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any problem that benefits from diverse solutions. Evaluate by metric or LLM judge, merge the winner. 7 slash commands, agent templates, git DAG orchestration, message board coordination.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/agenthub","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":188,"sizeBytes":714},{"name":"plugin.json","path":"engineering/autoresearch-agent/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/autoresearch-agent/.claude-plugin/plugin.json","title":"autoresearch-agent","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fautoresearch-agent%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"autoresearch-agent","description":"Autonomous experiment loop that optimizes any file by a measurable metric. 5 slash commands, 8 evaluators, configurable loop intervals (10min to monthly).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/autoresearch-agent","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":163,"sizeBytes":550},{"name":"plugin.json","path":"engineering/behuman/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/behuman/.claude-plugin/plugin.json","title":"behuman","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbehuman%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"behuman","description":"Self-Mirror consciousness loop for human-like AI responses. Adds inner dialogue (Self → Mirror → Conscious Response) to make AI output feel authentic, not robotic. Zero dependencies — pure prompt technique.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/behuman","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":172,"sizeBytes":595},{"name":"plugin.json","path":"engineering/book-to-skill/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/book-to-skill/.claude-plugin/plugin.json","title":"book-to-skill","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fbook-to-skill%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"book-to-skill","description":"Converts books, documentation folders, and source collections (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into structured agent skills: a master SKILL.md with core frameworks and a topic index, on-demand chapter files, a glossary, a patterns file, and a decision cheatsheet. Ships 4 stdlib-only tools (multi-format extractor with invisible-Unicode sanitization, four-family generated-skill validator, pre/post-flight token budget estimator, and a plugin emitter that wraps a compiled skill as an installable claude-skills package), 5 references citing 7-8 sources each (including the full step-by-step conversion workflow), a cs-book-to-skill agent, and /cs-book-to-skill + /cs-book-to-plugin commands. Use when the user wants to study a document with an agent, apply an author's frameworks while working, turn internal docs or standards into a reusable knowledge base, or package a compiled book skill as a plugin.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/book-to-skill","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/book-to-skill"]},"isInternal":false,"tokens":343,"sizeBytes":1335},{"name":"plugin.json","path":"engineering/caveman/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/caveman/.claude-plugin/plugin.json","title":"caveman","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcaveman%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"caveman","description":"Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Enhanced from Matt Pocock's MIT-licensed caveman skill (https://github.com/mattpocock/skills) with: (1) stdlib Python tools (text compressor, token-savings estimator, caveman-style linter), (2) 3 reference docs citing 5+ authoritative sources each (compression principles, technical communication patterns, when caveman backfires), (3) cs-caveman-mode persona agent + /cs-caveman slash command. Matt's voice and persistence rules preserved verbatim per MIT. Use when user says \"caveman mode\", \"talk like caveman\", \"use caveman\", \"less tokens\", \"be brief\", or invokes /caveman.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/caveman","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/caveman"]},"isInternal":false,"tokens":302,"sizeBytes":1113},{"name":"plugin.json","path":"engineering/chaos-engineering/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/chaos-engineering/.claude-plugin/plugin.json","title":"chaos-engineering","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fchaos-engineering%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"chaos-engineering","description":"End-to-end chaos engineering discipline: design experiments with hypothesis + steady-state metric + blast radius + abort criteria, calculate risk score against error budget, and generate blameless postmortems. 3 stdlib Python tools (experiment_designer, blast_radius_calculator, experiment_postmortem), 4 references on chaos principles + experiment design + 7-attack taxonomy + tooling landscape (Chaos Toolkit/Mesh/Litmus/Gremlin/AWS FIS/DIY), templates for plans + postmortems, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (chaos targets).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/chaos-engineering","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":270,"sizeBytes":1025},{"name":"plugin.json","path":"engineering/claude-coach/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/claude-coach/.claude-plugin/plugin.json","title":"power-user-coach","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fclaude-coach%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"power-user-coach","description":"Personal Claude power-user coach. On first activation, delivers a personalized, ranked cheat-code glossary filtered to the user's use cases. On every subsequent turn, scans for missed power-user opportunities and surfaces at most ONE ⚡ tip when a tip would genuinely 10x the next attempt. Silence is the default. Ships SKILL.md, cheat-codes glossary, coaching-rules decision tree, and three stdlib Python tools (cheat-code filter, prompt rater, 5-gate tip classifier). Includes cs-claude-coach agent persona and /cs-claude-coach slash command.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/claude-coach","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/claude-coach"]},"isInternal":false,"tokens":260,"sizeBytes":949},{"name":"plugin.json","path":"engineering/code-tour/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/code-tour/.claude-plugin/plugin.json","title":"code-tour","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcode-tour%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"code-tour","description":"Create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Supports 10 developer personas (vibecoder, new joiner, architect, security reviewer, etc.), all CodeTour step types, and SMIG description formula.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/code-tour","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":188,"sizeBytes":645},{"name":"plugin.json","path":"engineering/coding-agent-rollout/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/coding-agent-rollout/.claude-plugin/plugin.json","title":"coding-agent-rollout","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcoding-agent-rollout%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"coding-agent-rollout","description":"Roll Claude Code out to a team with guardrails you can check. Four deterministic stdlib scripts: a settings linter that reads shared, local, user and managed settings together (array merge, deny-ask-allow order) and blocks blanket shell allows, pre-approved destructive commands and committed credentials; an MCP and plugin inventory that blocks anything missing from your approved list or holding a literal secret, and flags unpinned or plain-http servers; a CLAUDE.md layering audit that resolves every layer and @import and flags broken imports, contradictions, secrets and resident size; and a privacy-safe adoption tracker that turns local session files into counts only and classifies the rollout as PILOT, SPREADING, EMBEDDED or STALLED. Ships cs-claude-code-rollout agent, /cs-claude-rollout and /cs-claude-settings-lint commands, 3 references, a baseline managed-settings policy and a four-phase rollout plan.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/coding-agent-rollout","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/coding-agent-rollout"]},"isInternal":false,"tokens":326,"sizeBytes":1339},{"name":"plugin.json","path":"engineering/collab-proof/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/collab-proof/.claude-plugin/plugin.json","title":"collab-proof","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fcollab-proof%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"collab-proof","description":"Assisted retrospective: after a session, calibrates what Claude contributed vs what the developer drove. LLM-assessed 4-frame analysis, zero dependencies.","version":"2.14.1","author":{"name":"dong7812","url":"https://github.com/dong7812"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/collab-proof","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/collab-proof"]},"isInternal":false,"tokens":159,"sizeBytes":545},{"name":"plugin.json","path":"engineering/data-quality-auditor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/data-quality-auditor/.claude-plugin/plugin.json","title":"data-quality-auditor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdata-quality-auditor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"data-quality-auditor","description":"Audit datasets for completeness, consistency, accuracy, and validity. 3 stdlib-only Python tools: data profiler with DQS scoring, missing value analyzer with MCAR/MAR/MNAR classification, and multi-method outlier detector.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/data-quality-auditor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":176,"sizeBytes":622},{"name":"plugin.json","path":"engineering/deep-learning-book/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/deep-learning-book/.claude-plugin/plugin.json","title":"deep-learning-book","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdeep-learning-book%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"deep-learning-book","description":"Study companion and working knowledge base for the Deep Learning textbook by Goodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org. Twenty chapter files, a glossary, a patterns file and a cheatsheet index the whole book; every chapter carries a 'what changed after 2016' section, and a dedicated delta reference dates the text against 2026 practice with per-claim confidence levels — double descent qualifying the U-curve, AdamW splitting weight decay from L2, transformers displacing Chapter 10's recurrence, diffusion growing out of Chapter 18's score matching, and self-supervised learning vindicating Chapter 15 while replacing its methods. Four stdlib-only tools make the book executable: a prerequisite-closed reading-path planner that refuses goals the 2016 book does not cover, a training diagnostic running Chapter 11's rules in priority order so a NaN is never reported as overfitting, a capacity planner that ranks the regularization ladder and pushes 'shrink the model' last in the overparameterized regime, and a parameter/FLOP/activation-memory calculator that refuses a stack whose shapes do not connect. Deliberately a companion, not a compilation: the book is copyrighted, so nothing here reproduces its text — every chapter file is original synthesis linking to the official free chapter. Use when studying or teaching this book, planning a route through it, or checking whether one of its recommendations is still current.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/deep-learning-book","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/deep-learning-book"]},"isInternal":false,"tokens":434,"sizeBytes":1893},{"name":"plugin.json","path":"engineering/demo-video/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/demo-video/.claude-plugin/plugin.json","title":"demo-video","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdemo-video%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"demo-video","description":"Create polished demo videos from screenshots and scene descriptions. Orchestrates playwright, ffmpeg, and edge-tts to produce product walkthroughs, feature showcases, and marketing teasers with story structure, scene design system, and narration guidance.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/demo-video","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":170,"sizeBytes":635},{"name":"plugin.json","path":"engineering/docker-development/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/docker-development/.claude-plugin/plugin.json","title":"docker-development","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fdocker-development%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"docker-development","description":"Docker and container development agent skill and plugin for Dockerfile optimization, docker-compose orchestration, multi-stage builds, and container security hardening. Covers build performance, layer caching, and production-ready container patterns.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/docker-development","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":166,"sizeBytes":646},{"name":"plugin.json","path":"engineering/feature-flags-architect/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/feature-flags-architect/.claude-plugin/plugin.json","title":"feature-flags-architect","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Ffeature-flags-architect%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"feature-flags-architect","description":"End-to-end feature-flag discipline: classify, ship, ramp, retire. Detects stale flags as debt, generates phased rollout plans (ring/linear/log/cohort), and audits every flag for a documented kill switch. 3 stdlib Python tools, 4 references on flag taxonomy + provider trade-offs (LaunchDarkly/GrowthBook/Statsig/Unleash/Flipt/DIY) + rollout strategies + lifecycle. /flag-cleanup slash command. Cross-tool compatible.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/feature-flags-architect","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":232,"sizeBytes":822},{"name":"plugin.json","path":"engineering/grill-me/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/grill-me/.claude-plugin/plugin.json","title":"grill-me","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fgrill-me%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"grill-me","description":"Relentless plan-and-design interrogator. Walks the decision tree of a plan one branch at a time, asking forcing questions sequentially with recommended answers. Explores codebase to resolve answers where possible. Enhanced from Matt Pocock's MIT-licensed grill-me skill (https://github.com/mattpocock/skills) with: (1) stdlib Python tools (decision-tree extractor, question generator, session-state tracker), (2) 3 reference docs citing 5+ authoritative sources each (forcing-question patterns, decision-tree completeness, when to stop grilling), (3) cs-grill-master persona agent + /cs-grill-me slash command. Matt's relentless one-at-a-time interview discipline preserved verbatim per MIT. Use when user wants to stress-test a plan, get grilled on their design, or says \"grill me\".","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/grill-me","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/grill-me"]},"isInternal":false,"tokens":303,"sizeBytes":1170},{"name":"plugin.json","path":"engineering/grill-with-docs/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/grill-with-docs/.claude-plugin/plugin.json","title":"grill-with-docs","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fgrill-with-docs%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"grill-with-docs","description":"Docs-anchored grilling session — interrogates a plan against the project's existing language (CONTEXT.md) and recorded decisions (docs/adr/), updating those files inline as terminology and decisions crystallise. Derived from Matt Pocock's MIT-licensed grill-with-docs skill (https://github.com/mattpocock/skills) with: (1) 3 stdlib Python tools (CONTEXT.md linter, ADR scanner, glossary-to-code consistency check), (2) 3 reference docs each citing 7+ authoritative sources on ubiquitous language, ADR practice, and CONTEXT.md as a living artifact, (3) cs-grill-with-docs persona agent + /cs-grill-with-docs slash command. Matt's interview discipline + domain-awareness rules + ADR-when-3-criteria-are-met gate preserved verbatim per MIT.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/grill-with-docs","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/grill-with-docs"]},"isInternal":false,"tokens":313,"sizeBytes":1145},{"name":"plugin.json","path":"engineering/handoff/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/handoff/.claude-plugin/plugin.json","title":"handoff-engineering","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhandoff%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"handoff-engineering","description":"Conversation-handoff document generator. Compacts the current conversation into a markdown handoff so a fresh agent can continue. References existing artifacts (PRDs, plans, ADRs, issues, commits) by path/URL — does not duplicate them. Enhanced from Matt Pocock's MIT-licensed handoff skill (https://github.com/mattpocock/skills) with: (1) stdlib Python tools (template generator, artifact deduplicator, skill recommender), (2) 3 reference docs citing 5+ authoritative sources each (handoff structure, deduplication discipline, next-session skill matching), (3) cs-handoff-author persona agent + /cs-handoff slash command. Matt's no-duplication discipline preserved verbatim per MIT. Use when user wants to hand off the current conversation to a fresh agent or starts a new session that picks up prior work.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/handoff","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/handoff"]},"isInternal":false,"tokens":311,"sizeBytes":1203},{"name":"plugin.json","path":"engineering/helm-chart-builder/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/helm-chart-builder/.claude-plugin/plugin.json","title":"helm-chart-builder","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhelm-chart-builder%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"helm-chart-builder","description":"Helm chart development agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw — chart scaffolding, values design, template patterns, dependency management, security hardening, and chart testing.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/helm-chart-builder","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":175,"sizeBytes":616},{"name":"plugin.json","path":"engineering/hivemind/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/hivemind/.claude-plugin/plugin.json","title":"hivemind","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhivemind%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"hivemind","description":"Opt-in plugin: orchestrate opencode workers from Claude Code to cut token costs. Claude Code plans, reviews and merges; opencode runs single workers or parallel swarms (scout/coder/tester) on free or open-source models with worktree isolation. Requires the third-party opencode CLI and account, and by default worker prompts and code are sent to opencode's hosted service; point --model at a local model to keep code on your machine. Not part of any domain bundle; install it only if you want that data flow.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/hivemind","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./"]},"isInternal":false,"tokens":237,"sizeBytes":878},{"name":"plugin.json","path":"engineering/human-gate/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/human-gate/.claude-plugin/plugin.json","title":"human-gate","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fhuman-gate%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"human-gate","description":"The human-verification lane for an agent loop. Builds a single-file HTML review page for a Markdown or HTML artifact (opens over file://, makes no network request of its own, and sanitizes reviewed HTML -- on* handlers, javascript: URLs and iframes are dropped so a draft cannot execute inside the page), collects batched feedback as a structured batch.v1 artifact instead of chat prose, and runs a gate that refuses to close while a BLOCKER is open, the reviewer is unnamed, the sidecar changed after collection, the round carries unresolved integrity problems (a mistyped severity silently downgrades to NIT, so a real blocker can be lost to a typo), or nobody has reviewed at all. Non-blocking by design: no poll loop, a headless guard, a round cap, and escalation on exhaustion. Feedback lands in a hand-writable Markdown sidecar, so the loop still works over SSH and in CI where no browser exists. Use before shipping a plan, spec, RFC, report, or any irreversible action, or when the user says 'let me review that', 'get sign-off', or 'don't ship until I've seen it'. The human counterpart to agent-harness's machine verification -- NOT a content humanizer (see content-humanizer / behuman).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/human-gate","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/human-gate"]},"isInternal":false,"tokens":393,"sizeBytes":1588},{"name":"plugin.json","path":"engineering/karpathy-coder/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/karpathy-coder/.claude-plugin/plugin.json","title":"karpathy-coder","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkarpathy-coder%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"karpathy-coder","description":"Active coding discipline enforcer based on Karpathy's 4 principles: surface assumptions, keep it simple, make surgical changes, define verifiable goals. Ships 4 Python tools (complexity_checker, diff_surgeon, assumption_linter, goal_verifier), a review agent, /karpathy-check slash command, and a pre-commit hook. All tools stdlib-only.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/karpathy-coder","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":208,"sizeBytes":724},{"name":"plugin.json","path":"engineering/kubernetes-operator/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/kubernetes-operator/.claude-plugin/plugin.json","title":"kubernetes-operator","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fkubernetes-operator%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"kubernetes-operator","description":"End-to-end Kubernetes Operator discipline: CRD design, reconcile-loop patterns, and OperatorHub Capability Levels. Ships CRD validator, reconcile-loop linter, and capability auditor (3 stdlib Python tools), 4 references on the operator pattern + CRD design + reconcile patterns + framework comparison (controller-runtime/kubebuilder/operator-sdk/metacontroller/KOPF), CRD + Go controller skeletons, and /operator-audit slash command. NOT a generic k8s skill — specifically the Operator pattern.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/kubernetes-operator","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":229,"sizeBytes":897},{"name":"plugin.json","path":"engineering/llm-cost-optimizer/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-cost-optimizer/.claude-plugin/plugin.json","title":"llm-cost-optimizer","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-cost-optimizer%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"llm-cost-optimizer","description":"Use when you need to reduce LLM API spend, control token usage, route between models by cost/quality, implement prompt caching, or build cost observability for AI features. Triggers: 'my AI costs are ","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/llm-cost-optimizer","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":176,"sizeBytes":596},{"name":"plugin.json","path":"engineering/llm-wiki/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/llm-wiki/.claude-plugin/plugin.json","title":"llm-wiki","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fllm-wiki%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"llm-wiki","description":"Turn Claude Code + Obsidian into a second brain. The LLM incrementally ingests sources into a persistent, interlinked markdown wiki — building entity/concept/source pages, flagging contradictions, maintaining an index and log. Knowledge compounds instead of being re-derived by RAG on every query. Inspired by Karpathy's LLM Wiki gist. Ships SKILL, 3 sub-agents, 5 slash commands, 8 Python tools (stdlib only), full vault templates, and cross-tool compatibility (Claude Code, Codex CLI, Cursor, Antigravity, OpenCode, Gemini CLI).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/llm-wiki","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":255,"sizeBytes":911},{"name":"plugin.json","path":"engineering/memory-engineering/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/memory-engineering/.claude-plugin/plugin.json","title":"memory-engineering","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fmemory-engineering%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"memory-engineering","description":"Engineer an agent's forgetting, not just its remembering. Four deterministic stdlib scripts implement the four lenses of agent memory: a cost profiler that splits construction from query spend and reports cost per correct answer (construction energy exceeds total query energy across 300 queries in the Stanford characterization); an architecture picker that scores the four paradigm families — long-context, flat RAG, structure-augmented RAG, agentic — disqualifies on hard constraints, names the cost the winning choice makes you pay, and refuses to pick when the top two tie; a density auditor that classifies every record in a real memory directory or JSONL export as FACT / SKILL / LOG / PROSE, finds near-duplicates, and flags stale and time-relative wording; and a forgetting-policy linter that fails any design with no forgetting rule or that auto-merges contradictions. Ships cs-memory-engineer agent, /cs-memory-engineering and /cs-forgetting-audit commands, 4 references citing 7 sources each, and a seven-question forcing worksheet.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/memory-engineering","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/memory-engineering"]},"isInternal":false,"tokens":339,"sizeBytes":1463},{"name":"plugin.json","path":"engineering/prompt-governance/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/prompt-governance/.claude-plugin/plugin.json","title":"prompt-governance","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fprompt-governance%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"prompt-governance","description":"Use when managing prompts in production at scale: versioning prompts, running A/B tests on prompts, building prompt registries, preventing prompt regressions, or creating eval pipelines for production","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/prompt-governance","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":166,"sizeBytes":594},{"name":"plugin.json","path":"engineering/security-guidance/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/security-guidance/.claude-plugin/plugin.json","title":"security-guidance","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fsecurity-guidance%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"security-guidance","description":"PreToolUse security reminder hook for Claude Code. Catches 12 common security anti-patterns in Edit/Write/MultiEdit operations BEFORE they happen — command injection (exec, os.system, subprocess shell=True), XSS (innerHTML, dangerouslySetInnerHTML, document.write), SQL injection (f-string queries, .format), unsafe deserialization (pickle, yaml.unsafe_load), code injection (eval, new Function), and GitHub Actions workflow injection. Session-state caching prevents duplicate warnings; 30-day auto-cleanup of stale state files. Disable per-session with ENABLE_SECURITY_REMINDER=0. Ported from David Dworken's MIT-licensed plugin at github.com/alirezarezvani/aeo-box.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/security-guidance","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/security-guidance"]},"isInternal":false,"tokens":273,"sizeBytes":1081},{"name":"plugin.json","path":"engineering/skill-doctor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skill-doctor/.claude-plugin/plugin.json","title":"skill-doctor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskill-doctor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"skill-doctor","description":"Grade an agent setup from real conversation history. Harvests recent local Claude Code and Codex sessions scoped to one repo, condenses and secret-redacts transcripts (12-pattern redactor, chmod-0600 artifacts, nothing ever uploaded), has the agent judge each transcript against two fixed rubrics (efficiency, code-quality — labels only, preserved verbatim from upstream), then runs a deterministic aggregation gate that derives every number from the label tables, refuses scores for unsampled sessions and suggestions that cite no scored session, and renders one self-contained HTML report (no JS, no CDN, dark-mode, print-to-PDF). Proposed skill edits stay staged as diffs until an explicit per-skill yes, and zero suggestions is a valid, reportable success. Ships cs-skill-doctor agent, /cs-skill-doctor command, 3 stdlib tools, 2 verbatim rubrics, 3 references citing 7 sources each, and the 3 handoff-shape assets.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/skill-doctor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/skill-doctor"]},"isInternal":false,"tokens":330,"sizeBytes":1318},{"name":"plugin.json","path":"engineering/skillopt-sleep/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/skillopt-sleep/.claude-plugin/plugin.json","title":"skillopt-sleep","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fskillopt-sleep%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"skillopt-sleep","description":"Nightly offline self-evolution for this repo's Claude agent: harvests past Claude Code sessions (read-only), mines recurring tasks, replays them offline on your own API budget, and consolidates what it learns into validated CLAUDE.md memory and SKILL.md skills behind a held-out validation gate, staged for review (nothing live changes without /skillopt-sleep adopt). Default backend is mock (no API spend); vendored from microsoft/SkillOpt with safety-hardening patches -- see attribution.derivation_note. Use when the user wants their agent to learn from how this repo's skills are actually used, asks about a nightly/offline sleep or dream cycle, memory/skill consolidation, or invokes /skillopt-sleep.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/skillopt-sleep","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/skillopt-sleep"]},"isInternal":false,"tokens":287,"sizeBytes":1108},{"name":"plugin.json","path":"engineering/slo-architect/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/slo-architect/.claude-plugin/plugin.json","title":"slo-architect","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fslo-architect%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"slo-architect","description":"End-to-end SLO/SLI/error-budget discipline per Google SRE Workbook. Ships SLO designer (refuses to render without required fields), error-budget calculator with multi-window burn-rate alert thresholds (PromQL-shaped), and SLO reviewer that catches the 7 common bugs (target too high, window too short, no SLI definition, CPU-as-SLI, etc.). 4 references on principles + SLI design + error budget math + composition with feature-flags-architect/chaos-engineering/kubernetes-operator. Asset templates for SLO YAML and error budget policy. /slo-design slash command. NOT a generic observability skill.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/slo-architect","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":262,"sizeBytes":983},{"name":"plugin.json","path":"engineering/spinning-up-deep-rl/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/spinning-up-deep-rl/.claude-plugin/plugin.json","title":"spinning-up-deep-rl","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fspinning-up-deep-rl%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"spinning-up-deep-rl","description":"Knowledge base from \"Spinning Up in Deep RL\" by Joshua Achiam (OpenAI, MIT-licensed). Use when applying Achiam's frameworks for RL fundamentals and MDPs, the model-free algorithm taxonomy, policy gradient derivations, the six reference algorithms (VPG, TRPO, PPO, DDPG, TD3, SAC), debugging silently-failing RL code, or running rigorous multi-seed RL experiments.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://github.com/alirezarezvani"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/spinning-up-deep-rl","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/spinning-up-deep-rl"]},"isInternal":false,"tokens":230,"sizeBytes":790},{"name":"plugin.json","path":"engineering/statistical-analyst/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/statistical-analyst/.claude-plugin/plugin.json","title":"statistical-analyst","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fstatistical-analyst%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"statistical-analyst","description":"Hypothesis testing, A/B experiment analysis, sample size calculation, and confidence intervals. 3 stdlib-only Python tools with Z-test, t-test, chi-square, effect sizes, power analysis, and Wilson score intervals.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/statistical-analyst","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":176,"sizeBytes":611},{"name":"plugin.json","path":"engineering/terraform-patterns/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/terraform-patterns/.claude-plugin/plugin.json","title":"terraform-patterns","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fterraform-patterns%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"terraform-patterns","description":"Terraform infrastructure-as-code agent skill and plugin for module design patterns, state management strategies, provider configuration, security hardening, and CI/CD plan/apply workflows. Covers mono-repo vs multi-repo, workspaces, policy-as-code, and drift detection.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/terraform-patterns","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":182,"sizeBytes":665},{"name":"plugin.json","path":"engineering/universal-scraping-architect/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/universal-scraping-architect/.claude-plugin/plugin.json","title":"universal-scraping-architect","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Funiversal-scraping-architect%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"universal-scraping-architect","description":"A universal scraping skill with intelligent routing, token budget tracking, and quota awareness. Supports Firecrawl and local Python extraction (firecrawl, pandas, requests, beautifulsoup4). Free-tier compatible, BYOK.","version":"2.14.1","author":{"name":"Mehansh Barthwal","url":"https://github.com/mehanshbarthwal-lab"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/universal-scraping-architect","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":181,"sizeBytes":647},{"name":"plugin.json","path":"engineering/workflow-builder/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/workflow-builder/.claude-plugin/plugin.json","title":"workflow-builder","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fworkflow-builder%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"workflow-builder","description":"Workflow-builder skill: design and write deterministic multi-agent workflow scripts (.js files in .claude/workflows/) for Claude Code's Workflow tool (CLAUDE_CODE_WORKFLOWS=1, /workflows). Every session opens with an intake question set; when the user is vague, a stdlib recommendation engine infers and proposes a topology with rationale instead of stalling. Ships 3 stdlib Python tools (intake recommendation engine, .js validator enforcing the pure-literal-meta / no-non-determinism / guarded-loop / parallel-thunk rules, topology scaffolder), 3 references citing 7-8 authoritative sources each (full API surface, orchestration patterns, decision + intake guide), templates + a runnable example, cs-workflow-architect persona agent + /cs-workflow-build slash command. Use when building, scaffolding, or running a custom Claude Code workflow or orchestrating sub-agents (fan-out, pipeline, loop, judge-panel).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/workflow-builder","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/workflow-builder"]},"isInternal":false,"tokens":326,"sizeBytes":1320},{"name":"plugin.json","path":"engineering/write-a-skill/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/write-a-skill/.claude-plugin/plugin.json","title":"write-a-skill","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fwrite-a-skill%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"write-a-skill","description":"Skill-author skill: create new agent skills with proper structure, progressive disclosure, and bundled resources. Enhanced from Matt Pocock's MIT-licensed write-a-skill (https://github.com/mattpocock/skills) with: (1) stdlib Python validation tools (description validator, structure validator, review-checklist runner), (2) 3 reference docs citing 5+ authoritative sources each (progressive disclosure principles, description design patterns, quality gates), (3) cs-skill-author persona agent + /cs-write-a-skill slash command. Matt's voice and 3-phase workflow (Gather → Draft → Review) preserved verbatim per his MIT license. Use when user wants to create, write, build, or author a new agent skill.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/write-a-skill","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/write-a-skill"]},"isInternal":false,"tokens":287,"sizeBytes":1105},{"name":"plugin.json","path":"engineering/zero-hallucination-coder/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering/zero-hallucination-coder/.claude-plugin/plugin.json","title":"zero-hallucination-coder","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=engineering%2Fzero-hallucination-coder%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"zero-hallucination-coder","description":"A disciplined coding pipeline that grounds code in verified structure before a line is written: Discuss -> Map -> Decompose -> Execute -> Verify, with a lazy-senior-dev YAGNI ladder that deletes unnecessary code first. No invented APIs, no assumed imports, no placeholder code. Opt-in for high-stakes, complex, or multi-file work; not for trivial edits. Synthesizes four MIT/open-source projects (Ralph, GSD Core, Graphify, Ponytail).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/engineering/zero-hallucination-coder","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/zero-hallucination-coder"]},"isInternal":false,"tokens":241,"sizeBytes":867},{"name":"plugin.json","path":"finance/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/.claude-plugin/plugin.json","title":"finance-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"finance-skills","description":"3 finance skills plus a router: financial analyst (ratio analysis, DCF valuation, budgeting, forecasting), SaaS metrics coach (ARR, MRR, churn, CAC, LTV, NRR, Quick Ratio, 12-month projections), and month-end close (close calendar critical path, reconciliation proof, flux explanation gate). 10 Python automation tools. The business-investment-advisor skill ships as a separate nested plugin. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/finance","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":231,"sizeBytes":838},{"name":"plugin.json","path":"finance/business-investment-advisor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/business-investment-advisor/.claude-plugin/plugin.json","title":"business-investment-advisor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fbusiness-investment-advisor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"business-investment-advisor","description":"Business investment analysis and capital allocation advisor. Use when evaluating whether to invest in equipment, real estate, a new business, hiring, technology, or any capital expenditure. Also use f","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/finance/business-investment-advisor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":167,"sizeBytes":610},{"name":"plugin.json","path":"finance/month-end-close/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/finance/month-end-close/.claude-plugin/plugin.json","title":"month-end-close","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=finance%2Fmonth-end-close%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"month-end-close","description":"Run a faster, provable month-end close. Three deterministic stdlib scripts: a close calendar planner that orders tasks by dependency, finds the critical path and slack, maps WD+n deadlines to dates and blocks on missing owners, missing or self-review of key controls and a critical path past the target workday; a reconciliation matcher that matches GL to bank or sub-ledger by reference then amount and date, builds the proof, ages reconciling items and blocks on any unexplained difference or preparer-as-reviewer; and a flux analyzer that applies your materiality rule and refuses material fluctuations explained with boilerplate or without a quantified driver. Ships cs-close-controller agent, /cs-month-end-close and /cs-flux-review commands, 3 references citing COSO 2013 and PCAOB AS 2201 / AS 2305 / SAPA 11, and a reconciliation sign-off template.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/finance/month-end-close","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/month-end-close"]},"isInternal":false,"tokens":310,"sizeBytes":1258},{"name":"plugin.json","path":"loop-library/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/loop-library/.claude-plugin/plugin.json","title":"loop-library","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=loop-library%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"loop-library","description":"Discover, compare, audit, repair, adapt, and design repeatable AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs. Vendored verbatim from the Forward Future Loop Library (MIT).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/loop-library","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./"]},"isInternal":false,"tokens":171,"sizeBytes":599},{"name":"plugin.json","path":"markdown-html/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/markdown-html/.claude-plugin/plugin.json","title":"markdown-html-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=markdown-html%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"markdown-html-skills","description":"Convert long markdown files into world-class, single-file, lightly-interactive HTML. v2.10.3 completes the markdown-html/ domain — adds md-slides (slide-deck converter: arrow-key / Space / PgDn / Home/End / P keyboard navigation + presenter mode with split-view clock + notes + next-slide preview + URL-hash deep linking + @media print page-per-slide for PDF export) on top of md-review v2.10.2 (code-review: 2-col diff + severity-tagged margin annotations + WCAG-1.4.1 badges + mandatory named reviewer footer), md-document v2.10.1 (long-form: sticky TOC + scrollspy + search + code-copy + Prism.js autoloader), and the v2.10.0 foundation: markdown-html-orchestrator (context: fork; deterministic doc-type classifier; refuses < 100 lines per Shihipar; refuses without onboarding) + design-system (10-question onboarding wizard; WCAG-AA-validated 12-token palette; project > global > defaults precedence; MARKDOWN_HTML_NO_CONFIG=1 bypass). 15 stdlib-only Python tools (3 per skill across 5 skills), 15 references citing 5-7 sources each, 4 template/schema assets. Inspired by Thariq Shihipar's Claude Code HTML output essay (Medium, 2026). Outputs are single self-contained .html files; only externals are Google Fonts CSS and (opt-in per skill) Prism.js CDN. Domain complete.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/markdown-html","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/markdown-html-orchestrator","./skills/design-system","./skills/md-document","./skills/md-review","./skills/md-slides"]},"isInternal":false,"tokens":473,"sizeBytes":1796},{"name":"plugin.json","path":"marketing-skill/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/.claude-plugin/plugin.json","title":"marketing-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"marketing-skills","description":"44 production-ready marketing skills across 8 pods: Content (copywriting, content strategy, content production), SEO + AEO (traditional audits, schema markup, programmatic SEO, site architecture, plus Answer Engine Optimization for LLM citation in ChatGPT/Perplexity/Claude/Gemini/Mistral), CRO (A/B testing, forms, popups, signup flows, pricing, onboarding), Channels (email sequences, social media, paid ads, cold email, X/Twitter growth), Growth (launch strategy, referral programs, free tools), Intelligence (competitor analysis, marketing psychology, analytics tracking), and Sales enablement. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/marketing-skill","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":274,"sizeBytes":1046},{"name":"plugin.json","path":"marketing-skill/skills/aeo/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/aeo/.claude-plugin/plugin.json","title":"aeo","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Faeo%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"aeo","description":"Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO (which optimizes for search rankings), AEO optimizes for citation in LLM-generated responses. Ships 3 stdlib Python tools (aeo_audit.py for E-E-A-T + structure scoring, aeo_optimizer.py for content rewriting in conservative/balanced/aggressive modes, citation_tracker.py for local-first citation ledger), 3 references citing 7+ authoritative sources each (E-E-A-T methodology, per-LLM citation patterns, AEO-vs-SEO strategy), and industry-aware thresholds for 8 industries (saas/healthcare/finance/legal/ecommerce/b2b/media/education) with stricter YMYL calibration. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'E-E-A-T audit', 'LLM citation strategy', 'answer engine optimization'.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/marketing-skill/skills/aeo","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./"]},"isInternal":false,"tokens":343,"sizeBytes":1271},{"name":"plugin.json","path":"marketing-skill/skills/youtube-full/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/skills/youtube-full/.claude-plugin/plugin.json","title":"youtube-full","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fskills%2Fyoutube-full%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"youtube-full","description":"YouTube transcripts, video search, channel browsing, playlist extraction, and new-upload monitoring with open-source tools (yt-dlp, youtube-transcript-api, YouTube RSS). No account or API key needed; a hosted transcript API is mentioned only as an optional, user-chosen fallback.","version":"2.14.1","author":{"name":"therohitdas","url":"https://github.com/therohitdas"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/marketing-skill/skills/youtube-full","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./"]},"isInternal":false,"tokens":182,"sizeBytes":668},{"name":"plugin.json","path":"marketing-skill/video-content-strategist/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing-skill/video-content-strategist/.claude-plugin/plugin.json","title":"video-content-strategist","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing-skill%2Fvideo-content-strategist%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"video-content-strategist","description":"Use when planning video content strategy, writing video scripts, optimizing YouTube channels, building short-form video pipelines (Reels, TikTok, Shorts), or repurposing long-form content into video. ","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/marketing-skill/video-content-strategist","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":172,"sizeBytes":612},{"name":"plugin.json","path":"marketing/landing/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/landing/.claude-plugin/plugin.json","title":"landing","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flanding%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"landing","description":"Premium single-file HTML landing page generator with GSAP 3D animations, scroll-triggered effects, and mouse-parallax depth. Forcing 3-4 question grill-me intake (product+pitch, audience register, brand overrides, tone) locks down positioning before any copy or markup is written. Outputs a single self-contained HTML file (Claude Code) or HTML artifact (Claude.ai) with all CSS/JS inline — only externals are Google Fonts + GSAP via CDN. Configurable brand colors via CSS custom property overrides. Source spec: megaprompts/04-landing-megaprompt.md (PR #657). Distinct from product-team/skills/landing-page-generator (which outputs Next.js TSX for conversion-optimized lead-gen) — this skill is for premium visual one-pagers with motion design.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/marketing/landing","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/landing"]},"isInternal":false,"tokens":294,"sizeBytes":1129},{"name":"plugin.json","path":"marketing/linkedin/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/marketing/linkedin/.claude-plugin/plugin.json","title":"linkedin","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=marketing%2Flinkedin%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"linkedin","description":"Organic LinkedIn presence, end to end, with the platform rules enforced in code. An orchestrator (context: fork) gates every request against LinkedIn's User Agreement §8.2 — refusing automation, scraping, engagement pods, bulk DMs, fake identity, fabricated proof, and named third-party automation tools, each with a compliant substitute — then routes to one of five sub-skills. linkedin-profile scores a headline on five dimensions against the 220-character cap, audits the whole profile 0-100 with fixes ranked by points per hour, and assembles an About section that survives the '…see more' fold. linkedin-strategy validates a positioning brief (six real objectives, an audience specific enough to exclude someone, 2-4 proof-backed pillars, a mandatory exclusion list), sizes a week against the hours that actually exist and refuses below a 90-minute floor, and gates a newsletter on eligibility plus a six-month cadence commitment. linkedin-content lints posts 0-100 across mechanics, hook, integrity, and accessibility — blocking on the 3,000-character cap, engagement bait, and Unicode pseudo-bold that screen readers cannot read — picks the format the material actually supports, and splits long sources into standalone units against a reuse ledger. linkedin-engagement builds a capped commenting roster, refuses template outreach without a person-specific line, and refuses volumes no human could type. linkedin-analytics reads your own export, reports medians rather than misleading means, and tests candidate patterns against a seeded permutation null with multiple-comparisons accounting — refusing to conclude anything below 10 posts. 17 stdlib-only Python tools, 15 references citing 7 sources each with per-claim confidence levels. No LinkedIn credentials, no API calls, nothing auto-sent.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/linkedin-skills","./skills/linkedin-profile","./skills/linkedin-strategy","./skills/linkedin-content","./skills/linkedin-engagement","./skills/linkedin-analytics"]},"isInternal":false,"tokens":524,"sizeBytes":2377},{"name":"plugin.json","path":"product-team/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/.claude-plugin/plugin.json","title":"product-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"product-skills","description":"13 production-ready product skills bundled in this plugin: product-skills fork-orchestrator with continuous-discovery loop (deterministic 16-lane router, Torres cadence tracker, OST linter), product manager toolkit (RICE, PRDs), product strategist, UX researcher, UI design system, competitive teardown, landing page generator, SaaS scaffolder, product analytics, experiment designer, product discovery, roadmap communicator, spec-to-repo. Companion standalone plugins: agile-product-owner, code-to-prd, apple-hig-expert, research-summarizer. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/product-team","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":258,"sizeBytes":993},{"name":"plugin.json","path":"product-team/agile-product-owner/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/agile-product-owner/.claude-plugin/plugin.json","title":"agile-product-owner","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fagile-product-owner%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"agile-product-owner","description":"Agile product ownership for backlog management and sprint execution. User story generation (INVEST-compliant), acceptance criteria patterns (Given/When/Then, rule-based, checklist), epic breakdown with 5 split techniques, sprint planning with velocity-based capacity math, and weighted backlog prioritization. Includes user_story_generator Python tool.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/product-team/agile-product-owner","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":192,"sizeBytes":751},{"name":"plugin.json","path":"product-team/apple-hig-expert/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/apple-hig-expert/.claude-plugin/plugin.json","title":"apple-hig-expert","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fapple-hig-expert%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"apple-hig-expert","description":"Master Apple's Human Interface Guidelines (HIG) with focus on 2026 Liquid Glass aesthetics. Design and audit iOS, macOS, and visionOS apps for full compliance and premium feel. Includes hig_checker Python tool for tap targets, contrast, and accessibility validation. Reference docs cover visual design, platform specifics (iOS/macOS/visionOS), and accessibility best practices.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/product-team/apple-hig-expert","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":205,"sizeBytes":770},{"name":"plugin.json","path":"product-team/code-to-prd/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/code-to-prd/.claude-plugin/plugin.json","title":"code-to-prd","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fcode-to-prd%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"code-to-prd","description":"Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, models, APIs, and interactions for frontend (React, Vue, Angular, Next.js), backend (NestJS, Django, Express, FastAPI), and fullstack applications.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/product-team/code-to-prd","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":186,"sizeBytes":642},{"name":"plugin.json","path":"product-team/research-summarizer/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/product-team/research-summarizer/.claude-plugin/plugin.json","title":"research-summarizer","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=product-team%2Fresearch-summarizer%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"research-summarizer","description":"Structured research summarization agent skill and plugin for Claude Code, Codex, and Gemini CLI. Summarize academic papers, compare web articles, extract citations, and produce actionable research briefs.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/product-team/research-summarizer","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":168,"sizeBytes":603},{"name":"plugin.json","path":"productivity/andreessen/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/andreessen/.claude-plugin/plugin.json","title":"andreessen","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fandreessen%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"andreessen","description":"Marc Andreessen-mode decision and productivity skill. A blunt, market-first operator that pressure-tests ventures, ideas, features, and career bets through Andreessen's documented frameworks (market > team > product; product/market fit is the only milestone that matters; bias to build) and runs his 3x5-card + Anti-Todo daily routine. Runs on a fixed anti-sycophancy operating prompt: leads with the strongest counterargument, never validates premises, no disclaimers, explicit confidence levels, never apologizes for disagreeing. Issues hard verdicts (BUILD-POUR-FUEL / MARKET-FIRST-DERISK / KILL-OR-REPICK-MARKET) backed by deterministic stdlib tools.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/andreessen","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/andreessen"]},"isInternal":false,"tokens":274,"sizeBytes":1046},{"name":"plugin.json","path":"productivity/capture/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/capture/.claude-plugin/plugin.json","title":"capture-skill","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fcapture%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"capture-skill","description":"Brain-dump organizer. Ingests an unstructured stream of mixed thoughts, tasks, ideas and transforms it into a clean four-section actionable system (Projects/Ideas, Tasks, Connections, How I Can Help) with zero information loss. Fast-to-action by design — no upfront intake. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project. Workspace detection is real (Glob/Grep) — never fabricates connections. Source spec: megaprompts/05-capture-megaprompt.md (PR #657).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/capture","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/capture"]},"isInternal":false,"tokens":247,"sizeBytes":921},{"name":"plugin.json","path":"productivity/deep-work/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/deep-work/.claude-plugin/plugin.json","title":"deep-work","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fdeep-work%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"deep-work","description":"Plan a deep work day the Cal Newport way: time-block planning + shallow-work budgeting + focus-session tracking. Classifies every task deep vs shallow (recent-graduate heuristic, explicit override wins), audits the shallow share against a 30-50% budget with a WITHIN-BUDGET / OVER-BUDGET verdict, then builds an energy-first time-blocked day — deep blocks of at least 90 minutes in the earliest hours, a hard 4-hour deep ceiling the planner refuses to exceed, shallow work batched into at most two windows, 10-minute attention-residue buffers, a fixed lunch, and a hard stop that never silently extends. A JSON-backed focus-session logger tracks weekly deep hours vs target and consecutive-day streaks, and an end-of-day shutdown ritual closes every open loop. Deterministic stdlib scripts do the arithmetic; refusals (exit 2) name exactly what to cut or defer.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/deep-work","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/deep-work"]},"isInternal":false,"tokens":316,"sizeBytes":1252},{"name":"plugin.json","path":"productivity/email/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/email/.claude-plugin/plugin.json","title":"email-pair","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Femail%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"email-pair","description":"Email triage system — paired skills (inbox-setup + inbox-triage) for personalized recurring email triage. inbox-setup runs once via interactive interview to build a knowledge base of 7 files (taxonomy, patterns, evaluation-framework, rate-card, blocklist, tracker, triage-log/) in ${WORKSPACE}/Email/. inbox-triage runs on recurring cadence (1-3x daily) or on demand: classifies recent emails, researches new senders, generates recommendations, drafts replies (NEVER sends), delivers a report, and updates the KB with learnings. The two skills share a strict file contract — PR #657's cross-skill consistency audit verified the 7 KB filenames align verbatim between the two megaprompts. Source specs: megaprompts/06-inbox-setup-megaprompt.md + megaprompts/07-inbox-triage-megaprompt.md.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/email","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/inbox-setup","./skills/inbox-triage"]},"isInternal":false,"tokens":321,"sizeBytes":1207},{"name":"plugin.json","path":"productivity/fable-goal/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/fable-goal/.claude-plugin/plugin.json","title":"fable-goal","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Ffable-goal%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"fable-goal","description":"Convert a rambling description of a desired outcome into one polished, autonomous /goal prompt ready to paste into a fresh session. Use when the user says '/fable-goal', 'turn this into a goal prompt', 'write me a fable prompt', or rambles about something they want made and asks for the prompt that makes it happen. Extracts deliverable/quantity/stakes/tools/destination, asks at most one question batch, verifies every named resource against the live environment, writes a 150-350 word prose prompt with the seven-part anatomy (desire + stakes, quality bar, tool inventory + discovery mandate, creative-freedom grant, medium-matched verification loop, delivery, goal line + autonomy directive), and self-checks six binary criteria before delivering. The output is a single copy-paste prompt, never the build itself.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/fable-goal","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/fable-goal"]},"isInternal":false,"tokens":301,"sizeBytes":1209},{"name":"plugin.json","path":"productivity/handoff/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/handoff/.claude-plugin/plugin.json","title":"handoff-productivity","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fhandoff%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"handoff-productivity","description":"Compact the current conversation into a handoff document for another agent to pick up. Save to a user-configured location (OS temp, home folder, or per-project .handoff/), redact secrets before write, suggest skills for the next session, and auto-load the latest handoff on the next SessionStart. First-run setup asks where to save so the project folder never gets cluttered. Use when the user says 'hand this off', 'handoff doc', 'summarize this for a new session', 'compact this conversation', 'I'm ending this session', or any variation signaling intent to pass work to a fresh agent.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/handoff","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/session-handoff"]},"isInternal":false,"tokens":260,"sizeBytes":991},{"name":"plugin.json","path":"productivity/meetings/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/meetings/.claude-plugin/plugin.json","title":"meetings","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fmeetings%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"meetings","description":"Personal meeting hygiene, end to end. Before the meeting: a cost gate that prices the meeting in real dollars (attendees x minutes x rate, optionally + the 23-minute refocus overhead per attendee) and refuses to let it exist without a decision, an agenda, and a named owner — verdicts are ASYNC / NOT-READY / MEET, never a shrug. Then a timeboxed agenda builder that rejects any topic without a desired outcome, orders decision topics first, enforces a 5-minute closing actions-recap buffer, and refuses overflowing agendas by name. After the meeting: a deterministic action-item extractor that turns raw notes into an owner + due-date checklist and flags ORPHAN (no owner) and NO-DUE items, because an action item without an owner and a date is theater. Built on the Rogelberg / HBR / Grove meeting-science canon with stdlib-only scripts.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/meetings","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/meetings"]},"isInternal":false,"tokens":314,"sizeBytes":1227},{"name":"plugin.json","path":"productivity/reflect/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/reflect/.claude-plugin/plugin.json","title":"reflect-skill","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Freflect%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"reflect-skill","description":"Mid-conversation reflection skill that pauses execution and zooms out from detail-mode to honestly reassess direction, assumptions, and bias. Use when the user says 'reflect', 'take a step back', 'step back', 'zoom out', 'are we missing something', 'bigger picture', 'sanity check this', 'are we on track', 'are we overthinking this', 'forest for the trees', or any variation signaling intent to break out of detail-mode and reassess. Also trigger when the conversation has gone deep on implementation details without strategic check-in, or when the user shows signs of being stuck — that's often a signal the framing needs a reset, not more detail work. Intentionally low-intake: runs the 5-dimension analysis immediately when prior context is rich enough; asks one forcing clarifier only when invocation context is too thin to reassess from.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/reflect","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/reflect"]},"isInternal":false,"tokens":307,"sizeBytes":1234},{"name":"plugin.json","path":"productivity/roast/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/roast/.claude-plugin/plugin.json","title":"roast","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Froast%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"roast","description":"Pressure-test a business idea before you build it. Convenes a 5-angle adversarial panel — The Critic (what kills this?), The Champion (the 10x upside?), The Analyst (does the logic hold?), The Investigator (what does the market say?), and The Customer (would I actually pay?) — fired in parallel as independent reviewers, then a Judge synthesizes one GO / RESHAPE / KILL verdict with explicit confidence and the cheapest 48-hour test to de-risk it. Never averages the scores: a weighted synthesizer with demand/fatal-flaw/logic veto gates produces the call, backed by deterministic stdlib tools. The opposite of Claude's default agreeableness.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/roast","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/roast"]},"isInternal":false,"tokens":270,"sizeBytes":1024},{"name":"plugin.json","path":"productivity/swedish-mentor/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/swedish-mentor/.claude-plugin/plugin.json","title":"swedish-mentor","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fswedish-mentor%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"swedish-mentor","description":"CEFR-leveled Swedish-learning mentor. Places the learner with a two-question probe (never trusting a vague self-label), builds a listening/reading/writing/speaking path, and recommends 3-6 vetted YouTube and podcast resources by level — Peter SFI, Lätt Svenska med Oskar, Radio Sweden på lätt svenska, Klartext, Fluent Fiction, Sommar i P1 — with a maintained catalog in references/swedish-resources.md and a hard never-invent-a-URL rule.","version":"2.14.1","author":{"name":"mh-mansouri","url":"https://github.com/mh-mansouri"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/swedish-mentor","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./"]},"isInternal":false,"tokens":227,"sizeBytes":820},{"name":"plugin.json","path":"productivity/weekly-review/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/productivity/weekly-review/.claude-plugin/plugin.json","title":"weekly-review","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=productivity%2Fweekly-review%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"weekly-review","description":"Run a GTD-style weekly review that actually closes loops. Walks David Allen's three-phase ritual — GET CLEAR (collect, process inboxes to zero, empty your head), GET CURRENT (next actions, previous + upcoming calendar, waiting-for, project lists), GET CREATIVE (someday/maybe, new ideas) — backed by three deterministic stdlib scripts: an open-loop scanner that inventories unchecked checkboxes, TODO/FIXME markers, and stale files; a checklist gate that computes completion, names every missing step, and refuses a COMPLETE verdict while any GET CURRENT step is unaccounted for; and a commitment auditor that flags STALLED, NO-NEXT-ACTION, and SOMEDAY-CANDIDATE projects with a 0-100 commitment-health score. The periodic-review counterpart to capture (intake) and reflect (per-conversation reflection).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/productivity/weekly-review","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/weekly-review"]},"isInternal":false,"tokens":304,"sizeBytes":1209},{"name":"plugin.json","path":"project-management/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/project-management/.claude-plugin/plugin.json","title":"pm-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=project-management%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"pm-skills","description":"9 project management skills: pm-skills fork-orchestrator with agentic delivery loop (deterministic 8-lane router, Jira MCP snapshot bridge to flow metrics/Monte Carlo forecasts, delegation-governance gate), senior PM, scrum master, Jira expert, Confluence expert, Atlassian admin, template scaffolder, meeting analyzer, team communications — plus bundled Atlassian Remote MCP (SSE) integration. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/project-management","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":231,"sizeBytes":848},{"name":"plugin.json","path":"ra-qm-team/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/.claude-plugin/plugin.json","title":"ra-qm-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"ra-qm-skills","description":"14 regulatory affairs & quality management skills for HealthTech/MedTech: ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, GDPR/DSGVO, ISO 27001 ISMS, SOC 2, CAPA management, risk management, clinical evaluation, and more. Agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/ra-qm-team","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":215,"sizeBytes":665},{"name":"plugin.json","path":"ra-qm-team/compliance-team-eu-ai-act/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-eu-ai-act/.claude-plugin/plugin.json","title":"compliance-team-eu-ai-act","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-eu-ai-act%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"compliance-team-eu-ai-act","description":"EU AI Act (Regulation (EU) 2024/1689) operational compliance specialist for compliance teams. Three deterministic tools: AI system risk classifier (Article 5 prohibited / Article 6 + Annex III high-risk / Article 50 limited-risk / minimal-risk per the binding regulation), conformity assessment planner (Article 43 Module A vs Module H + notified-body routing + Annex IV technical documentation checklist), obligation tracker (provider/deployer/importer/distributor obligations matrix per Title III Chapter 3 + GPAI obligations per Articles 51-55). 4 in-depth references: Titles I-XII Article-by-Article walkthrough, Annex III 8 high-risk categories with Article 6(2) carve-outs, GPAI obligations including systemic-risk threshold, cross-framework mapping to ISO 42001 + NIST AI RMF + GDPR. Stdlib-only. Built for compliance officers executing Article-level conformity work — not for executive AI strategy (see chief-ai-officer-advisor for that).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/ra-qm-team/compliance-team-eu-ai-act","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":347,"sizeBytes":1360},{"name":"plugin.json","path":"ra-qm-team/compliance-team-iso42001/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/ra-qm-team/compliance-team-iso42001/.claude-plugin/plugin.json","title":"compliance-team-iso42001","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=ra-qm-team%2Fcompliance-team-iso42001%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"compliance-team-iso42001","description":"ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams: AIMS gap analyzer (Clauses 4-10 coverage scoring + remediation priority), AI risk register builder (Annex A 38 controls + risk-to-treatment map per ISO 23894), AIMS audit scheduler (Clause 9.2 internal audit cadence + 12-month plan + auditor independence checks). 4 in-depth references: ISO 42001 Clauses 4-10 walkthrough, Annex A controls A.1-A.10, AIMS implementation maturity model, cross-framework mapping (42001 ↔ EU AI Act ↔ NIST AI RMF ↔ ISO 23894). Stdlib-only. Standalone-installable; also bundled in ra-qm-skills. Built for compliance officers running internal AIMS audits, not for executive AI strategy decisions (see chief-ai-officer-advisor for those).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/ra-qm-team/compliance-team-iso42001","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills"]},"isInternal":false,"tokens":336,"sizeBytes":1167},{"name":"plugin.json","path":"research-ops/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research-ops/.claude-plugin/plugin.json","title":"research-ops-skills","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research-ops%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"research-ops-skills","description":"4 Research-Operations skills + 1 orchestrator: clinical-research (study design: protocol synopsis, endpoint selection, sample-size/power, phase-gating, feasibility), research-finance (R&D program budgeting, burn/runway, F&A indirect-rate modeling, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM both-methods, survey/sampling design, segmentation, CI synthesis), product-research (interview/JTBD/usability/concept-test design, saturation, insight repository synthesis). Orchestrator skill uses context: fork. Each sub-skill ships per-skill onboarding (onboard.py), a customization loader (config_loader.py) consumed by every tool, and an isolated opt-in autoresearch evaluator (ar_evaluator.py) bridging to engineering/autoresearch-agent. 24 stdlib-only Python tools (12 analysis + 12 onboarding/customization/autoresearch), 12 reference docs. Distinct from ra-qm-team (regulatory/QM submission), finance (corporate close/valuation), research/grants (NIH funding discovery), product-team (persona/journey/live experiments), marketing-skill (campaign analytics).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research-ops","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/research-ops-skills","./skills/clinical-research","./skills/research-finance","./skills/market-research","./skills/product-research","./skills/interview-mapper"]},"isInternal":false,"tokens":418,"sizeBytes":1653},{"name":"plugin.json","path":"research/deep-research/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/deep-research/.claude-plugin/plugin.json","title":"deep-research","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdeep-research%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"deep-research","description":"Disciplined, multi-source meta-research for high-stakes questions — the heavyweight alternative to the fast research router. Runs a 9-phase pipeline (reframe into falsifiable hypotheses → genre/blocks → plan → capability discovery → parallel sub-agent fan-out → score & triangulate → synthesize + adversarial pass → verify → refresh targets), triangulates every thesis against >=3 independent, differently-typed sources, saves each source to its own file with verbatim quotes, and never fabricates a citation. Output is an auditable, reusable folder with a delta-update refresh protocol. Use when a wrong answer is expensive: strategy, comparing N options, hypothesis validation, mapping a field.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/deep-research","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/deep-research"]},"isInternal":false,"tokens":270,"sizeBytes":1111},{"name":"plugin.json","path":"research/deepread/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/deepread/.claude-plugin/plugin.json","title":"deepread","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdeepread%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"deepread","description":"Evidence-first reading of supplied documents — books, articles, PDFs, document sets. Five modes (quick, deep, map, feynman, book), claim/reason/evidence decomposition with four-level confidence labels, an evidence ledger, knowledge maps, and Feynman teach-back. Starts from material the user supplies; for discovering sources across the web use deep-research, and for citation-formatted briefs use research-summarizer.","version":"2.14.1","author":{"name":"xiehuan123","url":"https://github.com/xiehuan123"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/deepread","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./"]},"isInternal":false,"tokens":209,"sizeBytes":777},{"name":"plugin.json","path":"research/dossier/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/dossier/.claude-plugin/plugin.json","title":"dossier","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fdossier%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"dossier","description":"Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network signals, reputation signals, red flags, 3-5 conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica Nonprofit Explorer) as workhorses; optional BYOK MCPs (LinkedIn, Crunchbase, Apollo, Pitchbook, SimilarWeb) enhance coverage. Triggers: 'research [company]', 'dossier on [person/company]', 'background check on [entity]', 'prep me for a meeting with [person/company]', 'due diligence on [company]', 'what should I know about [entity]', 'research [person] before I [meet/hire/invest]', 'competitor research on [company]', 'investor diligence [company]', 'interview prep for [company]'. Honors sensitivity exclusions for journalism + personal-vetting contexts.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/dossier","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/dossier"]},"isInternal":false,"tokens":393,"sizeBytes":1587},{"name":"plugin.json","path":"research/grants/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/grants/.claude-plugin/plugin.json","title":"grants","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fgrants%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"grants","description":"NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Triggers: 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research', or any grant-related request. NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/grants","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/grants"]},"isInternal":false,"tokens":317,"sizeBytes":1290},{"name":"plugin.json","path":"research/litreview/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/litreview/.claude-plugin/plugin.json","title":"litreview","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Flitreview%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"litreview","description":"Academic literature orientation skill. Turns a research question into a strategically planned mini literature review, delivered as a researcher-friendly Word document (.docx). Searches via free keyless APIs by default (PubMed E-utilities + OpenAlex) with the Consensus MCP as an optional enhancement lane when connected. Grill-me intake (research question + framework hint + tentative depth) before recon search; second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — orientation guide, not a finished review. Implements research-pack Agent Integrity Rules: 1 q/sec sequential execution, lane check (no plan-tier detection), three-count tracking (sent/received/cited). Source spec: megaprompts/09-litreview-megaprompt.md (PR #657). Sibling of pulse (research-pack shape).","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/litreview","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/litreview"]},"isInternal":false,"tokens":318,"sizeBytes":1279},{"name":"plugin.json","path":"research/notebooklm/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/notebooklm/.claude-plugin/plugin.json","title":"notebooklm","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fnotebooklm%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"notebooklm","description":"Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/notebooklm","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/notebooklm"]},"isInternal":false,"tokens":287,"sizeBytes":1129},{"name":"plugin.json","path":"research/patent/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/patent/.claude-plugin/plugin.json","title":"patent","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpatent%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"patent","description":"Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Triggers: 'prior art search for [invention]', 'patent search on [topic]', 'freedom to operate analysis', 'FTO for [product]', 'patent landscape for [field]', 'is [invention] novel', 'patents on [topic]', 'competitive patent analysis', 'prior art for litigation', 'patent diligence on [company]'. Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/patent","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/patent"]},"isInternal":false,"tokens":363,"sizeBytes":1476},{"name":"plugin.json","path":"research/pulse/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/pulse/.claude-plugin/plugin.json","title":"pulse","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fpulse%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"pulse","description":"Multi-source recency research skill. Takes the pulse of any topic across Reddit, Hacker News, the open web, and (optionally) X/Twitter within a configurable recent window (default 30 days). Forcing 2–4 question grill-me intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Phases 1–3 run in parallel per the research-pack convention. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Source spec: megaprompts/01-pulse-megaprompt.md (PR #657). Implements the Agent Integrity Rules block locked down by PR #657 audit: 1 q/sec per platform, three-count tracking (sent/received/cited), retry-once-after-3s, stop-after-3-consecutive-failures.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/pulse","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/pulse"]},"isInternal":false,"tokens":306,"sizeBytes":1160},{"name":"plugin.json","path":"research/research/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/research/.claude-plugin/plugin.json","title":"research-orchestrator","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fresearch%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"research-orchestrator","description":"Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers: 'research [topic]', 'look into [topic]', 'what do we know about [topic]', 'investigate [topic]', 'find me information on [topic]', 'do some research on [topic]', 'I need to understand [topic]', or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/research","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/research"]},"isInternal":false,"tokens":318,"sizeBytes":1314},{"name":"plugin.json","path":"research/syllabus/.claude-plugin/plugin.json","rawUrl":"https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/research/syllabus/.claude-plugin/plugin.json","title":"syllabus","category":"plugin-manifest","format":"json","content":"<!-- Skill available on-demand via /api/skills/alirezarezvani/claude-skills?path=research%2Fsyllabus%2F.claude-plugin%2Fplugin.json -->","frontmatter":{"name":"syllabus","description":"Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.","version":"2.14.1","author":{"name":"Alireza Rezvani","url":"https://alirezarezvani.com"},"homepage":"https://github.com/alirezarezvani/claude-skills/tree/main/research/syllabus","repository":"https://github.com/alirezarezvani/claude-skills","license":"MIT","skills":["./skills/syllabus"]},"isInternal":false,"tokens":354,"sizeBytes":1559}],"systemPromptSnippet":"<yakaai_skills repo=\"alirezarezvani/claude-skills\">\n<!-- File: docs/llms-full.txt (Tokens: ~3687 | Category: root-instruction) -->\n# Claude Code Skills & Agent Plugins — Full Repository Description\n\n> A comprehensive, self-contained description of the `alirezarezvani/claude-skills` repository, written for AI agents and LLM crawlers. This file follows the [llms.txt](https://llmstxt.org) convention (`llms-full.txt` variant: the expanded, single-file version). For the concise index, see [llms.txt](https://alirezarezvani.github.io/claude-skills/llms.txt).\n\n- **Project:** Claude Code Skills & Agent Plugins\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Documentation site:** https://alirezarezvani.github.io/claude-skills/\n- **Author:** Alireza Rezvani\n- **License:** MIT (free to extract, deploy, adapt, and redistribute)\n- **Distribution:** Claude Code plugin marketplace (`.claude-plugin/marketplace.json`) and the ClawHub registry (clawhub.com)\n\n---\n\n## What this repository is\n\nThis is a **library of skill packages** for Claude AI and Claude Code — reusable, production-ready modules that bundle domain expertise, best practices, deterministic analysis tools, and strategic frameworks. It is **not a traditional application**. It is a catalog of self-contained skill folders meant to be extracted and deployed by users into their own AI-agent workflows.\n\nTeams download a skill folder and use it immediately: the skill's `SKILL.md` teaches the agent the workflow, the `scripts/` provide deterministic Python CLI tools, the `references/` supply expert knowledge bases, and the `assets/` give ready-to-customize templates.\n\n### Headline scale (derived from the tree by `scripts/derive_counters.py`)\n\n| Metric | Count |\n|--------|-------|\n| Production-ready skills | 354 |\n| Marketplace plugins | 82 |\n| Top-level domains | 18 |\n| Python automation tools | 593 |\n| Reference guides | 722 |\n| Agents (cs-* + personas) | 96 |\n| Slash commands | 102 |\n\nCounters are generated from the actual file tree; run `python3 scripts/derive_counters.py --check` to verify the docs still match the tree.\n\n---\n\n## Cross-tool compatibility\n\nSkills are authored once and made portable across many AI coding agents via sync scripts in `scripts/`. Supported targets include:\n\n- **Claude Code** (primary) — plugins, agents, slash commands, MCP servers, hooks\n- **OpenAI Codex** — `scripts/sync-codex-skills.py`, `~/.codex/`\n- **Gemini CLI** — `scripts/sync-gemini-skills.py`\n- **Cursor** — rules-format export\n- **Hermes Agent** — `scripts/sync-hermes-skills.py`\n- **Mistral Vibe** — `scripts/sync-vibe-skills.py`, `~/.vibe/skills/`\n- **Codebuff** — `scripts/sync-codebuff-skills.py`\n- **OpenClaw**, **Aider**, **Windsurf**, **Kilo Code**, **OpenCode**, **Augment**, **Antigravity** — documented in the Multi-Tool Integrations guide.\n\n---\n\n## Design principles\n\n1. **Skills are products.** Each skill is deployable as a standalone package with no dependency on other skills.\n2. **Documentation-driven.** Success depends on clear, actionable `SKILL.md` docs.\n3. **Algorithm over AI.** Analysis tools use deterministic Python (standard library only) — **no LLM/ML calls inside scripts**. This keeps skills portable, fast, and reproducible.\n4. **Template-heavy.** Skills ship ready-to-use templates users customize.\n5. **Platform-specific.** Specific, actionable frameworks beat generic advice.\n\n### Anti-patterns the repo deliberately avoids\n- Dependencies between skills (each stays self-contained)\n- Complex build systems or test frameworks (portability first)\n- Generic advice instead of specific frameworks\n- LLM calls in scripts (defeats portability and speed)\n\n---\n\n## Skill package pattern\n\nEvery skill follows this structure:\n\n```\nskill-name/\n├── SKILL.md        # Master documentation: the workflow the agent follows\n├── scripts/        # Python CLI tools (stdlib-only, no LLM calls; support --help and JSON output)\n├── references/     # Expert knowledge bases (markdown), each citing 5-8 authoritative sources\n└── assets/         # User-facing templates\n```\n\nKnowledge flows: `references/` → informs `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\nEach `SKILL.md` carries YAML frontmatter with a `name` and a `description` whose trigger phrasing (e.g. \"Use when…\") tells the agent when to invoke the skill.\n\n---\n\n## Repository structure\n\n```\nclaude-skills/\n├── .claude-plugin/        # Plugin registry (marketplace.json — 82 plugins)\n├── agents/                # cs-* agents + 7 personas\n├── commands/              # Slash commands\n├── engineering-team/      # Core engineering skills\n├── engineering/           # POWERFUL-tier advanced engineering skills\n├── product-team/          # Product skills\n├── marketing-skill/       # Marketing skills (8 pods incl. AEO)\n├── marketing/             # Landing-page generator skill\n├── c-level-advisor/       # C-level advisory skills (full C-suite + founder-mode)\n├── project-management/    # PM skills + bundled Atlassian Remote MCP\n├── ra-qm-team/            # Regulatory / quality-management compliance skills\n├── compliance-os/         # Compliance audit-prep orchestrator + sub-skills\n├── business-growth/       # Customer success, sales eng, revops\n├── business-operations/   # Internal-ops skills (orchestrator + sub-skills)\n├── commercial/            # Per-deal-economics skills (orchestrator + sub-skills)\n├── finance/               # Finance skills\n├── research/              # Academic research skills (orchestrator + specialists)\n├── research-ops/          # Enterprise research operations (orchestrator + sub-skills)\n├── productivity/          # Capture, email, reflect, handoff, andreessen\n├── markdown-html/         # Markdown-to-interactive-HTML converter suite\n├── standards/             # Communication, quality, git, security standards\n├── templates/             # Reusable templates\n├── docs/                  # This MkDocs Material documentation site\n└── scripts/               # Build, sync, and validation scripts\n```\n\n---\n\n## The 18 domains in detail\n\n### Engineering — Core (`engineering-team/`)\nFullstack, AI/ML, DevOps, security, data, and QA skills. Includes senior-role skills (architect, backend, frontend, fullstack, DevOps, data engineer/scientist, ML, computer vision, prompt, QA, security, SecOps), cloud architects (AWS/Azure/GCP), a full security suite (adversarial reviewer, AI security, cloud security, incident response, red team, threat detection, pen testing), Playwright Pro (10 sub-skills), a Self-Improving Agent suite, Snowflake development, and Stripe integration.\n\n### Engineering — POWERFUL (`engineering/`)\nAdvanced, higher-leverage engineering skills: agent design, RAG architecture, MCP server building, CI/CD pipelines, database/schema design, observability, SLO architecture, chaos engineering, Kubernetes operators, feature-flags, migration architecture, performance profiling, dependency auditing, and meta-skills for **authoring skills** (`write-a-skill`), token compression (`caveman`), plan interrogation (`grill-me`), and conversation continuity (`handoff`). Also hosts AgentHub, the autoresearch-agent (Karpathy file-optimization loop), the LLM Wiki, ship-gate, and a PreToolUse security-guidance hook.\n\n### Product (`product-team/`)\nRICE prioritization, OKRs, user stories, UX research and design, product discovery/strategy, competitive teardowns, experiment design, product analytics, SaaS scaffolding, code-to-PRD, spec-to-repo, and an Apple HIG expert.\n\n### Marketing (`marketing-skill/`)\nEight pods spanning content creation, copywriting/editing, SEO, **AEO (Answer Engine Optimization)**, ASO (app-store optimization), demand generation, paid ads, CRO (conversion-rate optimization across page/form/signup/paywall/popup/onboarding), social media, email sequences, pricing strategy, launch strategy, schema markup, and campaign analytics.\n\n### Marketing — Landing Pages (`marketing/`)\nA single-file HTML landing-page generator with multiple design styles, brand-palette validation, and GSAP animation patterns.\n\n### Project Management (`project-management/`)\nJira and Confluence experts, Atlassian admin/templates, scrum master, senior PM, meeting analyzer, and team communications. Ships a bundled Atlassian Remote MCP (`.mcp.json`, SSE transport, OAuth handled by Claude Code).\n\n### C-Level Advisory (`c-level-advisor/`)\nA full C-suite of opinionated advisor skills (CEO, CFO, CMO, CPO, CRO, COO, CTO, CHRO, CISO, CDO, CAIO, CCO, VP Engineering, General Counsel) plus a **Founder-Mode** operating system: `/c-level-agents:office-hours`, `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`, plus onboarding, cross-eval, and decision-freeze commands. Includes an Executive Mentor suite and strategic frameworks (RICE, JTBD, OKR, ADKAR, Wardley mapping). Memory is Markdown-only (no database dependency).\n\n### Regulatory & Quality (`ra-qm-team/`)\nISO 13485, EU MDR 2017/745, FDA, GDPR/DSGVO, ISO 27001, SOC 2, CAPA, risk management, and QMS/ISMS audit skills for regulated industries (notably medical devices).\n\n### Compliance OS (`compliance-os/`)\nAn orchestrator plus audit-prep sub-skills for SOC 2, ISO 13485, ISO 27001, GDPR, FDA QSR, EU AI Act readiness, and ISO 42001 (AIMS).\n\n### Business & Growth (`business-growth/`)\nCustomer success management, sales engineering, revenue operations, and contract/proposal writing.\n\n### Business Operations (`business-operations/`)\nInternal-ops skills for BizOps leads and COO direct reports: process mapping (BPMN + bottleneck + cycle-time), vendor management (scorecard + SLA + third-party risk), capacity planning (Erlang-C), internal comms (ADKAR + Kotter), knowledge ops (SOP/runbook hygiene), and procurement optimization. Orchestrator uses `context: fork` chaining. Every output is a recommendation routed to a named human — never an auto-decision.\n\n### Commercial (`commercial/`)\nPer-deal-and-packaging skills: pricing strategist (model picker + Van Westendorp PSM + packaging), deal desk (scorer + approval router + redliner), partnerships architect, channel economics, commercial policy, RFP responder (Shipley method), and commercial forecaster. Pricing outputs a model and a range (never a single number); deal outputs route to a named approver (never auto-approve).\n\n### Finance (`finance/`)\nFinancial analysis, DCF valuation, budgeting/forecasting, business investment advisory, and SaaS-metrics coaching.\n\n### Research (`research/`)\nAcademic/literature research: an orchestrator (hybrid router) plus specialists for recency+sentiment pulse, literature review, NIH grants, entity dossiers, patent/prior-art landscapes, course-reading syllabi, and NotebookLM browser automation.\n\n### Research Operations (`research-ops/`)\nThe enterprise counterpart to `research/`: clinical study design (sample size, endpoints, phase-gate — estimates confirmed by a named clinical owner), R&D program finance (budget, burn/runway, CapEx-vs-OpEx routing), market research (TAM/SAM/SOM with method + assumptions, never a single number), and product research (study design, saturation planning, insight synthesis requiring recurrence across independent participants).\n\n### Productivity (`productivity/`)\nCapture (brain-dump-to-action), email (inbox setup + triage, drafts-only), reflect (light-prompt journaling), handoff (conversation continuity with redaction linting and session hooks), and andreessen (market-first decision engine).\n\n### Markdown to HTML (`markdown-html/`)\nA converter suite operationalizing Thariq Shihipar's thesis that markdown collapses past ~100 lines and HTML restores density/clarity/shareability. Ships an orchestrator (doctype router), a design-system onboarding wizard (WCAG-AA-validated brand palette), and three converters: `md-document` (long-form → single-file HTML with TOC/search/code-copy/scrollspy), `md-review` (code-review markdown → 2-column diff + severity annotations), and `md-slides` (markdown deck → single-file HTML presentation with keyboard nav, presenter mode, and print-to-PDF). Output is single-file HTML (Google Fonts + Prism.js CDN the only permitted externals).\n\n---\n\n## Agents and slash commands\n\n- **Agents (`agents/`):** 96 total, mostly `cs-*` prefixed personas (e.g. `cs-ceo-advisor`, `cs-senior-engineer`, `cs-aeo`, domain orchestrators) plus 7 general personas. Agents orchestrate skills and carry a distinct operating voice.\n- **Slash commands (`commands/`):** 102 total, including `/prd`, `/rice`, `/okr`, `/tdd`, `/changelog`, `/slo-design`, `/chaos-experiment`, `/plugin-audit`, `/seo-auditor`, and the `/cs-*` family (office-hours, boardroom, bizops, commercial, research-ops, markdown-html routers, and per-skill commands).\n\n---\n\n## Plugin distribution\n\nPlugins are registered in `.claude-plugin/marketplace.json` (82 plugins) across these categories: development (34), leadership (9), research (9), productivity (6), marketing (5), compliance (4), product (4), finance (2), and one each of project-management, business-growth, design, knowledge, operations, commercial, research-ops, documentation, and engineering.\n\n### plugin.json rules (for anyone extending the library)\n- Required fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills`.\n- Two approved extension fields: `source` (provenance for megaprompt-derived skills) and `attribution` (credit for MIT-licensed external derivations).\n- Skill paths are relative to the plugin root and start with `./`. Canonical forms: single-skill = `[\"./\"]`; `skills/` subdir = `\"./skills\"`; multi-skill domain = explicit `[\"./sub1\", \"./sub2\", ...]`.\n- Validation: `scripts/check_plugin_json.py --all` runs in CI on every PR.\n\n---\n\n## Git and contribution workflow\n\n- **Branch strategy:** feature → dev → main. **All PRs target `dev`, never `main`.** `main` receives only periodic `dev → main` promotion PRs from the maintainer.\n- **Conventional commits** are enforced (e.g. `feat(agents): …`, `fix(tool): …`, `docs(workflow): …`).\n- **Branch protection:** `main` requires PR approval; direct pushes are blocked.\n\n### ClawHub publishing constraints\n- The `cs-` prefix is used only on the ClawHub registry when a slug conflicts with another publisher — repo folder names and local skill names are never renamed.\n- No paid/commercial service dependencies; free-tier APIs and bring-your-own-key patterns are acceptable.\n- Rate limit: 5 new skills per hour.\n- Package versions match the repo release version.\n\n---\n\n## How an agent should use this repository\n\n1. **Find a matching skill** by browsing the [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/) or a domain index, matching the task to a skill's `description` trigger.\n2. **Read the skill's `SKILL.md`** to learn the workflow.\n3. **Run the skill's Python tools** (`scripts/*.py`, stdlib-only, all support `--help` and most support JSON output) for deterministic analysis.\n4. **Consult `references/`** for the expert knowledge underpinning the workflow.\n5. **Apply the `assets/` templates** to produce the deliverable.\n\nTo install as a plugin, add the marketplace and install the relevant plugin via Claude Code; see [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/) and [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/) for non-Claude tools.\n\n---\n\n*Generated to make the repository accessible to AI agents. Counters reflect `scripts/derive_counters.py` at the time of writing; the repository evolves — the GitHub repository and documentation site are the authoritative sources.*\n\n<!-- File: docs/llms.txt (Tokens: ~1334 | Category: root-instruction) -->\n# Claude Code Skills & Agent Plugins\n\n> An open-source (MIT) library of 354 production-ready agent skills, 82 installable plugins, 96 agents, and 102 slash commands across 18 domains — engineering, product, marketing, compliance, finance, research, and more. Each skill is a self-contained package bundling domain expertise, deterministic Python tools (stdlib-only, no LLM calls), reference knowledge bases, and ready-to-use templates. Skills are portable across Claude Code, OpenAI Codex, Gemini CLI, Cursor, Hermes Agent, Mistral Vibe, OpenClaw, and 6+ more AI coding tools.\n\nThis file follows the [llms.txt](https://llmstxt.org) convention. For a full, self-contained description of the entire repository, see [llms-full.txt](https://alirezarezvani.github.io/claude-skills/llms-full.txt).\n\nKey facts for agents:\n- **License:** MIT. Free to extract, deploy, and adapt.\n- **Repository:** https://github.com/alirezarezvani/claude-skills\n- **Distribution:** Claude Code plugin marketplace + ClawHub registry.\n- **Design philosophy:** Algorithm over AI (deterministic code, not LLM calls in tools), documentation-driven, template-heavy, self-contained skills.\n- **Skill package shape:** `SKILL.md` (master doc) + `scripts/` (Python CLI tools) + `references/` (knowledge bases) + `assets/` (templates).\n\n## Getting started\n\n- [Home](https://alirezarezvani.github.io/claude-skills/): Overview and value proposition.\n- [Getting Started](https://alirezarezvani.github.io/claude-skills/getting-started/): Install and use skills/plugins.\n- [Multi-Tool Integrations](https://alirezarezvani.github.io/claude-skills/integrations/): Using skills with Codex, Gemini CLI, Cursor, Hermes, Vibe, OpenClaw, and more.\n- [Skills Overview](https://alirezarezvani.github.io/claude-skills/skills/): Index of all 354 skills by domain.\n- [Plugins](https://alirezarezvani.github.io/claude-skills/plugins/): The 82 installable marketplace plugins.\n- [Agents](https://alirezarezvani.github.io/claude-skills/agents/): The 96 cs-* agents and personas.\n- [Commands](https://alirezarezvani.github.io/claude-skills/commands/): The 102 slash commands.\n\n## Domains\n\n- [Engineering — Core](https://alirezarezvani.github.io/claude-skills/skills/engineering-team/): Fullstack, AI/ML, DevOps, security, data, QA.\n- [Engineering — POWERFUL](https://alirezarezvani.github.io/claude-skills/skills/engineering/): Agent design, RAG, MCP, CI/CD, observability, SLOs, skill authoring.\n- [Product](https://alirezarezvani.github.io/claude-skills/skills/product-team/): RICE, OKRs, user stories, UX research, SaaS scaffolding.\n- [Marketing](https://alirezarezvani.github.io/claude-skills/skills/marketing-skill/): Content, SEO, AEO, ASO, demand gen, campaign analytics.\n- [Project Management](https://alirezarezvani.github.io/claude-skills/skills/project-management/): Jira/Confluence, Atlassian MCP, scrum.\n- [C-Level Advisory](https://alirezarezvani.github.io/claude-skills/skills/c-level-advisor/): Full C-suite advisors + founder-mode orchestration.\n- [Regulatory & Quality](https://alirezarezvani.github.io/claude-skills/skills/ra-qm-team/): ISO 13485, MDR, FDA, GDPR, ISO 27001.\n- [Compliance OS](https://alirezarezvani.github.io/claude-skills/skills/compliance-os/): Audit-prep orchestrator for SOC 2, ISO, GDPR, EU AI Act.\n- [Business & Growth](https://alirezarezvani.github.io/claude-skills/skills/business-growth/): Customer success, sales engineering, revenue operations.\n- [Business Operations](https://alirezarezvani.github.io/claude-skills/skills/business-operations/): Process mapping, vendor management, capacity planning.\n- [Commercial](https://alirezarezvani.github.io/claude-skills/skills/commercial/): Pricing, deal desk, partnerships, RFP response.\n- [Finance](https://alirezarezvani.github.io/claude-skills/skills/finance/): Financial analysis, DCF valuation, SaaS metrics.\n- [Research](https://alirezarezvani.github.io/claude-skills/skills/research/): Literature review, grants, patents, entity dossiers.\n- [Research Operations](https://alirezarezvani.github.io/claude-skills/skills/research-ops/): Clinical study design, R&D finance, market/product research.\n- [Productivity](https://alirezarezvani.github.io/claude-skills/skills/productivity/): Capture, email triage, reflection, handoff.\n- [Markdown to HTML](https://alirezarezvani.github.io/claude-skills/skills/markdown-html/): Markdown-to-interactive-HTML converter suite.\n\n## Optional\n\n- [Guides](https://alirezarezvani.github.io/claude-skills/guides/best-claude-code-plugins/): Best plugins, per-tool skill guides (Codex, Gemini CLI, Cursor, OpenClaw).\n- [Orchestration](https://alirezarezvani.github.io/claude-skills/orchestration/): How skills chain together.\n- [Custom GPTs](https://alirezarezvani.github.io/claude-skills/custom-gpts/): Using the library with custom GPTs.\n- [Personas](https://alirezarezvani.github.io/claude-skills/personas/): Startup CTO, Growth Marketer, Solo Founder bundles.\n\n<!-- File: agent-launcher/CLAUDE.md (Tokens: ~770 | Category: claude-rule) -->\n# CLAUDE.md — agent-launcher domain\n\nGuidance for working inside `agent-launcher/`. See the root `CLAUDE.md` for\nrepo-wide rules.\n\n## What this domain is\n\nA plugin that scaffolds and launches **Claude Managed Agents (CMA)** in the user's\nown Anthropic account, organized around a **per-session goal** that compiles into a\n**loop or workflow**. Inspired by `anthropics/launch-your-agent` (Apache-2.0);\nindependent re-implementation, not a fork.\n\n## Non-negotiable rules (enforced by SPEC.md + validators)\n\n1. **Deterministic scaffolders only.** Every script under `skills/*/scripts/` is\n   stdlib-only and makes **no** network/API calls. Live launches are emitted as\n   BYOK curl. Do not add `requests`, `anthropic`, or any network client.\n2. **Never surface the API key.** Launch scripts read `$ANTHROPIC_API_KEY`; no\n   tool echoes/logs/writes a key. `payload_validator.py` and reviewers check this.\n3. **CMA limits are law.** Keep `references/cma-primitives.md` as the source of\n   truth for ceilings; validators must match it.\n4. **Bounded loops only.** `loop_compiler.py` never emits a grade→iterate loop\n   without a `max_iterations` cap (1..20).\n5. **The hook is opt-in and crash-proof.** Gated by `AGENT_LAUNCHER_SESSION=1`;\n   exits 0 on any error. Never make it fire unconditionally.\n6. **The folder is the user's.** All artifacts go under `./my-agent/`; scripts\n   accept `--out-dir` and default there. Never write into the plugin folder.\n\n## Structure\n\n- `skills/agent-launcher-orchestrator/` — `context: fork` goal router\n  (`goal_router.py`, `goal_state.py`, `loop_compiler.py`).\n- `skills/{interview,stage-launch,grade-iterate,run-without-you,wrap-up}/` — one\n  phase each, 3 tools each.\n- `agents/` — `cs-agent-launcher-orchestrator` + 3 phase specialists.\n- `commands/` — 8 `/cs-*` commands.\n- `hooks/` — opt-in `session_start.py` / `session_end.py` + `hooks.json`.\n- `references/` — 5 shared docs. `assets/` — schema + templates + example.\n\n## Tool conventions\n\n- Every tool: `argparse` with real `--help`, a `--sample` that runs a deterministic\n  demo and exits 0, and JSON output via `--json` where a machine reads it.\n- Default output dir `./my-agent/`; never assume network access.\n- Import shared logic via relative `sys.path` insert (see how the orchestrator\n  tools import `goal_state`).\n\n## Forcing-question discipline\n\nEvery SKILL.md ships a \"Forcing-question library\" (Matt Pocock grill-with-docs):\nwalk one question at a time, recommend an answer, cite the reference. The\n`/cs-grill-agent-launcher` command surfaces them.\n\n## When editing\n\n- Changing a CMA limit → update `references/cma-primitives.md` **and** every\n  validator in lockstep.\n- Adding a loop shape → update `loop_compiler.py` **and**\n  `references/loops-and-workflows.md`.\n- Keep `SPEC.md` authoritative; if you ship something different, record it in the\n  delivery report.\n\n<!-- File: agents/CLAUDE.md (Tokens: ~3279 | Category: claude-rule) -->\n# Agent Development Guide\n\nThis guide provides comprehensive instructions for creating **cs-* prefixed agents** that seamlessly integrate with the 346 production skills in this repository (count derived via `scripts/derive_counters.py`).\n\n## Agent Architecture\n\n### What are cs-* Agents?\n\n**cs-* agents** are specialized Claude Code agents that orchestrate the repository's 346 skills. Each agent:\n- References skills via relative paths (`../marketing-skill/`)\n- Executes Python automation tools from skill packages\n- Follows established workflows and templates\n- Maintains skill portability and independence\n\n**Key Principle**: Agents ORCHESTRATE skills, they don't replace them. Skills remain self-contained and portable.\n\n### ClawHub Publishing Constraints\n\nWhen skills are published to **ClawHub** (clawhub.com):\n- **cs- prefix for slug conflicts only** — applies only on the ClawHub registry when another publisher already owns the slug. Repo folder names and local skill names are never renamed.\n- **No paid/commercial service dependencies** — skills must not require paid third-party API keys or commercial services unless provided by the project itself.\n- **plugin.json** — ONLY fields: `name`, `description`, `version`, `author`, `homepage`, `repository`, `license`, `skills: \"./\"`.\n- **Rate limit:** 5 new skills/hour on ClawHub. Use drip publishing for bulk operations.\n\n### Production Agents\n\n**33 agents live in this folder** (93 agent files repo-wide, including plugin-bundled agents). A representative selection:\n\n| Agent | Domain | Description |\n|-------|--------|-------------|\n| [cs-content-creator](marketing/cs-content-creator.md) | Marketing | AI-powered content creation with brand voice consistency and SEO optimization |\n| [cs-demand-gen-specialist](marketing/cs-demand-gen-specialist.md) | Marketing | Demand generation and customer acquisition specialist |\n| [cs-ceo-advisor](c-level/cs-ceo-advisor.md) | C-Level | Strategic leadership advisor for CEOs |\n| [cs-cto-advisor](c-level/cs-cto-advisor.md) | C-Level | Technical leadership advisor for CTOs |\n| [cs-product-manager](product/cs-product-manager.md) | Product | RICE prioritization and customer discovery |\n| [cs-product-strategist](product/cs-product-strategist.md) | Product | Product strategy, OKR cascades, market positioning |\n| [cs-agile-product-owner](product/cs-agile-product-owner.md) | Product | Agile product ownership and backlog management |\n| [cs-ux-researcher](product/cs-ux-researcher.md) | Product | UX research, usability testing, design insights |\n| [cs-product-analyst](product/cs-product-analyst.md) | Product | Product analytics, KPI design, experiment design |\n| [cs-engineering-lead](engineering-team/cs-engineering-lead.md) | Engineering | Engineering team coordination and incident management |\n| [cs-workspace-admin](engineering-team/cs-workspace-admin.md) | Engineering | Google Workspace administration via gws CLI |\n| [cs-senior-engineer](engineering/cs-senior-engineer.md) | Engineering | Architecture decisions, code review, CI/CD setup |\n| [cs-fullstack-engineer](engineering/cs-fullstack-engineer.md) | Engineering | Fullstack orchestrator (v2.8.1): walks 7 Matt Pocock forcing questions, picks profile via deterministic engine, forks (`context: fork`) into api-design-reviewer / database-designer / slo-architect / ci-cd-pipeline-builder. Invokable via `/cs-fullstack-review` or `Agent({subagent_type:\"cs-fullstack-engineer\"})`. |\n| [cs-frontend-engineer](engineering/cs-frontend-engineer.md) | Engineering | Frontend orchestrator (v2.8.1): walks 7 forcing questions (device, LCP target, rendering, bundle, SEO, design system, WCAG), picks framework profile, forks into a11y-audit / performance-profiler / epic-design / apple-hig-expert. Invokable via `/cs-frontend-review`. |\n| [cs-backend-engineer](engineering/cs-backend-engineer.md) | Engineering | Backend orchestrator (v2.8.1): walks 7 forcing questions (read/write + QPS, tenancy, sync vs async, sensitivity, pattern, RPO/RTO, SLO), picks language + pattern profile, forks into api-design-reviewer / database-designer / migration-architect / slo-architect / observability-designer. Invokable via `/cs-backend-review`. |\n| [cs-growth-strategist](business-growth/cs-growth-strategist.md) | Business | Growth strategy and revenue optimization |\n| [cs-financial-analyst](finance/cs-financial-analyst.md) | Finance | Financial analysis, DCF valuation, SaaS metrics |\n| [cs-project-manager](project-management/cs-project-manager.md) | PM | Project management with Atlassian integration |\n| [cs-quality-regulatory](ra-qm-team/cs-quality-regulatory.md) | RA/QM | Regulatory affairs and quality management |\n\n**Template Available**: [templates/agent-template.md](../templates/agent-template.md) (318 lines) - Use this to create new agents\n\n### Agent vs Skill\n\n| Aspect | Agent (cs-*) | Skill |\n|--------|-------------|-------|\n| **Purpose** | Orchestrate and execute workflows | Provide tools, knowledge, templates |\n| **Location** | `agents/domain/` | `domain-skill/skill-name/` |\n| **Structure** | Single .md file with YAML frontmatter | SKILL.md + scripts/ + references/ + assets/ |\n| **Integration** | References skills via `../../` | Self-contained, no dependencies |\n| **Naming** | cs-content-creator, cs-ceo-advisor | content-creator, ceo-advisor |\n\n## Agent File Structure\n\n### Required YAML Frontmatter\n\nEvery agent file must start with valid YAML frontmatter:\n\n```yaml\n---\nname: cs-agent-name\ndescription: One-line description of what this agent does\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n```\n\n**Field Definitions:**\n- **name**: Agent identifier with `cs-` prefix (e.g., `cs-content-creator`)\n- **description**: Single sentence describing agent's purpose\n- **No `skills:` field.** Claude Code preloads every skill listed there into the subagent's context on each spawn (resolved by `plugin:skill` name, not by path). This repo's agents are lightweight routers, so name the skill folder in the agent body instead and let the agent load it on demand (decision recorded on PR #939).\n- **domain**: Domain category (marketing, product, engineering, c-level, pm, ra-qm)\n- **model**: Claude model to use (sonnet, opus, haiku)\n- **tools**: Array of Claude Code tools agent can use\n\n### Required Markdown Sections\n\nAfter YAML frontmatter, include these sections:\n\n1. **Purpose** (2-3 paragraphs)\n2. **Skill Integration** (with subsections)\n   - Skill Location\n   - Python Tools\n   - Knowledge Bases\n   - Templates\n3. **Workflows** (minimum 3 workflows)\n4. **Integration Examples** (concrete code/command examples)\n5. **Success Metrics** (how to measure effectiveness)\n6. **Related Agents** (cross-references)\n7. **References** (links to documentation)\n\n## Relative Path Resolution\n\n### Path Pattern\n\nAll skill references use the `../../` pattern:\n\n```markdown\n**Skill Location:** `../marketing-skill/skills/content-creator/`\n\n### Python Tools\n\n1. **Brand Voice Analyzer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py content.txt`\n\n2. **SEO Optimizer**\n   - **Path:** `../marketing-skill/skills/content-production/scripts/seo_optimizer.py`\n   - **Usage:** `python ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"keyword\"`\n```\n\n### Why `../../`?\n\nFrom agent location: `agents/marketing/cs-content-creator.md`\nTo skill location: `marketing-skill/content-creator/`\n\nNavigation: `agents/marketing/` → `../../` (up to root) → `marketing-skill/content-creator/`\n\n**Always test paths resolve correctly!**\n\n## Python Tool Integration\n\n### Execution Pattern\n\nAgents execute Python tools from skill packages:\n\n```bash\n# From agent context\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt\n\n# With JSON output\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py input.txt json\n\n# With arguments\npython ../product-team/skills/product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n```\n\n### Tool Requirements\n\nAll Python tools must:\n- Use standard library only (or minimal dependencies documented in SKILL.md)\n- Support both JSON and human-readable output\n- Provide `--help` flag with usage information\n- Return appropriate exit codes (0 = success, 1 = error)\n- Handle missing arguments gracefully\n\n### Error Handling\n\nWhen Python tools fail:\n1. Check file path resolution\n2. Verify input file exists\n3. Check Python version compatibility (3.8+)\n4. Review tool's `--help` output\n5. Inspect error messages in stderr\n\n## Workflow Documentation\n\n### Workflow Structure\n\nEach workflow must include:\n\n```markdown\n### Workflow 1: [Clear Descriptive Name]\n\n**Goal:** One-sentence description\n\n**Steps:**\n1. **[Action]** - Description with specific commands/tools\n2. **[Action]** - Description with specific commands/tools\n3. **[Action]** - Description with specific commands/tools\n\n**Expected Output:** What success looks like\n\n**Time Estimate:** How long this workflow takes\n\n**Example:**\n\\`\\`\\`bash\n# Concrete example command\npython ../marketing-skill/skills/content-production/scripts/seo_optimizer.py article.md \"primary keyword\"\n\\`\\`\\`\n```\n\n### Minimum Requirements\n\nEach agent must document **at least 3 workflows** covering:\n1. Primary use case (most common scenario)\n2. Advanced use case (complex scenario)\n3. Integration use case (combining multiple tools)\n\n## Agent Template\n\nUse this template when creating new agents:\n\n```markdown\n---\nname: cs-agent-name\ndescription: One-line description\ndomain: domain-name\nmodel: sonnet\ntools: [Read, Write, Bash, Grep, Glob]\n---\n\n# Agent Name\n\n## Purpose\n\n[2-3 paragraphs describing what this agent does, why it exists, and who it serves]\n\n## Skill Integration\n\n**Skill Location:** \\`../../domain-skill/skill-name/\\`\n\n### Python Tools\n\n1. **Tool Name**\n   - **Purpose:** What it does\n   - **Path:** \\`../../domain-skill/skill-name/scripts/tool.py\\`\n   - **Usage:** \\`python ../../domain-skill/skill-name/scripts/tool.py [args]\\`\n\n### Knowledge Bases\n\n1. **Reference Name**\n   - **Location:** \\`../../domain-skill/skill-name/references/file.md\\`\n   - **Content:** What's inside\n\n### Templates\n\n1. **Template Name**\n   - **Location:** \\`../../domain-skill/skill-name/assets/template.md\\`\n   - **Use Case:** When to use\n\n## Workflows\n\n### Workflow 1: [Name]\n\n**Goal:** Description\n\n**Steps:**\n1. Step 1\n2. Step 2\n3. Step 3\n\n**Expected Output:** Success criteria\n\n**Example:**\n\\`\\`\\`bash\npython ../../domain-skill/skill-name/scripts/tool.py input.txt\n\\`\\`\\`\n\n### Workflow 2: [Name]\n[Same structure]\n\n### Workflow 3: [Name]\n[Same structure]\n\n## Integration Examples\n\n[Concrete examples with actual commands and expected outputs]\n\n## Success Metrics\n\n- Metric 1: How to measure\n- Metric 2: How to measure\n- Metric 3: How to measure\n\n## Related Agents\n\n- [cs-related-agent](../<domain>/cs-related-agent.md) - How they relate\n\n## References\n\n- [Skill Documentation](../../domain-skill/skill-name/SKILL.md)\n- [Domain Roadmap](../../<domain-skill>/roadmap.md)\n```\n\n## Quality Standards\n\n### Agent Quality Checklist\n\nBefore committing an agent:\n\n- [ ] YAML frontmatter valid (no parsing errors)\n- [ ] All required fields present (name, description, skills, domain, model, tools)\n- [ ] cs-* prefix used for agent naming\n- [ ] Relative paths resolve correctly (../../ pattern)\n- [ ] Skill location documented and accessible\n- [ ] Python tools referenced with correct paths\n- [ ] At least 3 workflows documented\n- [ ] Integration examples provided and tested\n- [ ] Success metrics defined\n- [ ] Related agents cross-referenced\n\n### Testing Agent Integration\n\nTest these aspects:\n\n**1. Path Resolution**\n```bash\n# From agent directory\ncd agents/marketing/\nls ../marketing-skill/skills/content-creator/  # Should list contents\n```\n\n**2. Python Tool Execution**\n```bash\n# Create test input\necho \"Test content\" > test-input.txt\n\n# Execute tool\npython ../marketing-skill/skills/content-production/scripts/brand_voice_analyzer.py test-input.txt\n\n# Verify output\n```\n\n**3. Knowledge Base Access**\n```bash\n# Verify reference files exist\ncat ../marketing-skill/skills/content-creator/references/brand_guidelines.md\n```\n\n## Domain-Specific Guidelines\n\n### Marketing Agents (agents/marketing/)\n- Focus on content creation, SEO, demand generation\n- Reference: `../marketing-skill/`\n- Tools: brand_voice_analyzer.py, seo_optimizer.py\n\n### Product Agents (agents/product/)\n- Focus on prioritization, user research, agile workflows\n- Reference: `../product-team/`\n- Tools: rice_prioritizer.py, user_story_generator.py, okr_cascade_generator.py\n\n### C-Level Agents (agents/c-level/)\n- Focus on strategic decision-making\n- Reference: `../c-level-advisor/`\n- Tools: Strategic analysis and planning tools\n\n### Engineering Agents (agents/engineering/)\n- Focus on scaffolding, code quality, fullstack development\n- Reference: `engineering-team/`\n- Tools: project_scaffolder.py, code_quality_analyzer.py\n\n## Common Pitfalls\n\n**Avoid these mistakes:**\n\n❌ Hardcoding absolute paths\n❌ Skipping YAML frontmatter validation\n❌ Forgetting to test relative paths\n❌ Documenting workflows without examples\n❌ Creating agent dependencies (keep them independent)\n❌ Duplicating skill content in agent files\n❌ Using LLM calls instead of referencing Python tools\n\n## Next Steps\n\nAfter creating an agent:\n\n1. Test all relative paths resolve\n2. Execute all Python tools from agent context\n3. Verify all workflows with concrete examples\n4. Update agent catalog in main README.md\n5. Create GitHub issue for agent testing\n6. Commit with conventional commit message: `feat(agents): implement cs-agent-name`\n\n---\n\n**Last Updated:** June 10, 2026\n**Current:** 33 agents in this folder across 10 domain subfolders (93 agent files repo-wide)\n**Related:** See [main CLAUDE.md](../CLAUDE.md) for repository overview\n\n<!-- File: business-growth/CLAUDE.md (Tokens: ~1330 | Category: claude-rule) -->\n# Business & Growth Skills - Claude Code Guidance\n\nThis guide covers the 5 production-ready business and growth skills and their Python automation tools.\n\n## Business & Growth Skills Overview\n\n**Available Skills:**\n1. **customer-success-manager/** - Customer health scoring, churn risk analysis, expansion opportunities (3 Python tools)\n2. **sales-engineer/** - Technical discovery, RFP analysis, competitive positioning, POC planning (3 Python tools)\n3. **revenue-operations/** - Pipeline analysis, forecast accuracy, GTM efficiency metrics (3 Python tools)\n\n**Total Tools:** 9 Python automation tools, 9 knowledge bases, 19+ templates\n\n## Python Automation Tools\n\n### Customer Success Manager Tools\n\n#### 1. Health Score Calculator (`customer-success-manager/scripts/health_score_calculator.py`)\n\n**Purpose:** Multi-dimensional customer health scoring with trend analysis\n\n**Features:**\n- Weighted scoring across 4 dimensions (usage, engagement, support, relationship)\n- Red/Yellow/Green classification with configurable thresholds\n- Trend analysis comparing current vs previous period\n- Segment-aware benchmarking (Enterprise/Mid-Market/SMB)\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json\npython customer-success-manager/scripts/health_score_calculator.py customer_data.json --format json\n```\n\n#### 2. Churn Risk Analyzer (`customer-success-manager/scripts/churn_risk_analyzer.py`)\n\n**Purpose:** Identify at-risk accounts with intervention recommendations\n\n**Features:**\n- Risk scoring based on behavioral signals\n- Warning signal detection and categorization\n- Tier-appropriate intervention playbooks\n- Urgency-based prioritization\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json\npython customer-success-manager/scripts/churn_risk_analyzer.py customer_data.json --format json\n```\n\n#### 3. Expansion Opportunity Scorer (`customer-success-manager/scripts/expansion_opportunity_scorer.py`)\n\n**Purpose:** Identify upsell and cross-sell opportunities\n\n**Features:**\n- Adoption depth analysis across product modules\n- Whitespace mapping for unused features\n- Revenue opportunity estimation\n- Priority ranking by effort and impact\n\n**Usage:**\n```bash\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json\npython customer-success-manager/scripts/expansion_opportunity_scorer.py customer_data.json --format json\n```\n\n### Sales Engineer Tools\n\n#### 4. RFP Response Analyzer (`sales-engineer/scripts/rfp_response_analyzer.py`)\n\n**Purpose:** Score RFP/RFI coverage and identify gaps\n\n**Features:**\n- Requirement coverage scoring (Full/Partial/Planned/Gap)\n- Effort estimation per requirement\n- Gap identification with mitigation strategies\n- Overall bid/no-bid recommendation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json\npython sales-engineer/scripts/rfp_response_analyzer.py rfp_data.json --format json\n```\n\n#### 5. Competitive Matrix Builder (`sales-engineer/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Generate feature comparison matrices and competitive positioning\n\n**Features:**\n- Feature-by-feature comparison matrix\n- Competitive scoring with weighted categories\n- Differentiator identification\n- Battlecard-ready output\n\n**Usage:**\n```bash\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json\npython sales-engineer/scripts/competitive_matrix_builder.py competitive_data.json --format json\n```\n\n#### 6. POC Planner (`sales-engineer/scripts/poc_planner.py`)\n\n**Purpose:** Plan proof-of-concept engagements\n\n**Features:**\n- Timeline estimation based on scope\n- Resource allocation planning\n- Success criteria definition\n- Evaluation scorecard generation\n\n**Usage:**\n```bash\npython sales-engineer/scripts/poc_planner.py poc_data.json\npython sales-engineer/scripts/poc_planner.py poc_data.json --format json\n```\n\n### Revenue Operations Tools\n\n#### 7. Pipeline Analyzer (`revenue-operations/scripts/pipeline_analyzer.py`)\n\n**Purpose:** Analyze sales pipeline health and velocity\n\n**Features:**\n- Coverage ratio calculation (pipeline/quota)\n- Stage conversion rate analysis\n- Sales velocity metrics (4-lever model)\n- Deal aging analysis\n\n**Usage:**\n```bash\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json\npython revenue-operations/scripts/pipeline_analyzer.py pipeline_data.json --format json\n```\n\n#### 8. Forecast Accuracy Tracker (`revenue-operations/scripts/forecast_accuracy_tracker.py`)\n\n**Purpose:** Measure and improve forecast accuracy\n\n**Features:**\n- MAPE (Mean Absolute Percentage Error) calculation\n- Forecast bias detection (over/under-forecasting)\n- Period-over-period trend analysis\n- Category-level accuracy breakdown\n\n**Usage:**\n```bash\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json\npython revenue-operations/scripts/forecast_accuracy_tracker.py forecast_data.json --format json\n```\n\n#### 9. GTM Efficiency Calculator (`revenue-operations/scripts/gtm_efficiency_calculator.py`)\n\n**Purpose:** Calculate go-to-market efficiency metrics\n\n**Features:**\n- Magic number calculation\n- LTV:CAC ratio analysis\n- CAC payback period\n- Burn multiple assessment\n- Industry benchmarking\n\n**Usage:**\n```bash\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json\npython revenue-operations/scripts/gtm_efficiency_calculator.py gtm_data.json --format json\n```\n\n## Quality Standards\n\n**All business & growth Python tools must:**\n- Use standard library only (no external dependencies)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **Marketing:** Content creation, demand generation -> `../marketing-skill/`\n- **Product Team:** User research, feature prioritization -> `../product-team/`\n- **C-Level:** Strategic planning -> `../c-level-advisor/`\n- **Engineering:** Technical implementation -> `../engineering-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 5/5 business & growth skills production-ready\n**Total Tools:** 9 Python automation tools\n\n<!-- File: business-operations/CLAUDE.md (Tokens: ~992 | Category: claude-rule) -->\n# Business Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `business-operations/`.\n\n## Purpose\n\nThe Business Operations domain ships skills that help **internal operators** (BizOps lead, COO direct reports, vendor management office, IT ops) run the company day-to-day. This is **not strategy** (that's `c-level-advisor/`) and **not external sales** (that's `business-growth/`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Job-to-be-done | `context: fork`? |\n|---|---|---|\n| `business-operations-skills` | Domain orchestrator — routes inquiries to the 6 sub-skills | YES |\n| `process-mapper` | BPMN-style process docs + bottleneck + cycle-time (Lean / TOC canon) | YES |\n| `vendor-management` | Vendor scoring + SLA + third-party risk (NIST SP 800-161 / ISO 27036) | YES |\n| `capacity-planner` | Erlang-C queueing math for ops teams (NOT engineering capacity) | NO |\n| `internal-comms` | ADKAR + Kotter 8-step change comms (NOT marketing) | NO |\n| `knowledge-ops` | SOPs + runbooks with 5W2H validation + KB hygiene (NOT personal PKM) | YES |\n| `procurement-optimizer` | UNSPSC-aligned spend categorization + supplier consolidation | NO |\n\n## Build pattern\n\nPath-B 11-file contract per skill (Matt Pocock-derived discipline preserved):\n\n```\nskill/\n├── SKILL.md                  # YAML frontmatter + workflow + forcing-question library\n├── scripts/                  # 3 stdlib-only Python CLI tools\n├── references/               # 3 ref docs, ≥ 7 cited sources each\n└── assets/                   # ≥ 1 user-customizable template\n```\n\n## Hard rules\n\n1. **Stdlib-only Python** — no `requests`, `pandas`, `numpy`. Just `argparse`, `json`, `sys`, `pathlib`, `statistics`, `dataclasses`, `enum`, `datetime`, `math`, `re`, `collections`.\n2. **Deterministic logic** — no LLM calls in scripts. Same input → same output. Erlang-C math implemented in log-space to avoid factorial overflow.\n3. **Industry tuning** — every scoring tool exposes `--profile {saas,services,manufacturing,healthcare,…}` for threshold calibration.\n4. **Matt Pocock grill discipline** — orchestrator routes via one-question-per-turn with a recommended answer + canon citation. Never bundles. Never auto-routes silently after a question. Every SKILL.md ships a \"Forcing-question library\" section with 5-7 cited canon-anchored questions.\n5. **Output is recommendation, not approval** — `vendor-management` never says \"replace this vendor\"; `procurement-optimizer` never auto-consolidates suppliers; the human always decides.\n\n## Agent + command pattern\n\n- `cs-bizops-orchestrator` — the persona agent. Voice: \"Where does the work spend most of its time waiting?\" (Theory of Constraints anchor).\n- `/cs-bizops <inquiry>` — top-level router.\n- `/cs-grill-bizops <plan>` — Matt-style docs-anchored grilling **before** routing.\n- `/cs-process-map`, `/cs-vendor-review`, `/cs-capacity-plan`, `/cs-internal-comms`, `/cs-knowledge-ops`, `/cs-procurement` — direct per-skill invocation.\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/*` (external sales motion) — BizOps is **internal**\n- ❌ Skills that overlap `c-level-advisor/coo-advisor` — that's strategic; BizOps is tactical\n- ❌ \"Process improvement consultant\" generic skills — every skill must answer a SPECIFIC question (e.g., \"where's the bottleneck?\", \"is this vendor delivering?\", \"are we sized to peak demand?\", not \"how can we improve operations?\")\n- ❌ Tools without `--profile` tuning — every score must be industry-tunable\n- ❌ Bundled questions in the orchestrator — Matt's rule: one at a time, with a recommended answer\n- ❌ Engineering-specific framing in capacity-planner — that's vpe-advisor's lane\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-me`, `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/coo-advisor`\n\n<!-- File: c-level-advisor/CLAUDE.md (Tokens: ~2455 | Category: claude-rule) -->\n# C-Level Advisory Skills — Claude Code Guidance\n\nA complete virtual board of directors: 28 skills covering 10 executive roles, orchestration, cross-cutting capabilities, and culture & collaboration frameworks — plus the new **c-level-agents** plugin layer that surfaces 8 cs-* persona agents and 17 `/cs-*` slash commands on top of the skills.\n\n## Architecture\n\n```\n/cs-onboard setup (Founder Interview) → company-context.md\n                │\n        Chief of Staff (Router)\n                │\n    ┌───────────┼───────────┐\n    10 Roles    6 Cross-Cut  6 Culture\n    │           │            │\n    └───────────┼────────────┘\n                │\n        Executive Mentor (Critic)\n                │\n        Decision Logger (Two-Layer Memory)\n```\n\n## Skills Overview\n\n### C-Suite Roles (15)\n\n| Role | Folder | Reasoning Technique | Scripts |\n|------|--------|-------------------|---------|\n| **CEO** | `ceo-advisor/` | Tree of Thought | strategy_analyzer, financial_scenario_analyzer |\n| **CTO** | `cto-advisor/` | ReAct | tech_debt_analyzer, team_scaling_calculator |\n| **COO** | `coo-advisor/` | Step by Step | ops_efficiency_analyzer, okr_tracker |\n| **CPO** | `cpo-advisor/` | First Principles | pmf_scorer, portfolio_analyzer |\n| **CMO** | `cmo-advisor/` | Recursion of Thought | marketing_budget_modeler, growth_model_simulator |\n| **CFO** | `cfo-advisor/` | Chain of Thought | burn_rate_calculator, unit_economics_analyzer, fundraising_model |\n| **CRO** | `cro-advisor/` | Chain of Thought | revenue_forecast_model, churn_analyzer |\n| **CISO** | `ciso-advisor/` | Risk-Based | risk_quantifier, compliance_tracker |\n| **CHRO** | `chro-advisor/` | Empathy + Data | hiring_plan_modeler, comp_benchmarker |\n| **General Counsel** | `general-counsel-advisor/` | Risk-Based | contract_risk_scanner, term_sheet_analyzer |\n| **Chief Data Officer** | `chief-data-officer-advisor/` | Decision-Driven | ai_training_data_audit, data_product_strategy_picker, data_asset_valuator |\n| **Chief AI Officer** | `chief-ai-officer-advisor/` | Eval-Demanding | model_buildvsbuy_calculator, ai_risk_classifier, ai_cost_economics |\n| **Chief Customer Officer** | `chief-customer-officer-advisor/` | Retention-Obsessed | retention_decomposition_analyzer, customer_segmentation_designer, cs_coverage_calculator |\n| **VP of Engineering** ⭐ NEW v2.5.5 | `vpe-advisor/` | Throughput-First | delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer |\n| **Executive Mentor** | `executive-mentor/` | Adversarial | decision_matrix_scorer, stakeholder_mapper |\n\n### Orchestration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **C-Suite Onboard** | `cs-onboard/` | Founder interview → company-context.md |\n| **Chief of Staff** | `chief-of-staff/` | Routes questions, triggers board meetings |\n| **Board Meeting** | `board-meeting/` | 6-phase multi-agent deliberation |\n| **Decision Logger** | `decision-logger/` | Two-layer memory (raw + approved) |\n| **Agent Protocol** | `agent-protocol/` | Inter-agent invocation, loop prevention, quality loop |\n| **Context Engine** | `context-engine/` | Company context loading + anonymization |\n\n### Cross-Cutting Capabilities (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Board Deck Builder** | `board-deck-builder/` | Assembles board/investor updates |\n| **Scenario War Room** | `scenario-war-room/` | Multi-variable what-if modeling |\n| **Competitive Intel** | `competitive-intel/` | Systematic competitor tracking |\n| **Org Health Diagnostic** | `org-health-diagnostic/` | Cross-functional health scoring |\n| **M&A Playbook** | `ma-playbook/` | Acquiring or being acquired |\n| **International Expansion** | `intl-expansion/` | Market entry strategy |\n\n### Culture & Collaboration (6)\n\n| Skill | Folder | Purpose |\n|-------|--------|---------|\n| **Culture Architect** | `culture-architect/` | Build and operationalize culture |\n| **Company OS** | `company-os/` | EOS/Scaling Up operating system |\n| **Founder Coach** | `founder-coach/` | Founder development and growth |\n| **Strategic Alignment** | `strategic-alignment/` | Strategy cascade, silo detection |\n| **Change Management** | `change-management/` | ADKAR-based change rollout |\n| **Internal Narrative** | `internal-narrative/` | One story across all audiences |\n\n## c-level-agents Plugin (v1.0.0 — new in v2.5.0)\n\nA separate plugin at the repo's top-level `c-level-agents/` directory (moved out of `c-level-advisor/` in #949 so the two marketplace sources no longer overlap) that wraps the 10 C-roles with persona agents and slash commands. Founder-mode entry layer.\n\n### 13 cs-* Agents (in `../c-level-agents/agents/`)\n\n| Agent | Voice | Wraps Skill |\n|---|---|---|\n| cs-cfo-advisor | Numerate skeptic | cfo-advisor |\n| cs-cmo-advisor | Narrative-first | cmo-advisor |\n| cs-cro-advisor | Pipeline-paranoid | cro-advisor |\n| cs-cpo-advisor | JTBD-driven | cpo-advisor |\n| cs-coo-advisor | Execution OS | coo-advisor |\n| cs-chro-advisor | People-systems | chro-advisor |\n| cs-ciso-advisor | Risk-paranoid | ciso-advisor |\n| cs-chief-of-staff | Router & synthesist | chief-of-staff |\n| cs-general-counsel-advisor | Risk-paranoid (legal) | general-counsel-advisor |\n| cs-cdo-advisor | Decision-driven (data) | chief-data-officer-advisor |\n| cs-caio-advisor | Eval-demanding (AI) | chief-ai-officer-advisor |\n| cs-cco-advisor | Retention-obsessed (customer) | chief-customer-officer-advisor |\n| cs-vpe-advisor ⭐ NEW v2.5.5 | Throughput-first (engineering ops) | vpe-advisor |\n\nExisting `cs-ceo-advisor` and `cs-cto-advisor` live in `/agents/c-level/` and integrate with the same protocol.\n\n### 17 /cs-* Slash Commands (in `../c-level-agents/skills/`)\n\n**Forcing-question office hours (8):** `/c-level-agents:office-hours`, `/c-level-agents:cfo-review`, `/c-level-agents:cmo-review`, `/c-level-agents:cpo-review`, `/c-level-agents:cro-review`, `/c-level-agents:cto-review`, `/c-level-agents:ciso-review`, `/c-level-agents:gc-review`\n\n**Strategic sprint pipeline (5):** `/c-level-agents:brief` → `/c-level-agents:boardroom` → `/c-level-agents:decide` → `/c-level-agents:execute` → `/c-level-agents:post-mortem`\n\n**Meta + safety (4):** `/c-level-agents:founder-mode` (auto-router), `/cs-onboard` (founder interview), `/c-level-agents:cross-eval` (multi-model consensus), `/c-level-agents:freeze` (cooldown lock)\n\nSee [c-level-agents/README.md](../c-level-agents/README.md) for the full plugin guide and [c-level-agents/references/persona-voices.md](../c-level-agents/references/persona-voices.md) for voice specs.\n\n## Executive Mentor Slash Commands\n\nThe only skill with a `plugin.json` (namespace: `em`) because it has slash commands. Other skills are invoked by name through the Chief of Staff router or directly by the user. This is intentional — only add `plugin.json` when a skill has dedicated slash commands that need a namespace.\n\n| Command | Purpose |\n|---------|---------|\n| `/em:challenge` | Pre-mortem analysis of any plan |\n| `/em:board-prep` | Board meeting preparation |\n| `/em:hard-call` | Framework for hard decisions |\n| `/em:stress-test` | Stress-test any assumption |\n| `/em:postmortem` | Honest retrospective |\n\n## Key Design Decisions\n\n- **Two-layer memory:** Raw transcripts (reference) + approved decisions only (feeds future meetings). Prevents hallucinated consensus.\n- **Phase 2 isolation:** During board meetings, agents think independently before cross-examination.\n- **Internal Quality Loop:** Self-verify → peer-verify → critic pre-screen → present. No unverified output reaches the founder.\n- **Proactive triggers:** Every role has context-driven early warnings that surface issues without being asked.\n- **User Communication Standard:** Bottom Line → What → Why → How to Act → Your Decision. Results only, no process narration.\n\n## Python Tools (25 total)\n\nAll scripts are stdlib-only, CLI-first, with JSON output and embedded sample data.\n\n```bash\n# Examples\npython cfo-advisor/scripts/burn_rate_calculator.py\npython cro-advisor/scripts/churn_analyzer.py\npython cpo-advisor/scripts/pmf_scorer.py\npython org-health-diagnostic/scripts/health_scorer.py\npython strategic-alignment/scripts/alignment_checker.py\npython decision-logger/scripts/decision_tracker.py\n```\n\n## Integration with Other Domains\n\n| C-Level Role | Layers Above |\n|-------------|-------------|\n| CMO | marketing-skill/ (content, demand gen, ASO execution) |\n| CFO | finance/financial-analyst (spreadsheets, DCF) |\n| CRO | business-growth/ (revenue ops, sales engineering) |\n| CISO | ra-qm-team/ (ISO 27001 checklists, ISMS audits) |\n| CPO | product-team/ (PM toolkit, user stories, sprint planning) |\n\n---\n\n**Last Updated:** 2026-05-13\n**Skills Deployed:** 33 skills (15 roles incl. General Counsel, CDO, CAIO, CCO, and VPE + 5 mentor commands + 6 orchestration + 6 cross-cutting + 6 culture) + 21 /cs-* sub-skills in c-level-agents plugin\n**Agents:** 15 cs-* (cs-ceo, cs-cto in /agents/c-level/; 13 in ../c-level-agents/agents/ including new cs-vpe-advisor)\n**Python Tools:** 39 (stdlib-only) — +3 with vpe-advisor (delivery_throughput_analyzer, eng_hiring_funnel_calculator, eng_team_structure_designer)\n**Reference Docs:** 73 (71 in skills + 2 in c-level-agents/references)\n\n<!-- File: CLAUDE.md (Tokens: ~12596 | Category: claude-rule) -->\n# CLAUDE.md\n\nThis file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.\n\n## Project Purpose\n\nThis is a **comprehensive skills library** for Claude AI and Claude Code - reusable, production-ready skill packages that bundle domain expertise, best practices, analysis tools, and strategic frameworks. The repository provides modular skills that teams can download and use directly in their workflows.\n\n**Current Scope:** 398 production-ready skills across 20 domains with 766 Python automation tools, 877 reference guides, 123 agents (cs-* + 7 personas), and 157 slash commands, distributed as 104 marketplace plugins. Headline counters are derived from the tree by `scripts/derive_counters.py` (run with `--check` to verify the docs still match). **v2.11.2 (current)** vendors **engineering/skillopt-sleep/** — started as a verbatim, byte-for-byte copy of `microsoft/SkillOpt`'s `skillopt_sleep` engine (stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), then received 23 targeted patches after ten rounds of adversarial review (see `engineering/skillopt-sleep/README.md`'s numbered \"Deviations from upstream\" list, the authoritative source — re-apply all 23 on re-vendor). Gives a local agent a nightly \"sleep cycle\": read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget. The heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) was deliberately **not** vendored — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit. Attribution preserved in `.claude-plugin/authoring-notes.json` + `LICENSE` + `README.md` (MIT, © Microsoft Corporation / Yifan Yang), following the same verbatim-vendor pattern as `loop-library/`. **Unreleased (post-v2.11.2, PR #961 merged)** adds the **agent-launcher/** top-level domain — a plugin re-implementation of Anthropic's `launch-your-agent` reference skill (Apache-2.0; independent, not a fork) for building **Claude Managed Agents (CMA)** in the user's own account. Every session starts with a goal (`./my-agent/goal.json`, surfaced by an opt-in `AGENT_LAUNCHER_SESSION=1` SessionStart hook + `/cs-goal`); `loop_compiler.py` compiles that goal into a **bounded grade→iterate loop** (CMA `user.define_outcome` self-grading, `max_iterations` 1..20), a **recurring POSIX-cron scheduled-deployment loop**, or a **single-pass interview→stage→launch workflow**. 6 skills (orchestrator `context: fork` + interview + stage-launch + grade-iterate + run-without-you + wrap-up), 18 stdlib-only deterministic scaffolder tools (NO network/API calls — live launches emitted as BYOK curl that never prints the key), 4 agents, 8 `/cs-*` commands, opt-in hooks, 5 shared references, 4 assets; validators enforce CMA limits (≤20 skills/session, ≤8 memory stores, depth-1 multiagent, `max_iterations` ≤20, ≤1000 deployments/org). Distinct from `engineering/agent-harness` (generic bounded loop over any domain) and `engineering/write-a-skill` (authors Claude Code skills, not CMAs). **Unreleased (post-v2.11.2)** ships the **productivity coverage expansion** — public audit record `audit/productivity-2026-07/` (all 7 legacy skills scored, 24/24 scripts smoke-tested, coverage map vs the personal-productivity canon) + 3 gap-filling plugins, each with a cs-* agent, /cs-* commands, 3 stdlib scripts and 3 cited references: **weekly-review** (GTD loop; review-gate refuses COMPLETE while a mandatory GET CURRENT step is missing), **deep-work** (time-block planner refusing >4h deep demand, shallow-work budget auditor, focus-session logger), **meetings** (MEET/ASYNC/NOT-READY cost gate, outcome-required agenda builder, action-item extractor with ORPHAN/NO-DUE flags). **Unreleased (post-v2.11.1)** added **productivity/fable-goal** — converts a rambling description of a desired outcome into one polished, copy-paste `/goal` prompt for a fresh autonomous session (ported from `duncan-buildroom/freeskills`). **v2.11.1 (complete)** upgrades **product-team/** and **project-management/** into agent-harness domains: both prose routers rebuilt as `context: fork` orchestrators with deterministic goal routers (exit-code route/ask/refuse), a Jira MCP snapshot bridge (Kanban-Guide-2025 flow metrics + seeded Monte Carlo forecasts, verified end-to-end into velocity_analyzer), a delegation-governance loop gate (human owner / reviewer / machine-checkable acceptance / close refusal), a Torres continuous-discovery cadence tracker + Opportunity Solution Tree linter, cs-pm-orchestrator + cs-product-orchestrator agents, and /cs-pm|grill-pm|pm-loop + /cs-product|grill-product|product-loop commands — plus the public audit record `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria). **v2.9.0 (complete)** added the **research-ops/** top-level domain — enterprise Research Operations (orchestrator + clinical-research + research-finance + market-research + product-research), the managed counterpart to the academic research/ domain, with `context: fork` orchestration and a Matt Pocock \"Forcing-question library\" in every SKILL.md plus `/cs-grill-research-ops`. **v2.8.0 (complete)** added 2 new top-level domains — **business-operations/** (7 internal-ops skills: orchestrator + process-mapper + vendor-management + capacity-planner + internal-comms + knowledge-ops + procurement-optimizer) and **commercial/** (8 per-deal-economics skills: orchestrator + pricing-strategist + deal-desk + partnerships-architect + channel-economics + commercial-policy + rfp-responder + commercial-forecaster) — with orchestrator skills using `context: fork` for chaining, Matt Pocock docs-anchored \"Forcing-question library\" in every SKILL.md, plus `/cs-grill-bizops` and `/cs-grill-commercial`. **v2.8.2** adds a productivity-shaped `handoff` skill (sibling to engineering/handoff) inspired by Matt Pocock — first-run setup with configurable save location, redaction linter, SessionStart + SessionEnd hooks, fidelity self-check, `--refresh` flag. **v2.8.1** upgraded the engineering role-skills (senior-fullstack / senior-frontend / senior-backend) with karpathy-coder + Matt Pocock decision engines + per-role forcing questions. v2.7.3 ports `alirezarezvani/aeo-box` — AEO (Answer Engine Optimization) skill into marketing-skill/ + security-guidance PreToolUse hook into engineering/. v2.7.0 added 13 Path-B skills across 3 top-level domains (productivity, marketing, research). v2.6.0 added 4 Matt Pocock-derived productivity skills.\n\n**Key Distinction**: This is NOT a traditional application. It's a library of skill packages meant to be extracted and deployed by users into their own Claude workflows.\n\n## Maintainer-Local Folders (gitignored)\n\nThe following exist on the maintainer's disk but are excluded from the public GitHub tree so cloners only see production skill packages:\n\n- `documentation/` — sprint plans, strategy, implementation roadmaps\n- `eval-workspace/` — Tessl evaluation outputs\n- `megaprompts/` — pre-skill draft specs (Path-B source material)\n- `tests/` — pytest suite (run locally; not in CI)\n- `.autoresearch/` — autoresearch agent workspace\n- `AUDIT_REPORT.md` — internal audit snapshots\n\n**Distinct from the above:** the top-level `audit/` directory (e.g.\n`audit/newgen-2026-06/`) is an **intentional, public** audit record — rubric +\nper-domain reports with per-skill verification criteria that follow-up PRs use\nas acceptance gates. It is excluded from headline counters by\n`scripts/derive_counters.py`, but it is committed and visible to cloners.\n`AUDIT_REPORT.md` (gitignored, above) is the older internal-snapshot format.\n\nIn-repo references to paths under these folders (e.g. `documentation/implementation/...`) resolve locally for the maintainer but appear as dead links on GitHub. This is intentional.\n\n## Navigation Map\n\nThis repository uses **modular documentation**. For domain-specific guidance, see:\n\n| Domain | CLAUDE.md Location | Focus |\n|--------|-------------------|-------|\n| **Agent Development** | [agents/CLAUDE.md](agents/CLAUDE.md) | cs-* agent creation, YAML frontmatter, relative paths |\n| **Marketing Skills** | [marketing-skill/CLAUDE.md](marketing-skill/CLAUDE.md) | Content creation, SEO, ASO, demand gen, campaign analytics |\n| **Product Team** | [product-team/CLAUDE.md](product-team/CLAUDE.md) | RICE, OKRs, user stories, UX research, SaaS scaffolding |\n| **Engineering (Core)** | [engineering-team/CLAUDE.md](engineering-team/CLAUDE.md) | Fullstack, AI/ML, DevOps, security, data, QA tools |\n| **Engineering (POWERFUL)** | [engineering/](engineering/) | Agent design, RAG, MCP, CI/CD, database, observability |\n| **C-Level Advisory** | [c-level-advisor/CLAUDE.md](c-level-advisor/CLAUDE.md) | CEO/CTO strategic decision-making |\n| **Project Management** | [project-management/CLAUDE.md](project-management/CLAUDE.md) | Atlassian MCP, Jira/Confluence integration |\n| **RA/QM Compliance** | [ra-qm-team/CLAUDE.md](ra-qm-team/CLAUDE.md) | ISO 13485, MDR, FDA, GDPR, ISO 27001 compliance |\n| **Business & Growth** | [business-growth/CLAUDE.md](business-growth/CLAUDE.md) | Customer success, sales engineering, revenue operations |\n| **Finance** | [finance/CLAUDE.md](finance/CLAUDE.md) | Financial analysis, DCF valuation, budgeting, forecasting, SaaS metrics |\n| **Research Operations** | [research-ops/CLAUDE.md](research-ops/CLAUDE.md) | Clinical study design, R&D finance, market research, product research (enterprise counterpart to academic research/) |\n| **Markdown → HTML** | [markdown-html/CLAUDE.md](markdown-html/CLAUDE.md) | Markdown-to-interactive-HTML converter (orchestrator + design-system foundation; md-document/review/slides v2.10.1). Inspired by Shihipar's \"Claude Code HTML output\" essay |\n| **Agent Launcher** | [agent-launcher/CLAUDE.md](agent-launcher/CLAUDE.md) | Claude Managed Agent (CMA) launcher — session-goal orchestrator + interview / stage-launch / grade-iterate / run-without-you / wrap-up; deterministic BYOK-curl scaffolders; bounded grade→iterate + cron deployment loops. Re-implements anthropics/launch-your-agent (Apache-2.0) |\n| **Standards Library** | [standards/CLAUDE.md](standards/CLAUDE.md) | Communication, quality, git, security standards |\n| **Templates** | [templates/CLAUDE.md](templates/CLAUDE.md) | Template system usage |\n\n## Architecture Overview\n\n### Repository Structure\n\n```\nclaude-code-skills/\n├── .claude-plugin/            # Plugin registry (marketplace.json)\n├── agents/                    # 32 standalone agents (cs-* + 7 personas); 51+ cs-* agents repo-wide\n├── commands/                  # slash commands (changelog, tdd, saas-health, prd, code-to-prd, plugin-audit, sprint-plan, slo-design, etc.); 87+ repo-wide\n├── engineering-team/          # 51 core engineering skills + Playwright Pro + Self-Improving Agent + Security Suite\n├── engineering/               # 81 POWERFUL-tier advanced skills (incl. AgentHub, autoresearch-agent, self-eval, llm-wiki, tc-tracker, ship-gate, slo-architect, write-a-skill, caveman, grill-me, handoff, agent-harness)\n├── product-team/              # 17 product skills (incl. apple-hig-expert) + Python tools\n├── marketing-skill/           # 46 marketing skills (8 pods) + Python tools\n├── c-level-advisor/           # 66 C-level advisory skills (full C-suite + founder-mode agents + orchestration)\n├── project-management/        # 9 PM skills + bundled Atlassian Remote MCP (.mcp.json)\n├── ra-qm-team/                # 18 RA/QM compliance skills\n├── compliance-os/             # 9 compliance-OS skills\n├── business-growth/           # 5 business & growth skills + Python tools\n├── business-operations/       # 7 internal-ops skills (orchestrator + 6 sub-skills)\n├── commercial/                # 8 per-deal-economics skills (orchestrator + 7 sub-skills)\n├── finance/                   # 4 finance skills + Python tools\n├── research/                  # 8 academic research skills (orchestrator + 7 specialists)\n├── research-ops/              # 5 research-ops skills (orchestrator + clinical-research + research-finance + market-research + product-research)\n├── markdown-html/             # 2 markdown-to-HTML skills v2.10.0 foundation (orchestrator + design-system); md-document/review/slides land in v2.10.1\n├── agent-launcher/            # 6 CMA-launcher skills (session-goal orchestrator + 5 phase skills; 18 BYOK-curl scaffolder tools, opt-in SessionStart goal hook)\n├── eval-workspace/            # Skill evaluation results (Tessl)\n├── standards/                 # 5 standards library files\n├── templates/                 # Reusable templates\n├── docs/                      # MkDocs Material documentation site\n├── scripts/                   # Build scripts (docs generation)\n└── documentation/             # Implementation plans, sprints, delivery\n```\n\n### Skill Package Pattern\n\nEach skill follows this structure:\n```\nskill-name/\n├── SKILL.md              # Master documentation\n├── scripts/              # Python CLI tools (no ML/LLM calls)\n├── references/           # Expert knowledge bases\n└── assets/               # User templates\n```\n\n**Design Philosophy**: Skills are self-contained packages. Each includes executable tools (Python scripts), knowledge bases (markdown references), and user-facing templates. Teams can extract a skill folder and use it immediately.\n\n**Key Pattern**: Knowledge flows from `references/` → into `SKILL.md` workflows → executed via `scripts/` → applied using `assets/` templates.\n\n## Git Workflow\n\n**Branch Strategy:** feature → dev → main (PR only)\n\n> **⛔ HARD RULE — PR TARGET IS ALWAYS `dev`, NEVER `main`.**\n> Every PR (human or AI-created) must use `--base dev`. Nothing merges into `main`\n> directly — `main` only receives periodic `dev → main` promotion PRs opened by the\n> maintainer. If you find a PR targeting `main`, retarget it to `dev` before review.\n> AI agents (Claude Code included): set the base branch explicitly when creating PRs;\n> never rely on the repository default branch.\n\n**Branch Protection Active:** Main branch requires PR approval. Direct pushes blocked.\n\n### Quick Start\n\n```bash\n# 1. Always start from dev\ngit checkout dev\ngit pull origin dev\n\n# 2. Create feature branch\ngit checkout -b feature/agents-{name}\n\n# 3. Work and commit (conventional commits)\nfeat(agents): implement cs-{agent-name}\nfix(tool): correct calculation logic\ndocs(workflow): update branch strategy\n\n# 4. Push and create PR to dev\ngit push origin feature/agents-{name}\ngh pr create --base dev --head feature/agents-{name}\n\n# 5. After approval, PR merges to dev\n# 6. Periodically, dev merges to main via PR\n```\n\n**Branch Protection Rules:**\n- ✅ Main: Requires PR approval, no direct push\n- ✅ Dev: Unprotected, but PRs recommended\n- ✅ All: Conventional commits enforced\n\nSee [documentation/WORKFLOW.md](documentation/WORKFLOW.md) for complete workflow guide.\nSee [standards/git/git-workflow-standards.md](standards/git/git-workflow-standards.md) for commit standards.\n\n## Development Environment\n\n**No build system or test frameworks** - intentional design choice for portability.\n\n**Python Scripts:**\n- Use standard library only (minimal dependencies)\n- CLI-first design for easy automation\n- Support both JSON and human-readable output\n- No ML/LLM calls (keeps skills portable and fast)\n\n**If adding dependencies:**\n- Keep scripts runnable with minimal setup (`pip install package` at most)\n- Document all dependencies in SKILL.md\n- Prefer standard library implementations\n\n## Current Version\n\n**Version:** v2.14.1 (audit fix release: all 104 plugins bumped so `claude plugin update` reaches existing installs, new version-bump gate G11, category-scoped Codex installer, `${CLAUDE_PLUGIN_ROOT}` script paths, productivity handoff renamed session-handoff. See CHANGELOG.md [2.14.1].)\n\n**Previously: v2.14.0** (audit skills release: agent-regression-evals, coding-agent-rollout and month-end-close plugins, open-source-first youtube-full, claude-coach plugin renamed to power-user-coach with a one-time reinstall. See CHANGELOG.md [2.14.0].)\n\n**Previously: v2.13.0** (October triage and quality-audit release: runnable command names, self-contained c-level-agents/compliance-os, hivemind as an opt-in plugin, six new skills from the community backlog. See CHANGELOG.md [2.13.0].)\n\n**Previously: v2.12.0** (consolidated release — 20 domains, 380 skills; full reported-issue triage sweep; first tag since v2.9.0. See CHANGELOG.md [2.12.0].)\n\n---\n\n**Previously: v2.11.2** (skillopt-sleep — vendored nightly self-improvement plugin from microsoft/SkillOpt)\n\n**v2.11.2 highlights — engineering/skillopt-sleep/:**\n\nVendors `engineering/skillopt-sleep/` — a byte-for-byte start from [microsoft/SkillOpt](https://github.com/microsoft/SkillOpt)'s `skillopt_sleep` engine (32 files, stdlib-only, zero third-party deps) and its Claude Code plugin surface (`skills/`, `hooks/`, `commands/`, `scripts/`), following the same verbatim-vendor pattern as `loop-library/`. Gives a local agent a nightly gated self-improvement cycle: read-only harvest of past Claude Code session transcripts → mine recurring tasks → replay offline on the user's own API budget → consolidate into `CLAUDE.md`/`SKILL.md` edits behind a held-out validation gate → stage for review; nothing live changes until an explicit `/skillopt-sleep adopt` (which backs up first). Default `mock` backend spends no API budget.\n\n- **Deliberately not vendored:** the heavier `skillopt` *training* package (benchmark-driven, needs `numpy`/`openai`/`azure-*` + hand-labeled train/val/test data per task) — it optimizes one narrow, scoreable task at a time, which doesn't fit this repo's broad domain-expertise skills or its no-ML-in-scripts/no-test-framework conventions; `skillopt_sleep` mines its \"benchmark\" from real usage instead, which does fit.\n- **23 deviations from upstream (6 cosmetic, 17 safety/hardening)**, found across ten rounds of adversarial code review rather than assumed safe from the surface docs. The **numbered list in `engineering/skillopt-sleep/README.md`'s \"Deviations from upstream\" section is the single source of truth** — the plugin's `authoring-notes.json` `attribution.derivation_note` and this bullet are both summaries of it, kept in sync by hand; if any of the three ever disagree on the count again, README.md wins. Highlights: `redact_secrets()` now covers every artifact that goes live or persists — `proposed_SKILL.md`/`proposed_CLAUDE.md`, the cross-night task archive (`state.json`), `report.md`/`report.json` (previously only `diagnostics.json` was scrubbed, despite `report.md` being the file the SKILL.md's own workflow tells a human to read *first*), and — the gap that survived seven review rounds because every earlier fix was file-level — the CLI's own `cmd_run`/`cmd_harvest` console/`--json`/`--output` output, which read the same unredacted in-memory `Report`/`TaskRecord` objects and (via `scheduler.py`'s cron redirect) could leak straight into `cron.log`; the generated crontab line is fully `shlex.quote()`-d including the `extra` flags param, and `cron.log` itself is now `chmod 600` (previously uncovered by the state/staging chmod pass); `scheduler.py`'s per-project cron-line marker match is now anchored on end-of-line rather than a bare substring test, closing a real bug where scheduling/unscheduling one project could silently drop a sibling project's job whose path happened to be a prefix of it; the previously-dead `max_tokens_per_night` config key now sizes `dream_rollouts` down via the engine's own `plan_depth()` heuristic; a hardcoded internal Azure OpenAI backend (5 internal-looking endpoint hostnames + a Managed Identity client ID) was removed rather than carried forward; tool-shim names reachable via `--tasks-file` are now validated against a safe-identifier allowlist before use as a filename or shell text; `commands/skillopt-sleep.md` now tells the agent to confirm with the user before `schedule` (which installs a real crontab entry immediately, unlike every other action); every directory/file `state.py`/`staging.py` create is `chmod 0700`/`0600` rather than left at the world-readable process umask default.\n- One documented, opt-in exception to CLAUDE.md's \"no LLM calls in scripts\" anti-pattern (see that section) — `backend.py`'s `claude`/`codex` backends shell out to those CLIs only when a non-`mock` backend is explicitly selected.\n- Registered as its own installable marketplace plugin; **counters:** skills 358 → 359; tools 603 → 635; refs 732 (unchanged); commands 110 → 111; plugins 84 → 85 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**v2.14.0 — three audit-proposed skills (agent-regression-evals, coding-agent-rollout, month-end-close):**\n\nBuilt from the October quality audit's new-skill proposals, ranked by impact on teams. Each is a\nstandalone plugin mirrored into its domain bundle (`engineering/skills/`, `finance/skills/`), with\na cs-* agent, two `/cs-*` commands, stdlib scripts and three cited references; all three SKILL.md\nfiles pass the write-a-skill checklist. Evaluated with skill-creator (with-skill vs no-skill, one\nrealistic prompt each): 21/21 vs 17/21 assertions. The baseline's misses are why the skills exist:\nit called `bypassPermissions` in a project file \"YOLO mode for every engineer\" and `mcp__*` in\nallow \"all tools\", both of which Claude Code ignores, and it used a \"typical\" flux threshold\nwithout asking for the entity's policy.\n\n- **The evals changed the scripts, not just the scores.** Four fixes came from reading the runs:\n  the MCP inventory now scans `args` and `url` for credentials (a `postgresql://user:pass@`\n  string in `args` slipped past it); the reconciliation matcher names a carried-in\n  opening-balance difference before guessing transposition; the flux analyzer takes `--reviewer`\n  and blocks lines the reviewer owns; the flake detector warns when every failure lands in late\n  trials, the signature of state shared between trials.\n- **Rules these encode:** never compare single trials and never quarantine a critical case\n  (agent-regression-evals); policy that must hold for everyone goes in managed settings, not the\n  repo file (team-rollout); a reconciliation is a proof, a signature is not evidence of review\n  (PCAOB SAPA 11), and materiality thresholds are the entity's policy (month-end-close).\n- **Counters:** skills 392 → 398; tools 746 → 766; refs 859 → 877; agents 120 → 123;\n  commands 151 → 157; plugins 101 → 104 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/deep-learning-book (companion, not compilation):**\n\nNew `engineering/deep-learning-book/` plugin: a study companion for *Deep Learning* by\nGoodfellow, Bengio & Courville (MIT Press, 2016), free to read at deeplearningbook.org.\nRequested as \"convert this book into a skill\"; built as a **companion** instead, and the\nreasoning is the reusable part.\n\n- **Why not `book-to-skill`.** That skill's rights gate refuses a `shareable` package without\n  `public-domain` / `open-license` / `internal-docs` / `author-permission` — none applies to an\n  MIT Press title whose own site states the HTML-only format exists as a friction against\n  copying under the authors' contract — and its `rights_and_provenance.md` lists publishing a\n  compiled skill of a copyrighted book to a public marketplace under **Do not**. Its hard rule 1\n  also forbids scraping a book from the web, so the pipeline could not have run against a URL.\n  **The rule this sets:** when a user asks to convert a copyrighted work into a *shareable*\n  skill, build a companion that indexes and updates the source, not a compilation that\n  reproduces it; compile only when the gate clears, and keep the output local when it does not.\n  Recorded in `skills/deep-learning-book/references/rights_and_use.md`.\n- **What it is.** The compiled-skill *shape* (master SKILL.md at ~2.0k tokens with a chapter\n  index and topic index, `chapters/ch01..ch20`, glossary, patterns, cheatsheet) filled with\n  original synthesis — no passages, figures, or per-paragraph paraphrase — each chapter file\n  linking to the official free chapter. Passes `book_to_skill`'s own `book_skill_validator.py`\n  clean and every file is inside `token_budget_estimator.py`'s caps.\n- **The differentiator is the delta layer.** A static compilation freezes a source at its\n  publication date; this one dates it. Every chapter carries \"What changed after 2016\", and\n  `references/book_to_2026_delta.md` gives five corrections with primary citations and per-claim\n  confidence levels: double descent qualifying Ch 5's U-curve, AdamW splitting weight decay from\n  L2 (Ch 7 treats them as interchangeable), transformers displacing Ch 10's recurrence (keep the\n  gradient analysis, drop the architecture advice), diffusion growing out of Ch 14's denoising\n  autoencoders and Ch 18's score matching, and self-supervised learning vindicating Ch 15 while\n  replacing every method it names. Two claims are marked contested rather than propagated (batch\n  norm's \"internal covariate shift\" mechanism; the strong lottery-ticket form) and two named as\n  folklore. The stated rule: **the conflict is almost always in the recommendation, not the\n  analysis.**\n- **4 stdlib tools, each with a real refusal.** `reading_path_planner.py` (goal → prerequisite\n  closure over the book's actual dependency graph, ordered, priced in weeks; exit 3 for a goal\n  the book does not cover, naming what does; exit 4 with forcing questions when unroutable),\n  `training_diagnostics.py` (Ch 11's rules in priority order, so a NaN is never reported as\n  overfitting; exit 4 rather than diagnosing with no instruments), `capacity_planner.py`\n  (regularization ladder in cost order, with \"shrink the model\" pushed **last** in the\n  overparameterized regime per double descent; exit 4 on a val-below-train split),\n  `model_arithmetic.py` (params/FLOPs/activation memory per example for conv, linear, MHA and\n  LSTM/GRU stacks; exit 5 naming the layer whose shapes do not connect).\n- 4 references citing 7-8 sources each, 3 assets, `cs-deep-learning-tutor` agent, `/cs-deep-learning`\n  + `/cs-dl-reading-path` + `/cs-dl-diagnose`. **Counters:** skills 386 → 387; tools 723 → 727;\n  refs 838 → 842; agents 116 → 117; commands 146 → 149; plugins 97 → 98 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — marketing/linkedin (organic LinkedIn presence, platform rules in code):**\n\nNew `marketing/linkedin/` plugin answering [discussion #934](https://github.com/alirezarezvani/claude-skills/discussions/934), which asked for a strategic assistant for growing a LinkedIn presence organically rather than a post generator. Six skills (orchestrator + profile + strategy + content + engagement + analytics), 17 stdlib-only tools, 15 references, 2 agents, 8 `/cs-*` commands.\n\n- **The design constraint is the differentiator.** No LinkedIn credentials, no API calls, no scraping, nothing auto-sent — automated posting/connecting/commenting are prohibited by LinkedIn's User Agreement §8.2, and a restricted account ends a compounding asset. `linkedin_policy_gate.py` runs before any drafting and refuses seven request classes (automation, scraping, engagement pods, bulk messaging, fake identity, fabricated proof, named third-party automation platforms), each carrying the policy anchor **and a compliant substitute** — the gate never just says no. Orchestrator is `context: fork` with a deterministic five-lane router (route 0 / ask 2 / no-signal 3) and cross-lane prerequisites.\n- **Refusals are real, not warnings.** Cadence under 90 min/week returns a comment-only plan rather than a schedule that dies in week five; a newsletter whose six-month cost exceeds the budget is refused before the promise is made; an experiment needing more posts than a quarter allows is reported infeasible rather than quietly re-sized; the pattern miner refuses to test anything below 10 posts and reports `NOTHING_SURVIVED` as a finding.\n- **Evidence discipline — two popular claims corrected rather than propagated** (the `andreessen` precedent). (1) \"A personalised note triples connection acceptance (~45% vs ~15%)\" is not supported by the largest samples, which show acceptance close to identical either way (~26.4%); what a note actually moves is the **post-accept reply rate** (~5.4% → ~9.4%) — which is why `outreach_message_builder.py` refuses an ask in a first-touch note. (2) The ~19% in-body external-link reach reduction has **never been confirmed by LinkedIn as a penalty** and has a plausible dwell-time explanation, so it is a warning, not a block. Every reference carries per-claim confidence levels (🟢 LinkedIn-official / 🟡 third-party study / 🔴 folklore, named as folklore).\n- **Accessibility is a blocking lint finding, not a footnote.** Unicode pseudo-bold (the output of \"bold text generators\") fails the linter: screen readers announce those characters as mathematical symbols and LinkedIn search does not index them as words. Engagement bait is also blocking, per the Professional Community Policies. `pattern_miner.py` adds multiple-comparisons accounting and mirrored-candidate de-duplication that no comparable tool implements.\n- All six SKILL.md files are a full **6/6 PASS** on the write-a-skill checklist (binding for post-v2.6.0 skills). Every tool supports `--help`/`--sample`/`--output json` with typed exit codes. **Counters:** skills 380 → 386; tools 706 → 723; refs 823 → 838; agents 114 → 116; commands 138 → 146; plugins 96 → 97 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.12.0) — engineering/spinning-up-deep-rl (the first book compiled by book-to-skill):**\n\nThe first knowledge-base plugin produced end-to-end by `engineering/book-to-skill`, from OpenAI's\n[Spinning Up in Deep RL](https://spinningup.openai.com/) (MIT, © 2018 OpenAI; primarily developed by\nJoshua Achiam). Source obtained by cloning `openai/spinningup` and compiling its `docs/` reStructuredText\ntree — 38 files, ~37k words, ~49K tokens — through the full pipeline: `extract_document.py --mode technical`\n→ analysis → 20 chapter files → glossary / patterns / cheatsheet → master `SKILL.md` → `book_skill_validator.py`\n→ `skill_plugin_emitter.py`. Validator passes clean **in `--strict` mode**; every file is inside budget\n(resident core 2,101 / 4,000 tokens; 20 chapters averaging ~1,256 tokens each, loaded on demand).\n\n- **Rights basis is `open-license`, not fair use.** The emitter's Step-11 gate refuses a shareable package\n  without one; MIT permits derivative distribution. Upstream's notice is reproduced in full in the plugin's\n  `LICENSE` alongside this package's own, and the README names the source, the author and the commit-era —\n  a sidecar JSON is not a license notice.\n- **Chapter structure follows the source's own `toctree`**, not a heading scan: user documentation (ch01-06),\n  Introduction to RL Parts 1-3 (ch07-09), resources — the researcher essay, key papers, exercises, benchmarks\n  (ch10-13), one chapter per algorithm in lineage order (ch14-19: VPG → TRPO → PPO, DDPG → TD3 → SAC), and the\n  logger/MPI/ExperimentGrid utilities (ch20).\n- **The cheatsheet carries what a glossary cannot**: the debug-turnaround threshold (under 5 minutes), the seed\n  minimums (3, ideally 10+), the benchmark network defaults that differ by algorithm family ((64,32)/tanh\n  on-policy vs (256,256)/relu off-policy), and Spinning Up's own **parity disclosure** — DDPG/TD3/SAC are\n  research-grade, VPG/TRPO/PPO are not, and the docs say to use OpenAI Baselines for those instead.\n- **One emitter defect found and fixed in the same change.** `skill_plugin_emitter.py` was writing its `source`\n  provenance block into `plugin.json`, which this repo's own `scripts/check_plugin_json.py` hard-fails\n  (issue #954 — Claude Code rejects the whole manifest on any unrecognized key). Its inline comment claimed\n  `source`/`attribution` were \"approved extension fields,\" which had been true and no longer was. The manifest\n  builder now emits spec fields only and a new `_authoring_notes()` writes `.claude-plugin/authoring-notes.json`.\n  Every future `book-to-skill` package gets a manifest that passes CI; the one emitted here was the first to\n  catch it.\n- **write-a-skill checklist: 4/6, and the two remaining are structural, not defects.** A compiled\n  knowledge base is not a hand-authored instruction skill. (2) \"SKILL.md under 100 lines\" conflicts\n  with the format's mandatory 20-row Chapter Index plus Topic Index; the binding budget here is\n  `book_skill_validator.py`'s 4,000-token cap, and the file sits at 2,101 — trimming to 100 lines\n  would delete exactly the navigation that `budget.over_cap` exists to protect. (3) \"no\n  time-sensitive info\" fires on \"January 2020\", which is a **provenance pin on a frozen source**\n  (Spinning Up's last update), not a staleness claim — removing it would make the skill less honest\n  about what it covers. (5) was a real gap and is fixed: the resident core now carries a worked\n  invocation block.\n- **No new Python tools** — a compiled knowledge base ships notes, not scripts, so the tools and references\n  counters are unchanged. **Counters:** skills 387 → 388; agents 117 → 118; commands 149 → 150; plugins\n  98 → 99, on top of `deep-learning-book` which merged into `dev` first (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/skill-doctor (grade the agent setup from real sessions):**\n\nRebuild of [warpdotdev/common-skills](https://github.com/warpdotdev/common-skills)' `skill-doctor` (MIT, © Denver Technologies, Inc., pinned at `f3b58c81`) as a full plugin. Harvests the last N days of local Claude Code / Codex sessions scoped to one repo, has the agent judge each condensed transcript against two verbatim-preserved rubrics (efficiency, code quality — labels only, closed tables), measures which installed skills actually fired, and proposes only the skill edits the evidence justifies — one local, self-contained HTML report; nothing is ever uploaded.\n\n- **22 numbered deviations from upstream** — `engineering/skill-doctor/README.md`'s list is authoritative; `authoring-notes.json` summarizes it. Headline additions: **`score_aggregator.py`, a deterministic gate with no upstream counterpart** — upstream let the scoring LLM average its own scores and assemble `report.json`; here labels map to scores via embedded tables mirroring the rubrics, scores for unsampled sessions are rejected as fabrications, reasons are length-checked, and a suggestion that cites no scored session id (or carries no diff) fails at exit 4. **Collector hardening:** always-on 12-pattern secret redaction before any transcript touches disk (no off switch; per-label counts land in the inventory and report), `chmod 0700/0600` artifacts, plugin-layout skill discovery (`*/skills/*/SKILL.md`), slash-command usage detection mined from `<command-name>` markers before the injection filter drops them. **Renderer replaced:** zero JavaScript (upstream embeds a 1,531-line prebuilt diff bundle + canvas share-image) — pure-CSS diff coloring, native `<details>` collapse, `prefers-color-scheme`, print-to-PDF; Warp branding and the `warp.dev/factories` CTA removed. **Dropped:** the Warp `warp.sqlite` source and its 392-line hand-rolled protobuf decoder (unauditable vendored binary-format code; Warp users should run upstream).\n- Preserved verbatim: both scoring rubrics (`scorers/`) and the skill-improvement filing bar (\"would a competent agent with the current instructions still fail this way?\"), now §1–§2 of `references/skill_edit_governance.md`. Zero suggestions clearing the bar is a valid, reportable success; proposed edits stay staged under the run's scratch dir until an explicit per-skill yes, and proposals for this repo's skills must pass write-a-skill's 6-item checklist.\n- 3 stdlib tools (all `--help`/`--sample`/`--output json`, typed exit codes; the pipeline smoke-tests end-to-end from `--sample` fixtures including a planted fake secret), 3 references citing 7 sources each, 3 handoff-shape assets, `cs-skill-doctor` agent, `/cs-skill-doctor` command. SKILL.md is a full 6/6 PASS on the write-a-skill checklist. Distinct from `skillopt-sleep` (automated nightly loop; this is one interactive graded pass), `write-a-skill` (authors from expertise; this improves from evidence), and self-eval (grades the current session; this grades a window). **Counters** (this branch merged `dev` after `agent-memory` landed, so these deltas sit on top of it): skills 378 → 379; tools 703 → 706; refs 820 → 823; agents 110 → 111; commands 130 → 131; plugins 95 → 96 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/book-to-skill (document → knowledge-base skill → plugin):**\n\nDerived from [virgiliojr94/book-to-skill](https://github.com/virgiliojr94/book-to-skill) (MIT). Compiles a book, documentation folder, or spec collection (PDF, EPUB, DOCX, HTML, Markdown, RST, AsciiDoc, RTF, MOBI/AZW) into an agent skill: a resident master `SKILL.md` (core frameworks + chapter index + topic index, capped at 4k tokens) plus on-demand `chapters/chNN-*.md`, `glossary.md`, `patterns.md`, and a decision `cheatsheet.md`. The agent reads the core, then one chapter — never the whole source again.\n\n- **Vendored close to verbatim:** the extraction library (`scripts/book_to_skill/` — config, exceptions, sanitize, dependencies, utils + 7 per-format parsers) keeps upstream's format chains, chapter detection across Latin/Roman/Chinese/Thai/Korean heading styles, invisible-Unicode (Trojan Source) sanitization and DOCX entity-expansion guard.\n- **26 numbered deviations from upstream** — the list in `engineering/book-to-skill/README.md` is authoritative; the plugin's `authoring-notes.json` `attribution.derivation_note` summarizes it. Highlights: (5) `--install-missing` now defaults to `report` — it prints the pip command and uses the stdlib fallback instead of upstream's TTY prompt that runs `pip install` into the caller's environment; (6) a **rights gate** — `skill_plugin_emitter.py --distribution shareable` refuses without `--rights` from `public-domain|open-license|internal-docs|author-permission`, with `fair-use` deliberately excluded (a defence, not a licence); (10) the two upstream validators merged into one four-family gate, adding **budget** and **index** families — dead chapter links, unindexed chapter files and dangling topic refs are the failure that silently breaks navigation while the skill still looks complete, and upstream had no check for it; (11) folded YAML scalars now parse, so a wrapped description no longer under-reports its length past the 1024-char cap; (12) `discovery_tax.py` → `token_budget_estimator.py` with the optional `tiktoken` path dropped, a post-flight budget audit added, and an explicit **worth-converting verdict** that says \"just read it\" when the source is under ~3× the compiled skill.\n- **Repo-native addition with no upstream counterpart — Step 11 / `/cs-book-to-plugin`:** upstream stops at a bare folder in `~/.claude/skills/`, which this library cannot route to. `skill_plugin_emitter.py` wraps a compiled skill as a full plugin package (manifest + `cs-<slug>` agent + `/cs-<slug>` command + README) and prints the marketplace entry; it never edits `marketplace.json` itself, and refuses to wrap a skill carrying validation errors.\n- **Cross-linked into `engineering/write-a-skill`** (\"author first, compile second\" — that skill authors from expertise in your head, this one compiles from a document on disk).\n- 4 stdlib-only tools (all `--help` / `--sample` / `--output json`), 5 references citing 7–8 sources each, 3 assets, `cs-book-to-skill` agent, 2 commands. **Counters:** skills 362 → 363; tools 644 → 663; refs 741 → 746; agents 102 → 103; commands 116 → 118; plugins 88 → 89 (derived via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/memory-engineering (engineer the forgetting, not the remembering):**\n\nNew `engineering/memory-engineering/` plugin. Fills a real gap: the repo had no\nskill for designing, pricing, or auditing an **agent memory system** (nearest\nneighbours `llm-wiki`, `skillopt-sleep`, `agent-harness` all bound something\nelse — a vault, a loop, a task plan). Framing synthesized from *\"How to be a\nMemory Engineer, from the perspective of Stanford, Microsoft, Anthropic and\nNvidia\"* by [@N01ennn](https://x.com/N01ennn/status/2083971749079581120), with\nevery quantitative claim re-cited to the primary source.\n\n- **4 stdlib scripts, one per lens.** `memory_cost_profiler.py` (construction vs\n  query split, **cost per correct answer**, amortization, co-location warning →\n  WRITE-PATH-DOMINANT / UNDER-AMORTIZED / NEEDS-SCHEDULING-FIX);\n  `memory_architecture_picker.py` (scores the paper's four paradigm families,\n  disqualifies on hard constraints, **names the cost the choice makes you pay**,\n  and exits 2 refusing to pick when the top two are within 0.06 — printing the\n  tie-breaking question instead); `memory_density_auditor.py` (classifies every\n  record **FACT / SKILL / LOG / PROSE**, near-duplicates via word-shingle\n  Jaccard, staleness + volatile-wording flags, knowledge density per 1k tokens;\n  runs on a real `--dir` **or** `--jsonl`); `forgetting_policy_linter.py` — **the\n  gate**: 8 checks with **F1** (explicit forgetting rule) and **F4**\n  (contradictions surfaced, never auto-merged) blocking at exit 4.\n- **Evidence discipline — two of the source article's paraphrases are corrected\n  in the references rather than propagated.** (1) The 47× energy figure is the\n  *spread across ten evaluated systems* (BM25 at 4,145 J/correct answer vs\n  A-Mem/MIRIX at 115–197 kJ, a \"28–47× premium\"), **not** \"two systems with\n  identical accuracy.\" (2) The 97% first-pass-error reduction is **Rakuten's\n  named vendor-published customer testimonial** (Yusuke Kaji, at 27% lower cost\n  / 34% lower latency), not a controlled study or a general property of the\n  approach. Every reference carries per-claim confidence levels, per the\n  `andreessen` precedent.\n- **Two classifier defects found and fixed during the build**, both of which\n  would have produced garbage on any real repo: markdown headings *inside*\n  fenced code blocks were splitting records (fixed by masking fences before\n  heading detection — dropped 258 phantom records to 107 on a real directory),\n  and short fragments trivially matched at 1.00 Jaccard (fixed with a\n  20-word floor for duplicate candidacy, eliminating 41 false-positive\n  \"duplicates\"). A third fix added the **PROSE** class: an earlier version\n  labeled every signal-less block LOG, firing LOG_HEAVY at 74% on a prose\n  documentation folder.\n- 4 references citing 7 sources each (arXiv:2606.06448 Stanford characterization;\n  MSR PlugMem; arXiv:2604.09852 MEMENTO + OpenMementos; Anthropic managed-agents\n  memory), 3 assets (seven-question forcing worksheet, combined example spec\n  consumed by all three spec-taking scripts, fillable F1–F8 policy template),\n  `cs-memory-engineer` agent, `/cs-memory-engineering` + `/cs-forgetting-audit`.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist (binding for\n  post-v2.6.0 skills). **Counters** (this branch merged `dev` after\n  `book-to-skill` landed, so these deltas sit on top of it): skills 363 → 364;\n  tools 663 → 667; refs 746 → 750; agents 103 → 104; commands 118 → 120;\n  plugins 89 → 90 (verified via `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.2) — engineering/agent-memory (promotion is earned, not asserted):**\n\nNew `engineering/agent-memory/` plugin. Concept derived from\n[TencentCloud/TencentDB-Agent-Memory](https://github.com/TencentCloud/TencentDB-Agent-Memory)\n(MIT) — **no upstream code included**. A four-tier ladder over Claude Code's own\nhooks: **L0** raw transcripts (never injected) → **L1** candidate atoms\n(gitignored, recalled on lexical relevance per prompt) → **L2** project context\n(committed after adopt, loaded every session start) → **L3** stable persona\n(always loaded). Tiers are distinguished by *injection policy*, not storage\nformat.\n\n- **Three upstream choices deliberately rejected**, each for a repo rule rather\n  than taste: the managed **database** (self-contained-package rule → one\n  append-oriented JSONL per project, capped at 500 atoms); a **proxy layer**\n  between agent and model (Claude Code already exposes the three interception\n  points — adding a proxy to obtain hooks the platform provides buys nothing and\n  adds a failure mode on the critical path); **LLM-based extraction** (the\n  no-LLM-in-scripts anti-pattern, and a model call cannot run in an async\n  teardown hook on a latency budget, nor reproduce its output from the\n  transcript, which would break \"cite, don't invent\").\n- **The gates are the design.** L1→L2 needs ≥3 distinct sessions spanning ≥2\n  distinct calendar days (`stated` = 2 sessions, day rule *still applies*;\n  `verified` = 1 observation and is the only day-exempt path); L2→L3 needs ≥2\n  distinct projects + 30 days. Thresholds are tuned toward refusing because the\n  error costs are asymmetric: under-promotion is self-healing (the user restates\n  it, which is itself an observation), over-promotion silently steers every\n  future session.\n- **Two gates refuse rather than guess.** `redacted: true` blocks promotion on\n  *any* volume of evidence — a **durability-independent barrier**, since a\n  secret restated over five sessions passes every recurrence gate; the flag\n  firing means the text was altered, and a lexical filter finding one secret is\n  not proof it found all of them, while L2/L3 are committed to git. An open\n  contradiction freezes both claims, found by **reverse join** (the newer atom\n  carries no flag) rather than a mirrored field.\n- **Three hooks, all fail-open.** `SessionStart` injects L2+L3 and marks\n  L2↔L3 collisions the project-scoped detector structurally cannot see;\n  `UserPromptSubmit` recalls on a **100 ms internal budget** against a monotonic\n  clock (the 1 s hook `timeout` is a wedged-process backstop, not the budget);\n  `SessionEnd` is async and captures → redacts → merges → detects → stages.\n  Measured: spawn+recall p50 ≈ 29 ms / p95 ≈ 31 ms, scoring itself 2–3 ms over\n  500 atoms — **interpreter cold start is the entire cost**, which is why the\n  in-script loop is not worth optimizing further.\n- **Nothing reaches a `CLAUDE.md` without a human.** Promotions land in\n  `.memory/staged/`; `/cs-memory adopt` walks them one at a time and backs both\n  files up first. `cs-memory-curator` refuses to adopt a redacted claim, an\n  unresolvable citation, or to resolve a contradiction itself.\n- 5 stdlib scripts + 3 hooks (`memory_core.py` is a deviation from `DESIGN.md`\n  §10's four-script tree — the **`README.md` deviations list is authoritative**,\n  and §10.1's stale `+6` tool estimate is corrected to `+8` there and in\n  `DESIGN.md`), 3 references citing 6–7 sources each with per-claim confidence\n  levels, a 69-check example validator, and `DESIGN.md` — ~1,400 lines, 44\n  review rounds, open decisions ranked by what they gate, including the one that\n  permits deleting the folder if rule-based recall proves too low.\n- **SKILL.md is a full 6/6 PASS** on the write-a-skill checklist. **Counters:**\n  skills 377 → 378; tools 695 → 703 (+8: 5 scripts + 3 hooks); refs 817 → 820;\n  agents 109 → 110; commands 129 → 130; plugins 94 → 95 (verified via\n  `scripts/derive_counters.py --check`).\n\n---\n\n**Unreleased (post-v2.11.1) — productivity/fable-goal (ramble → autonomous /goal prompt):**\n\nImproved port of `duncan-buildroom/freeskills` `fable-goal` (informal \"free to use and modify\" grant — quoted, not relicensed; see the `attribution` block). Converts a rambling description of a desired outcome into one polished, copy-paste /goal prompt for a fresh autonomous session — the prompt is the deliverable, never the build. Adds over upstream: wrong-tool check, observable-done principle, six-slot extraction (deliverable/quantity/stakes/tools/quality/destination), per-medium verification defaults, six-point pre-delivery self-check, anti-pattern list + failure-mode catalog reference, second worked example in a non-web medium. Ships `goal_prompt_self_check.py` (stdlib runner for the mechanically checkable self-check subset — word count 150–350, goal line, autonomy directive, verification/freedom/destination language; exit 0/1, `--sample`, `--output json`), `/cs-fable-goal` command. Intentionally no `agents/`/`assets/` (single reasoning pass; see plugin README design notes). SKILL.md is a full PASS on the write-a-skill 6-item checklist. Counters: skills 357 → 358 (this PR also trues up pre-existing engineering-row drift 355 → 357); tools 602 → 603; refs 731 → 732; commands 109 → 110; plugins 83 → 84.\n\n---\n\n**Version:** v2.11.1 (pm/product agent-harness domains — deep audit + orchestrated loops for product-team & project-management)\n\n**v2.11.1 highlights — both PM/product routers become agent harnesses:**\n\nExtends the v2.11.0 agent-harness layer to the two people-process domains. Public audit record at `audit/pm-product-agentic-2026-07/` (AR-rubric scores for all 26 skills, research-backed improvement fields, executable verification criteria).\n\n- **project-management → delivery loop:** `pm-skills` rebuilt as a `context: fork` orchestrator with 3 stdlib tools — `pm_goal_router.py`\n\n<!-- [TRUNCATED AT 50KB] -->\n\n<!-- File: commercial/CLAUDE.md (Tokens: ~952 | Category: claude-rule) -->\n# Commercial — Domain Guide\n\nThis file provides domain-specific guidance for skills in `commercial/`.\n\n## Purpose\n\nThe Commercial domain ships skills that help **deal-desk operators, pricing teams, partner managers, RFP responders, and commercial forecasters** make per-deal and packaging decisions. This is **not strategy** (`c-level-advisor/cro-advisor`), **not sales execution** (`business-growth/sales-engineer`), and **not financial close** (`finance/financial-analysis`).\n\n## Skills (v2.8.0 complete)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `commercial-skills` | Domain orchestrator — routes to 7 sub-skills | YES |\n| `pricing-strategist` | Pricing model picker + Van Westendorp WTP + packaging | NO |\n| `deal-desk` | Per-deal scorer + discount approval routing + redline | NO |\n| `partnerships-architect` | 5-tier classifier + joint GTM + revshare modeler | NO |\n| `channel-economics` | Cost-to-serve + ROI + channel mix optimizer | NO |\n| `commercial-policy` | Data-backed discount matrix + exception flow + policy linter | NO |\n| `rfp-responder` | Shipley-method structured RFP/RFI/RFQ response | YES |\n| `commercial-forecaster` | 4Q-weighted bookings + cohort NRR/GRR + funnel-confidence | NO |\n\n## Hard rules (domain-specific)\n\n1. **Pricing outputs: model + range, never a specific number.** The human picks the number.\n2. **Deal outputs: score + named human approver. Never auto-approve.** Even at 0% discount.\n3. **Forecast outputs: surface the conversion assumption explicitly.** Pipeline math without disclosed assumptions is theatre.\n4. **RFP responses: never invent claims for GAP requirements.** Surface the gap; leadership decides bid/no-bid.\n5. **Partnership tiers: insist on independent-demand evidence for STRATEGIC.** Forrester: channel-led deals from your own pipeline cost more than direct.\n6. **Channel ROI requires retention differential.** CAC alone is meaningless without channel-level retention.\n7. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n8. **Industry tuning** via `--profile {saas,api,enterprise-software,marketplace,services,hardware}` on every scoring tool.\n9. **Matt Pocock grill discipline** — `/cs-grill-commercial` interrogates plan against SaaS pricing canon before any sub-skill runs.\n\n## Build pattern\n\nPath-B 11-file contract per skill. SKILL.md includes a \"Forcing-question library\" section that grills the user with cited canon (Skok, Tunguz, Bessemer, Ramanujam, ProfitWell, Winning by Design, Shipley, APMP).\n\n## Agent + command pattern\n\n- `cs-commercial-orchestrator` — margin-protective Commercial lead. Voice: \"What's the margin at full discount, AND what does next quarter's pipeline look like at the same terms?\"\n- `/cs-commercial <inquiry>` — top-level router\n- `/cs-grill-commercial <plan>` — Matt-style grilling first\n- `/cs-pricing-strategy`, `/cs-deal-review`, `/cs-partner-tier`, `/cs-channel-econ`, `/cs-commercial-policy`, `/cs-rfp-respond`, `/cs-commercial-forecast` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `business-growth/contract-and-proposal-writer` (prose authoring) — Commercial is **decision logic + structured response**\n- ❌ Skills that overlap `c-level-advisor/cro-advisor` — that's strategic CRO judgment\n- ❌ Skills that recommend a specific price — recommend model + range\n- ❌ Skills that auto-approve deals — score + route to named human\n- ❌ Forecasting tools that hide conversion assumptions\n- ❌ RFP responder that invents claims — surface GAPs, leadership decides\n- ❌ Partnership classifier that grants STRATEGIC tier without independent-demand evidence\n\n## References\n\n- Master plan: `documentation/implementation/bizops-commercial-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Strategic complement: `c-level-advisor/cro-advisor`\n- Sales execution complement: `business-growth/sales-engineer`\n\n<!-- File: engineering-team/CLAUDE.md (Tokens: ~2182 | Category: claude-rule) -->\n# Engineering Team Skills - Claude Code Guidance\n\nThis guide covers the 32 production-ready engineering skills and their Python automation tools.\n\n## Engineering Skills Overview\n\n**Core Engineering (16 skills):**\n- senior-architect, senior-frontend, senior-backend, senior-fullstack\n- senior-qa, senior-devops, senior-secops\n- code-reviewer, senior-security\n- aws-solution-architect, ms365-tenant-manager, google-workspace-cli, tdd-guide, tech-stack-evaluator, epic-design\n- **a11y-audit** — WCAG 2.2 accessibility audit and fix (a11y_scanner.py, contrast_checker.py)\n- **azure-cloud-architect** — Azure infrastructure design, ARM/Bicep templates, landing zones\n- **gcp-cloud-architect** — GCP infrastructure design, Terraform modules, cloud-native patterns\n- **security-pen-testing** — Penetration testing methodology, vulnerability assessment, exploit analysis\n- **snowflake-development** — Snowflake data warehouse development, SQL optimization, data pipeline patterns\n\n**Security (5 skills):**\n- **adversarial-reviewer** — Adversarial code review with 3 hostile personas (Saboteur, New Hire, Security Auditor)\n- **threat-detection** — Hypothesis-driven threat hunting, IOC sweep generation, z-score anomaly detection\n- **incident-response** — SEV1-SEV4 triage, 14-type incident taxonomy, NIST SP 800-61 forensics\n- **cloud-security** — IAM privilege escalation paths, S3 public access checks, security group detection\n- **red-team** — MITRE ATT&CK kill-chain planning, effort scoring, choke point identification\n- **ai-security** — ATLAS-mapped prompt injection detection, model inversion & data poisoning risk scoring\n\n**AI/ML/Data (5 skills):**\n- senior-data-scientist, senior-data-engineer, senior-ml-engineer\n- senior-prompt-engineer, senior-computer-vision\n\n**Total Tools:** 39+ Python automation tools\n\n## Core Engineering Tools\n\n### 1. Project Scaffolder (`senior-fullstack/scripts/project_scaffolder.py`)\n\n**Purpose:** Production-ready project scaffolding for modern stacks\n\n**Supported Stacks:**\n- Next.js + GraphQL + PostgreSQL\n- React + REST + MongoDB\n- Vue + GraphQL + MySQL\n- Express + TypeScript + PostgreSQL\n\n**Features:**\n- Docker Compose configuration\n- CI/CD pipeline (GitHub Actions)\n- Testing infrastructure (Jest, Cypress)\n- TypeScript + ESLint + Prettier\n- Database migrations\n\n**Usage:**\n```bash\n# Create new project\npython senior-fullstack/scripts/project_scaffolder.py my-project --type nextjs-graphql\n\n# Start services\ncd my-project && docker-compose up -d\n```\n\n### 2. Code Quality Analyzer (`senior-fullstack/scripts/code_quality_analyzer.py`)\n\n**Purpose:** Comprehensive code quality analysis and metrics\n\n**Features:**\n- Security vulnerability scanning\n- Performance issue detection\n- Test coverage assessment\n- Documentation quality\n- Dependency analysis\n- Actionable recommendations\n\n**Usage:**\n```bash\n# Analyze project\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project\n\n# JSON output\npython senior-fullstack/scripts/code_quality_analyzer.py /path/to/project --json\n```\n\n**Output:**\n```\nCode Quality Report:\n- Overall Score: 85/100\n- Security: 90/100 (2 medium issues)\n- Performance: 80/100 (3 optimization opportunities)\n- Test Coverage: 75% (target: 80%)\n- Documentation: 88/100\n\nRecommendations:\n1. Update lodash to 4.17.21 (CVE-2020-8203)\n2. Optimize database queries in UserService\n3. Add integration tests for payment flow\n```\n\n### 3. Fullstack Scaffolder (`senior-fullstack/scripts/fullstack_scaffolder.py`)\n\n**Purpose:** Rapid fullstack application generation\n\n**Usage:**\n```bash\npython senior-fullstack/scripts/fullstack_scaffolder.py my-app --stack nextjs-graphql\n```\n\n## AI/ML/Data Tools\n\n### Data Science Tools\n\n**Experiment Designer** (`senior-data-scientist/scripts/experiment_designer.py`)\n- A/B test design\n- Statistical power analysis\n- Sample size calculation\n\n**Feature Engineering Pipeline** (`senior-data-scientist/scripts/feature_engineering_pipeline.py`)\n- Automated feature generation\n- Correlation analysis\n- Feature selection\n\n**Statistical Analyzer** (`senior-data-scientist/scripts/statistical_analyzer.py`)\n- Hypothesis testing\n- Causal inference\n- Regression analysis\n\n### Data Engineering Tools\n\n**Pipeline Orchestrator** (`senior-data-engineer/scripts/pipeline_orchestrator.py`)\n- Airflow DAG generation\n- Spark job templates\n- Data quality checks\n\n**Data Quality Validator** (`senior-data-engineer/scripts/data_quality_validator.py`)\n- Schema validation\n- Null check enforcement\n- Anomaly detection\n\n**ETL Generator** (`senior-data-engineer/scripts/etl_generator.py`)\n- Extract-Transform-Load workflows\n- CDC (Change Data Capture) patterns\n- Incremental loading\n\n### ML Engineering Tools\n\n**Model Deployment Pipeline** (`senior-ml-engineer/scripts/model_deployment_pipeline.py`)\n- Containerized model serving\n- REST API generation\n- Load balancing config\n\n**MLOps Setup Tool** (`senior-ml-engineer/scripts/mlops_setup_tool.py`)\n- MLflow configuration\n- Model versioning\n- Drift monitoring\n\n**LLM Integration Builder** (`senior-ml-engineer/scripts/llm_integration_builder.py`)\n- OpenAI API integration\n- Prompt templates\n- Response parsing\n\n### Prompt Engineering Tools\n\n**Prompt Optimizer** (`senior-prompt-engineer/scripts/prompt_optimizer.py`)\n- Prompt A/B testing\n- Token optimization\n- Few-shot example generation\n\n**RAG System Builder** (`senior-prompt-engineer/scripts/rag_system_builder.py`)\n- Vector database setup\n- Embedding generation\n- Retrieval strategies\n\n**Agent Orchestrator** (`senior-prompt-engineer/scripts/agent_orchestrator.py`)\n- Multi-agent workflows\n- Tool calling patterns\n- State management\n\n### Computer Vision Tools\n\n**Vision Model Trainer** (`senior-computer-vision/scripts/vision_model_trainer.py`)\n- Object detection (YOLO, Faster R-CNN)\n- Semantic segmentation\n- Transfer learning\n\n**Inference Optimizer** (`senior-computer-vision/scripts/inference_optimizer.py`)\n- Model quantization\n- TensorRT optimization\n- ONNX export\n\n**Video Processor** (`senior-computer-vision/scripts/video_processor.py`)\n- Frame extraction\n- Object tracking\n- Scene detection\n\n## Tech Stack Patterns\n\n### Frontend (React/Next.js)\n- TypeScript strict mode\n- Component-driven architecture\n- Atomic design patterns\n- State management (Zustand/Jotai)\n- Testing (Jest + React Testing Library)\n\n### Backend (Node.js/Express)\n- Clean architecture\n- Dependency injection\n- Repository pattern\n- Domain-driven design\n- Testing (Jest + Supertest)\n\n### Fullstack Integration\n- GraphQL for API layer\n- REST for external services\n- WebSocket for real-time\n- Redis for caching\n- PostgreSQL for persistence\n\n## Development Workflows\n\n### Workflow 1: New Project Setup\n\n```bash\n# 1. Scaffold project\npython senior-fullstack/scripts/project_scaffolder.py my-app --type nextjs-graphql\n\n# 2. Start services\ncd my-app && docker-compose up -d\n\n# 3. Run migrations\nnpm run migrate\n\n# 4. Start development\nnpm run dev\n```\n\n### Workflow 2: Code Quality Check\n\n```bash\n# 1. Analyze codebase\npython senior-fullstack/scripts/code_quality_analyzer.py ./\n\n# 2. Fix security issues\nnpm audit fix\n\n# 3. Run tests\nnpm test\n\n# 4. Build production\nnpm run build\n```\n\n### Workflow 3: ML Model Deployment\n\n```bash\n# 1. Setup MLOps infrastructure\npython senior-ml-engineer/scripts/mlops_setup_tool.py\n\n# 2. Deploy model\npython senior-ml-engineer/scripts/model_deployment_pipeline.py model.pkl\n\n# 3. Monitor performance\n# Check MLflow dashboard\n```\n\n## Quality Standards\n\n**All engineering tools must:**\n- Support modern tech stacks (Next.js, React, Vue, Express)\n- Generate production-ready code\n- Include testing infrastructure\n- Provide Docker configurations\n- Support CI/CD integration\n\n## Integration Patterns\n\n### GitHub Actions CI/CD\n\nAll scaffolders generate GitHub Actions workflows:\n```yaml\n.github/workflows/\n├── test.yml          # Run tests on PR\n├── build.yml         # Build and lint\n└── deploy.yml        # Deploy to production\n```\n\n### Docker Compose\n\nMulti-service development environment:\n```yaml\nservices:\n  - app (Next.js)\n  - api (GraphQL)\n  - db (PostgreSQL)\n  - redis (Cache)\n```\n\n## Additional Resources\n\n- **Quick Start:** `START_HERE.md`\n- **Team Structure:** `TEAM_STRUCTURE_GUIDE.md`\n- **Engineering Roadmap:** `engineering_skills_roadmap.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 32 engineering skills production-ready\n**Total Tools:** 39+ Python automation tools across core + AI/ML/Data + epic-design + a11y\n\n---\n\n## epic-design\n\nBuild cinematic 2.5D interactive websites with scroll storytelling, parallax depth, and premium animations. Includes asset inspection pipeline, 45+ techniques across 8 categories, and accessibility built-in.\n\n**Key features:**\n- 6-layer depth system with automatic parallax\n- 13 text animation techniques, 9 scroll patterns\n- Asset inspection with background judgment rules\n- Python tool for automated image analysis\n- WCAG 2.1 AA compliant (reduced-motion)\n\n**Use for:** Product launches, portfolio sites, SaaS marketing pages, event sites, Apple-style animations\n\n**Live demo:** [epic-design-showcase.vercel.app](https://epic-design-showcase.vercel.app/)\n\n<!-- File: finance/CLAUDE.md (Tokens: ~1091 | Category: claude-rule) -->\n# Finance Skills - Claude Code Guidance\n\nThis guide covers 5 production-ready finance skills and their Python automation tools.\n\n## Finance Skills Overview\n\n**Available Skills:**\n1. **financial-analyst/** - Financial statement analysis, ratio analysis, DCF valuation, budgeting, forecasting (4 Python tools)\n2. **saas-metrics-coach/** - SaaS financial health: ARR, MRR, churn, CAC, LTV, NRR, Quick Ratio, 12-month projections (3 Python tools)\n3. **business-investment-advisor/** - Investment thesis evaluation, ROI modeling, capital allocation guidance\n4. **passive-deal-screener/** - Screens private deals from the passive LP perspective: equity syndications, preferred equity, hard money / bridge funds, and private credit, pasted from any source. Stress-tests returns against public benchmarks plus an illiquidity premium, converts the fee stack to gross-to-net drag, and surfaces red flags, missing disclosures, and GP questions with bad-answer signals (2 Python tools: `fee_drag_calculator.py`, `benchmark_comparator.py`)\n5. **month-end-close/** - Runs the accounting close: close calendar on its critical path with owner and reviewer checks, reconciliation proof with aging and transposition hints, and a flux gate that refuses boilerplate explanations (3 Python tools: `close_calendar_planner.py`, `reconciliation_matcher.py`, `flux_analyzer.py`; standalone plugin with `/cs-month-end-close` and `/cs-flux-review`)\n\n**Total Tools:** 12 Python automation tools; 5 knowledge bases and 6 templates across skills 1-3, plus 5 reference files in passive-deal-screener\n\n**Commands:** 2 (`/financial-health`, `/saas-health`)\n\n## Python Automation Tools\n\n### 1. Ratio Calculator (`financial-analyst/scripts/ratio_calculator.py`)\n\n**Purpose:** Calculate and interpret financial ratios from statement data\n\n**Features:**\n- Profitability ratios (ROE, ROA, Gross/Operating/Net Margin)\n- Liquidity ratios (Current, Quick, Cash)\n- Leverage ratios (Debt-to-Equity, Interest Coverage, DSCR)\n- Efficiency ratios (Asset/Inventory/Receivables Turnover, DSO)\n- Valuation ratios (P/E, P/B, P/S, EV/EBITDA, PEG)\n- Built-in interpretation and benchmarking\n\n**Usage:**\n```bash\npython financial-analyst/scripts/ratio_calculator.py financial_data.json\npython financial-analyst/scripts/ratio_calculator.py financial_data.json --format json\n```\n\n### 2. DCF Valuation (`financial-analyst/scripts/dcf_valuation.py`)\n\n**Purpose:** Discounted Cash Flow enterprise and equity valuation\n\n**Features:**\n- Revenue and cash flow projections\n- WACC calculation (CAPM-based)\n- Terminal value (perpetuity growth and exit multiple methods)\n- Enterprise and equity value derivation\n- Two-way sensitivity analysis\n- No external dependencies (uses math/statistics)\n\n**Usage:**\n```bash\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json\npython financial-analyst/scripts/dcf_valuation.py valuation_data.json --format json\n```\n\n### 3. Budget Variance Analyzer (`financial-analyst/scripts/budget_variance_analyzer.py`)\n\n**Purpose:** Analyze actual vs budget vs prior year performance\n\n**Features:**\n- Variance calculation (actual vs budget, actual vs prior year)\n- Materiality threshold filtering\n- Favorable/unfavorable classification\n- Department and category breakdown\n\n**Usage:**\n```bash\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json\npython financial-analyst/scripts/budget_variance_analyzer.py budget_data.json --format json\n```\n\n### 4. Forecast Builder (`financial-analyst/scripts/forecast_builder.py`)\n\n**Purpose:** Driver-based revenue forecasting and cash flow projection\n\n**Features:**\n- Driver-based revenue forecast model\n- 13-week cash flow projection\n- Scenario modeling (base/bull/bear)\n- Trend analysis from historical data\n\n**Usage:**\n```bash\npython financial-analyst/scripts/forecast_builder.py forecast_data.json\npython financial-analyst/scripts/forecast_builder.py forecast_data.json --format json\n```\n\n## Quality Standards\n\n**All finance Python tools must:**\n- Use standard library only (math, statistics, json, argparse)\n- Support both JSON and human-readable output via `--format` flag\n- Provide clear error messages for invalid input\n- Return appropriate exit codes\n- Process files locally (no API calls)\n- Include argparse CLI with `--help` support\n\n## Related Skills\n\n- **C-Level:** Strategic financial decision-making -> `../c-level-advisor/`\n- **Business & Growth:** Revenue operations, sales metrics -> `../business-growth/`\n- **Product Team:** Budget allocation, RICE scoring -> `../product-team/`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 4 finance skills documented here (domain totals: `scripts/derive_counters.py`)\n**Total Tools:** 12 Python automation tools\n**Commands:** /financial-health, /saas-health\n\n<!-- File: markdown-html/CLAUDE.md (Tokens: ~1578 | Category: claude-rule) -->\n# Markdown → HTML — Domain Guide\n\nThis file provides domain-specific guidance for skills in `markdown-html/`.\n\n## Purpose\n\nThe markdown-html domain converts long markdown files (the actual artifacts produced inside a Claude project — specs, reports, RFCs, PR writeups, slide outlines) into world-class, single-file, lightly-interactive HTML. Inspired by Thariq Shihipar's argument (Medium, 2026): markdown collapses past ~100 lines because it lacks visual machinery for density and lateral navigation; HTML restores both.\n\nIt is **not** an interactive prompt-tuning playground (`/playground` plugin owns that lane), **not** a landing-page generator (`marketing/landing/`), **not** a session-handoff brief generator (`engineering/handoff/` + `productivity/handoff/`), and **not** a static-site generator (single-file artifacts, not site indices).\n\n## Skills (v2.10.3 — domain complete)\n\n| Skill | Purpose | `context: fork`? | Status |\n|---|---|---|---|\n| `markdown-html-orchestrator` | Domain orchestrator — classifies doctype, gates on threshold + onboarding, routes to converter | YES | ✓ live |\n| `design-system` | One-time onboarding wizard + WCAG-AA-validated brand palette (12 CSS custom properties) + shared config | NO | ✓ live |\n| `md-document` | Long-form converter: sticky TOC, collapsibles, search, code-copy, scrollspy | NO | ✓ live |\n| `md-review` | Code-review converter: 2-col diff + severity-tagged margin annotations + jump-nav | NO | ✓ live |\n| `md-slides` | Slide-deck converter: arrow-key nav + presenter mode + print-to-PDF | NO | ✓ live |\n\nAll three converters are shipped. Routing always targets the converter skill's scripts — never hand-render HTML inline.\n\n## Hard rules (domain-specific)\n\n1. **Refuses input < 100 lines.** Markdown still wins below the threshold (Shihipar). Every converter (and the orchestrator) prints the line count and a \"keep as markdown\" recommendation.\n2. **Refuses without design-system onboarding.** The orchestrator's `route_explainer.py` checks `config_loader.setup_completed()`. If false, refuse and surface onboarding (`python3 markdown-html/skills/design-system/scripts/onboard.py`).\n3. **WCAG AA enforced.** `brand_palette_validator.py` rejects color combinations whose body-text contrast falls below 4.5:1 on bg. Link contrast is iteratively walked to 4.5:1 by adjusting luminance.\n4. **Single-file HTML output.** All CSS and JS inline. The only permitted external CDN entries are Google Fonts CSS and Prism.js. No bundler, no build step, no JS framework runtimes (vanilla JS + IntersectionObserver only).\n5. **Never silently chain converters.** \"Convert this markdown AND make slides from it AND a code review\" is three operations. Pick one, finish, ask before chaining.\n6. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n7. **Customization in use, not decoration.** Every converter MUST render differently when the user changes `design_style`, `brand.primary`, `code_theme`, or `toc.behavior`. If a token doesn't change behavior, it doesn't belong in the schema.\n8. **Onboarding-first.** The orchestrator surfaces onboarding the moment it detects a missing `setup_completed_at`. Don't render with placeholder defaults silently.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scripts + 3 references (each citing 5-7 sources) + (optional) 1 asset template. The orchestrator skill ships `context: fork` in its frontmatter. The `design-system` skill is the shared brand owner — every converter imports its `config_loader.py` via `sys.path.insert(0, .../design-system/scripts)`.\n\nEach SKILL.md ships a \"Forcing-question library\" section (cited-canon grilling, one question at a time) — same discipline as `research-ops`, `commercial`, and `business-operations`.\n\n## Agent + command pattern\n\n- `cs-markdown-html-orchestrator` — density-first markdown-to-HTML converter. Voice: \"What decision does this HTML drive — is the reader skimming, deciding, or presenting?\"\n- `/cs-markdown-html <path>.md` — top-level router (classifier + route + recommend)\n- `/cs-grill-markdown-html <path>.md` — Matt-Pocock-style 5-question grill before conversion\n- `/cs-design-system` — surface the onboarding wizard\n\nPer-sub-skill commands (all live):\n- `/cs-md-document`, `/cs-md-review`, `/cs-md-slides`\n\n## Anti-patterns (domain-level)\n\n- ❌ Converting markdown < 100 lines — markdown still wins. Refuse + cite Shihipar.\n- ❌ Skipping onboarding because \"the user wants it done now.\" Surface onboarding — it's 60 seconds.\n- ❌ Multi-file output (separate CSS / JS / image folders). Single file or nothing.\n- ❌ External JS framework runtimes (React, Vue, Svelte, Alpine). Vanilla JS + IntersectionObserver only.\n- ❌ Silently overwriting existing output files. `output_path_resolver.py` suffixes `-2`, `-3`, … by default.\n- ❌ Setting `MARKDOWN_HTML_NO_CONFIG=1` silently for an interactive user.\n- ❌ Decorative tokens — every token must change at least one converter's output.\n- ❌ Inventing brand colors when the user hasn't onboarded.\n- ❌ A skill that overlaps Anthropic's official Playground plugin (sliders/knobs/prompt-copy-back).\n- ❌ A skill that overlaps `marketing/landing/` (landing-page generation from scratch).\n\n## Customization pipeline\n\n1. User runs `python3 markdown-html/skills/design-system/scripts/onboard.py`.\n2. Wizard validates brand colors via `brand_palette_validator.py`, derives 12-token palette.\n3. Result written to `~/.config/markdown-html/design-system.json` (or `./.markdown-html/design-system.json` with `--scope project`).\n4. Every converter sub-skill imports `config_loader.py` and calls `load_config()` to read project > global > defaults.\n5. Each converter's renderer emits a single `<style>` block with `:root { --md-bg: ...; }` for all 12 tokens, then references those variables throughout the CSS.\n6. Result: change a single field via `--set brand.primary=#FF6B35` → next conversion re-renders with the new brand.\n\n## References\n\n- Spec: Thariq Shihipar — *Claude Code HTML output: Why Markdown Lost and How to Switch* (Medium, 2026)\n- Forking pattern source: `research-ops/skills/research-ops-skills/SKILL.md` (`context: fork`, two-signal routing)\n- Onboarding pattern source: `research-ops/skills/clinical-research/scripts/onboard.py` + `config_loader.py`\n- Brand palette math source: `marketing/landing/skills/landing/scripts/brand_palette_validator.py`\n- Matt Pocock grill-with-docs: `engineering/grill-with-docs`\n- Single-file HTML discipline source: `marketing/landing/skills/landing/SKILL.md`\n\n<!-- File: marketing-skill/CLAUDE.md (Tokens: ~431 | Category: claude-rule) -->\n# Marketing Skills — Agent Instructions\n\n## For All Agents (Claude Code, Codex CLI, OpenClaw)\n\nThis directory contains 44 marketing skills organized into 8 specialist pods (Content, SEO + AEO, CRO, Channels, Growth, Intelligence, Sales enablement, Marketing ops).\n\n### How to Use\n\n1. **Start with routing:** Read `marketing-ops/SKILL.md` — it has a routing matrix that maps user requests to the right skill.\n2. **Check context:** If `.claude/product-marketing-context.md` exists, read it first. It has brand voice, personas, and competitive landscape.\n3. **Load ONE skill:** Read only the specialist SKILL.md you need. Never bulk-load.\n\n### Skill Map\n\n- `marketing-context/` — Run first to capture brand context\n- `marketing-ops/` — Router (read this to know where to go)\n- `content-production/` — Write content (blog posts, articles, guides)\n- `content-strategy/` — Plan what content to create\n- `aeo/` — Answer Engine Optimization (E-E-A-T scoring, schema injection, citation tracking across LLMs)\n- `seo-audit/` — Traditional SEO audit\n- `page-cro/` — Conversion rate optimization\n- `pricing-strategy/` — Pricing and packaging\n- `content-humanizer/` — Fix AI-sounding content\n- `x-twitter-growth/` — X/Twitter audience growth, tweet composing, competitor analysis\n\n### Python Tools\n\n59 scripts, all stdlib-only. Run directly:\n```bash\npython3 <skill>/scripts/<tool>.py [args]\n```\nNo pip install needed. Scripts include embedded samples for demo mode (run with no args).\n\n### Anti-Patterns\n\n❌ Don't read all 44 SKILL.md files\n❌ Don't skip `.claude/product-marketing-context.md` if it exists\n❌ Don't use content-creator (deprecated → use content-production)\n❌ Don't install pip packages for Python tools\n\n<!-- File: product-team/CLAUDE.md (Tokens: ~2877 | Category: claude-rule) -->\n# Product Team Skills - Claude Code Guidance\n\nThis guide covers the 17 production-ready product management skills (13 bundled incl. the orchestrator + 4 standalone plugins) and their Python automation tools.\n\n## Orchestrator & Discovery Loop (product-skills)\n\n`skills/product-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a product goal deterministically across all 16 lanes (exit 0 route / 2 ask / 3 no signal)\npython3 skills/product-skills/scripts/product_goal_router.py --text \"help me prioritize features\"\n\n# Score the continuous-discovery cadence (Torres weekly habit; refuses on < 2 interviews)\npython3 skills/product-skills/scripts/discovery_cadence_tracker.py --input discovery_log.json\n\n# Lint the Opportunity Solution Tree (exit 2 blocks the tree from driving a roadmap)\npython3 skills/product-skills/scripts/ost_linter.py --input ost.json\n```\n\nCommands: `/cs-product` (router) · `/cs-grill-product` (canon-cited grilling) ·\n`/cs-product-loop` (the discovery loop). Agent: `cs-product-orchestrator`. Build-scale\ngoals compile through `engineering/agent-harness` with the `product-team.json` manifest.\nHard rules: no roadmap cites a tree that fails the linter; single-participant claims are\nanecdotes; AI features ship with eval specs (see\n`skills/product-skills/references/ai_product_evals.md`).\n\n## Product Skills Overview\n\n**Available Skills:**\n0. **product-skills/** - Domain orchestrator (`context: fork`) + continuous-discovery loop (3 tools: goal router, cadence tracker, OST linter)\n1. **product-manager-toolkit/** - RICE prioritization, customer interview analysis (2 tools)\n2. **agile-product-owner/** - User story generation, sprint planning (1 tool)\n3. **product-strategist/** - OKR cascade, strategic planning (1 tool)\n4. **ux-researcher-designer/** - Persona generation, user research (1 tool)\n5. **ui-design-system/** - Design token generation, component systems (1 tool)\n6. **competitive-teardown/** - Competitive matrix building, gap analysis (1 tool)\n7. **landing-page-generator/** - Landing page scaffolding (1 tool)\n8. **saas-scaffolder/** - SaaS project bootstrapping (1 tool)\n9. **product-analytics/** - KPI design, retention/cohort/funnel analysis (1 tool)\n10. **experiment-designer/** - Experiment design and sample size planning (1 tool)\n11. **product-discovery/** - Discovery frameworks and assumption mapping (1 tool)\n12. **roadmap-communicator/** - Roadmap communication and changelog generation (1 tool)\n13. **code-to-prd/** - Reverse-engineer any codebase into PRD (2 tools: codebase_analyzer, prd_scaffolder)\n14. **research-summarizer/** - Research synthesis and summarization (1 tool)\n15. **apple-hig-expert/** - Apple Human Interface Guidelines compliance and design (1 tool: hig_checker)\n16. **spec-to-repo/** - Convert a spec document into a scaffolded repository\n\n**Total Tools:** 22 Python automation tools\n\n**Agents:** 6 (cs-product-orchestrator, cs-product-manager, cs-agile-product-owner, cs-product-strategist, cs-ux-researcher, cs-product-analyst)\n\n**Slash Commands:** 11 (/cs-product, /cs-grill-product, /cs-product-loop, /rice, /okr, /persona, /user-story, /competitive-matrix, /prd, /sprint-plan, /code-to-prd)\n\n## Python Automation Tools\n\n### 1. RICE Prioritizer (`product-manager-toolkit/scripts/rice_prioritizer.py`)\n\n**Purpose:** RICE framework implementation for feature prioritization\n\n**Formula:** (Reach × Impact × Confidence) / Effort\n\n**Features:**\n- Portfolio analysis (quick wins vs big bets)\n- Quarterly roadmap generation\n- Capacity planning (story points or dev days)\n- CSV input/output for Jira/Linear integration\n- JSON export for dashboards\n\n**Usage:**\n```bash\n# Basic prioritization\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv\n\n# With capacity planning\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 20\n\n# JSON output\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --output json\n```\n\n**CSV Format:**\n```csv\nfeature,reach,impact,confidence,effort\nUser Dashboard,500,3,0.8,5\nAPI Rate Limiting,1000,2,0.9,3\nDark Mode,300,1,1.0,2\n```\n\n### 2. Customer Interview Analyzer (`product-manager-toolkit/scripts/customer_interview_analyzer.py`)\n\n**Purpose:** NLP-based interview transcript analysis\n\n**Features:**\n- Pain point extraction with severity scoring\n- Feature request identification\n- Sentiment analysis\n- Theme extraction\n- Jobs-to-be-done pattern recognition\n\n**Usage:**\n```bash\n# Analyze transcript\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt\n\n# JSON output\npython product-manager-toolkit/scripts/customer_interview_analyzer.py interview.txt json\n```\n\n### 3. User Story Generator (`agile-product-owner/scripts/user_story_generator.py`)\n\n**Purpose:** INVEST-compliant user story generation\n\n**Features:**\n- Sprint planning with capacity allocation\n- Epic breakdown into deliverable stories\n- Acceptance criteria generation\n- Story point estimation\n- Priority scoring\n\n**Usage:**\n```bash\n# Interactive mode\npython agile-product-owner/scripts/user_story_generator.py\n\n# Sprint planning (30 story points)\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### 4. OKR Cascade Generator (`product-strategist/scripts/okr_cascade_generator.py`)\n\n**Purpose:** Automated OKR hierarchy (company → product → team)\n\n**Features:**\n- Alignment scoring (vertical and horizontal)\n- Strategy templates (growth, retention, revenue, innovation)\n- Key result tracking\n- Progress visualization\n\n**Usage:**\n```bash\n# Growth strategy OKRs\npython product-strategist/scripts/okr_cascade_generator.py growth\n\n# Retention strategy\npython product-strategist/scripts/okr_cascade_generator.py retention\n```\n\n### 5. Persona Generator (`ux-researcher-designer/scripts/persona_generator.py`)\n\n**Purpose:** Data-driven persona creation from user research\n\n**Usage:**\n```bash\npython ux-researcher-designer/scripts/persona_generator.py\npython ux-researcher-designer/scripts/persona_generator.py --output json\n```\n\n### 6. Design Token Generator (`ui-design-system/scripts/design_token_generator.py`)\n\n**Purpose:** Complete design token system from brand color\n\n**Usage:**\n```bash\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern scss\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern json\n```\n\n### 7. Competitive Matrix Builder (`competitive-teardown/scripts/competitive_matrix_builder.py`)\n\n**Purpose:** Weighted competitive scoring with gap analysis\n\n**Usage:**\n```bash\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### 8. Landing Page Scaffolder (`landing-page-generator/scripts/landing_page_scaffolder.py`)\n\n**Purpose:** Generate production-ready landing pages as Next.js/React TSX components with Tailwind CSS (default) or plain HTML.\n\n**Features:**\n- TSX output (default): Next.js 14+ App Router components with Tailwind classes\n- 4 design styles: `dark-saas`, `clean-minimal`, `bold-startup`, `enterprise`\n- 7 section generators: nav, hero, features, testimonials, pricing, CTA, footer\n- Copy frameworks: PAS, AIDA, BAB\n\n**Usage:**\n```bash\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format html\n```\n\n### 9. Project Bootstrapper (`saas-scaffolder/scripts/project_bootstrapper.py`)\n\n**Purpose:** SaaS project scaffolding with auth, billing, and API setup\n\n**Usage:**\n```bash\npython saas-scaffolder/scripts/project_bootstrapper.py project_config.json\n```\n\n### 10. Metrics Calculator (`product-analytics/scripts/metrics_calculator.py`)\n\n**Purpose:** Product analytics — retention, cohort, and funnel analysis\n\n**Features:**\n- Retention curve analysis from event data\n- Funnel conversion tracking with stage-by-stage drop-off\n- Cohort grouping and comparison\n\n**Usage:**\n```bash\n# Retention analysis\npython product-analytics/scripts/metrics_calculator.py retention events.csv\n\n# Funnel analysis\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\n\n# KPI summary\npython product-analytics/scripts/metrics_calculator.py kpi metrics.csv --json\n```\n\n### 11. Sample Size Calculator (`experiment-designer/scripts/sample_size_calculator.py`)\n\n**Purpose:** Statistical sample size planning for A/B tests and experiments\n\n**Features:**\n- Minimum detectable effect (MDE) calculation\n- Absolute and relative effect size modes\n- Power analysis with configurable alpha/beta\n\n**Usage:**\n```bash\n# Absolute MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n\n# Relative MDE\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.15 --mde-type relative\n\n# Custom power/significance\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --alpha 0.01 --power 0.9\n```\n\n### 12. Assumption Mapper (`product-discovery/scripts/assumption_mapper.py`)\n\n**Purpose:** Map and prioritize product assumptions for discovery validation\n\n**Features:**\n- Risk × uncertainty scoring for prioritization\n- CSV input with structured assumption fields\n- Categorization by assumption type (desirability, viability, feasibility, usability)\n\n**Usage:**\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\npython product-discovery/scripts/assumption_mapper.py assumptions.csv --json\n```\n\n### 13. Changelog Generator (`roadmap-communicator/scripts/changelog_generator.py`)\n\n**Purpose:** Generate structured changelogs from git commit history\n\n**Note:** Requires `git` on PATH — must be run inside a git repository.\n\n**Usage:**\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to v2.0.0 --json\n```\n\n## Product Workflows\n\n### Workflow 1: Feature Prioritization to Sprint Execution\n\n```bash\npython product-manager-toolkit/scripts/rice_prioritizer.py features.csv --capacity 30\npython agile-product-owner/scripts/user_story_generator.py sprint 30\n```\n\n### Workflow 2: Strategy to Team-Level OKRs\n\n```bash\npython product-strategist/scripts/okr_cascade_generator.py growth --json > okrs.json\n```\n\n### Workflow 3: Research to Persona Artifacts\n\n```bash\npython ux-researcher-designer/scripts/persona_generator.py json > personas.json\n```\n\n### Workflow 4: Brand-Aligned Landing Page\n\n```bash\npython ../marketing-skill/content-production/scripts/brand_voice_analyzer.py website_copy.txt --format json > voice.json\npython ui-design-system/scripts/design_token_generator.py \"#0066CC\" modern css\npython landing-page-generator/scripts/landing_page_scaffolder.py config.json --format tsx\npython competitive-teardown/scripts/competitive_matrix_builder.py competitors.json\n```\n\n### Workflow 5: Product Analytics and Experimentation\n\n```bash\npython product-analytics/scripts/metrics_calculator.py retention events.csv\npython product-analytics/scripts/metrics_calculator.py funnel funnel.csv --stages visit,signup,activate,pay\npython experiment-designer/scripts/sample_size_calculator.py --baseline-rate 0.12 --mde 0.02 --mde-type absolute\n```\n\n### Workflow 6: Discovery and Opportunity Validation\n\n```bash\npython product-discovery/scripts/assumption_mapper.py assumptions.csv\n```\n\n### Workflow 7: Roadmap and Release Communication\n\n```bash\npython roadmap-communicator/scripts/changelog_generator.py --from v1.0.0 --to HEAD\n```\n\n## Quality Standards\n\n**All product Python tools must:**\n- CLI-first design for automation\n- Support both interactive and batch modes\n- JSON output for tool integration\n- Standard library only (minimal dependencies)\n- Actionable recommendations\n\n## Additional Resources\n\n- **Main Documentation:** `../CLAUDE.md`\n- **Marketing Brand Voice:** `../marketing-skill/content-production/scripts/brand_voice_analyzer.py`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 17/17 product skills production-ready (product-skills is now a fork-orchestrator + discovery loop)\n**Total Tools:** 22 Python automation tools\n**Agents:** 6 | **Commands:** 11\n\n<!-- File: project-management/CLAUDE.md (Tokens: ~2148 | Category: claude-rule) -->\n# Project Management Skills - Claude Code Guidance\n\nThis guide covers the 9 production-ready project management skills, 15 Python automation tools, and bundled Atlassian Remote MCP integration (`.mcp.json` ships with the plugin — OAuth handled by Claude Code, no env vars required).\n\n## PM Skills Overview\n\n**Available Skills:**\n1. **pm-skills/** - Domain orchestrator (`context: fork`) + agentic delivery loop (3 scripts: goal router, Jira snapshot bridge, delivery loop gate)\n2. **senior-pm/** - Portfolio health, risk analysis, resource planning (3 scripts)\n3. **scrum-master/** - Sprint health, velocity forecasting, retrospectives (3 scripts)\n4. **jira-expert/** - JQL building, workflow validation (2 scripts)\n5. **confluence-expert/** - Space structure, content auditing (2 scripts)\n6. **atlassian-admin/** - Permission auditing (1 script)\n7. **atlassian-templates/** - Template scaffolding (1 script)\n8. **meeting-analyzer/** - Meeting transcript behavioral analysis (prompt-driven; scripts are follow-up work)\n9. **team-communications/** - 3P updates, newsletters, FAQs (reference-driven)\n\n**Total Tools:** 15 Python automation tools\n**Agents:** 2 — cs-pm-orchestrator (routing + delivery loop) and cs-project-manager (legacy per-skill orchestration)\n**Slash Commands:** 6 (/cs-pm, /cs-grill-pm, /cs-pm-loop, /sprint-health, /project-health, /retro)\n**Key Feature:** Atlassian MCP Server integration for direct Jira/Confluence operations\n\n## Orchestrator & Delivery Loop (pm-skills)\n\n`skills/pm-skills/` is the domain's `context: fork` orchestrator and agent harness adapter:\n\n```bash\n# Route a PM goal deterministically (exit 0 route / 2 ask / 3 no signal)\npython3 skills/pm-skills/scripts/pm_goal_router.py --text \"our sprints feel off\"\n\n# Bridge a saved searchJiraIssuesUsingJql result into analyzable inputs\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to flow --forecast 20\npython3 skills/pm-skills/scripts/jira_snapshot_bridge.py --input snapshot.json --to sprint > sprint_data.json\npython3 skills/scrum-master/scripts/velocity_analyzer.py sprint_data.json\n\n# Gate agent-executed delivery loops (G1 human owner … G6 exhausted budget = escalation)\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode plan   # exit 2 = blocked\npython3 skills/pm-skills/scripts/delivery_loop_gate.py --plan plan.json --mode close  # exit 4 = refused\n```\n\nMulti-task goals compile through the repo-wide harness\n(`engineering/agent-harness` with the `project-management.json` manifest). Hard rules:\nagents contribute, humans own; forecasts are Monte Carlo ranges, never dates; exhausted\nbudgets escalate — never reported as success. The five reusable PM loops (sprint-flow,\nhealth, retro-action, RAID-hygiene, comms) are documented in\n`skills/pm-skills/references/pm_loop_playbook.md`.\n\n## Atlassian MCP Integration\n\n**Purpose:** Direct integration with Jira and Confluence via Model Context Protocol (MCP)\n\n**Canonical tool list:** [references/atlassian-mcp-tools.md](references/atlassian-mcp-tools.md) — the single source of truth for real tool names. Never invent tool names; if a capability isn't in that list (project creation, sprint management, field configuration, automation rules, space creation, …), it is NOT available via MCP — use the Atlassian web UI or REST API.\n\n**Capabilities (real tools, camelCase):**\n- Jira issues: `createJiraIssue`, `getJiraIssue`, `editJiraIssue`, `searchJiraIssuesUsingJql`, `transitionJiraIssue`, `addCommentToJiraIssue`, `createIssueLink`\n- Confluence pages: `createConfluencePage`, `getConfluencePage`, `updateConfluencePage`, `searchConfluenceUsingCql`, `getConfluencePageDescendants`\n- Discovery: `getAccessibleAtlassianResources` (get `cloudId` first), `getVisibleJiraProjects`, `getConfluenceSpaces`\n\n**Setup:** Bundled `.mcp.json` registers the `atlassian` SSE server; tools surface as `mcp__atlassian__<toolName>`.\n\n**Usage Pattern:**\n```\n# Jira: create an issue (call getAccessibleAtlassianResources first to obtain cloudId)\nmcp__atlassian__createJiraIssue (cloudId, projectKey=\"PROJ\", issueTypeName=\"Story\", summary=\"New feature\")\n\n# Confluence: create a page (body must be storage-format XHTML or ADF, not wiki markup)\nmcp__atlassian__createConfluencePage (cloudId, space, title=\"Sprint Retrospective\", body=<storage-format XHTML>)\n```\n\n**Not available via MCP** (use web UI/REST API): project creation, sprints, boards, filters, space creation, page deletion, labels, field/workflow/permission configuration, user provisioning, automation rules.\n\n## Skill-Specific Guidance\n\n### Senior PM (`senior-pm/`)\n\n**Focus:** Project planning, stakeholder management, risk mitigation\n\n**Key Workflows:**\n- Project charter creation\n- Stakeholder analysis and communication plans\n- Risk register maintenance\n- Status reporting and escalation\n\n### Scrum Master (`scrum-master/`)\n\n**Focus:** Agile ceremonies, team coaching, impediment removal\n\n**Key Workflows:**\n- Sprint planning facilitation\n- Daily standup coordination\n- Sprint retrospectives\n- Backlog refinement\n\n### Jira Expert (`jira-expert/`)\n\n**Focus:** Jira configuration, custom workflows, automation rules\n\n**Scripts:**\n- `scripts/jql_query_builder.py` — Pattern-matching JQL builder from natural language\n- `scripts/workflow_validator.py` — Validates workflow definitions for anti-patterns\n\n**Key Workflows:**\n- Workflow customization\n- Automation rule creation\n- Board configuration\n- JQL query optimization\n\n### Confluence Expert (`confluence-expert/`)\n\n**Focus:** Documentation strategy, templates, knowledge management\n\n**Scripts:**\n- `scripts/space_structure_generator.py` — Generates space hierarchy from team description\n- `scripts/content_audit_analyzer.py` — Analyzes page inventory for stale/orphaned content\n\n**Key Workflows:**\n- Space architecture design\n- Template library creation\n- Documentation standards\n- Search optimization\n\n### Atlassian Admin (`atlassian-admin/`)\n\n**Focus:** Suite administration, user management, integrations\n\n**Scripts:**\n- `scripts/permission_audit_tool.py` — Analyzes permission schemes for security gaps\n\n**Key Workflows:**\n- User provisioning and permissions\n- SSO/SAML configuration\n- App marketplace management\n- Performance monitoring\n\n### Atlassian Templates (`atlassian-templates/`)\n\n**Focus:** Ready-to-use templates for common PM tasks\n\n**Scripts:**\n- `scripts/template_scaffolder.py` — Generates Confluence storage-format XHTML templates\n\n**Available Templates:**\n- Sprint planning template\n- Retrospective formats (Start-Stop-Continue, 4Ls, Mad-Sad-Glad)\n- Project charter\n- Risk register\n- Decision log\n\n## Integration Patterns\n\n### Pattern 1: Sprint Planning\n\n```bash\n# 1. Create the sprint in the Jira board UI (sprint creation is NOT available via MCP —\n#    use Jira Software UI or REST /rest/agile/1.0/sprint)\n\n# 2. Generate user stories (product-team integration)\npython ../product-team/agile-product-owner/scripts/user_story_generator.py sprint 30\n\n# 3. Import stories to Jira via MCP: one mcp__atlassian__createJiraIssue call per story\n#    (cloudId, projectKey, issueTypeName=\"Story\", summary, description)\n```\n\n### Pattern 2: Documentation Workflow\n\n```bash\n# 1. Scaffold storage-format XHTML, then create the Confluence page via MCP\npython skills/atlassian-templates/scripts/template_scaffolder.py meeting-notes\n#    → pass the emitted markup as the body of mcp__atlassian__createConfluencePage\n\n# 2. Link the page to a Jira issue: paste the page URL into the issue via\n#    mcp__atlassian__editJiraIssue or as a comment via mcp__atlassian__addCommentToJiraIssue\n#    (read existing links with mcp__atlassian__getJiraIssueRemoteIssueLinks)\n```\n\n## Python Automation Tools\n\n### New Scripts (Phase 2)\n\n```bash\n# JQL from natural language\npython jira-expert/scripts/jql_query_builder.py \"high priority bugs assigned to me\"\n\n# Validate Jira workflow\npython jira-expert/scripts/workflow_validator.py workflow.json\n\n# Generate Confluence space structure\npython confluence-expert/scripts/space_structure_generator.py team_info.json\n\n# Audit Confluence content health\npython confluence-expert/scripts/content_audit_analyzer.py pages.json\n\n# Audit Atlassian permissions\npython atlassian-admin/scripts/permission_audit_tool.py permissions.json\n\n# Scaffold Confluence templates\npython atlassian-templates/scripts/template_scaffolder.py meeting-notes\n```\n\n## Additional Resources\n\n- **Installation Guide:** `INSTALLATION_GUIDE.txt`\n- **Implementation Summary:** `IMPLEMENTATION_SUMMARY.md`\n- **Real-World Scenario:** `REAL_WORLD_SCENARIO.md`\n- **PM Overview:** `README.md`\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** July 3, 2026\n**Skills Deployed:** 9/9 PM skills production-ready (pm-skills is now a fork-orchestrator + delivery loop)\n**Total Tools:** 15 Python automation tools\n**Agents:** cs-pm-orchestrator, cs-project-manager | **Commands:** 6\n**Integration:** Atlassian Remote MCP Server (bundled via `.mcp.json`) for Jira/Confluence automation\n\n<!-- File: ra-qm-team/CLAUDE.md (Tokens: ~1098 | Category: claude-rule) -->\n# Regulatory Affairs & Quality Management Skills - Claude Code Guidance\n\nThis guide covers the 14 production-ready RA/QM compliance skills for HealthTech/MedTech companies.\n\n## RA/QM Skills Overview\n\n**Strategic Leadership (2 skills):**\n- regulatory-affairs-head - RA strategy, regulatory intelligence, authority relations\n- quality-manager-qmr - QMS oversight, management review, quality culture\n\n**Quality Systems (3 skills):**\n- quality-manager-qms-iso13485 - ISO 13485 compliance, process management\n- capa-officer - CAPA system management, root cause analysis\n- quality-documentation-manager - DHF, DMR, DHR management\n\n**Risk & Security (2 skills):**\n- risk-management-specialist - ISO 14971 compliance, risk analysis\n- information-security-manager-iso27001 - ISO 27001, data protection, ISMS\n\n**Regulatory Specialists (2 skills):**\n- mdr-745-specialist - EU MDR 2017/745 compliance, technical documentation\n- fda-consultant-specialist - FDA 510(k), PMA, QSR compliance\n\n**Audit & Compliance (4 skills):**\n- qms-audit-expert - Internal audits, ISO 13485 certification\n- isms-audit-expert - ISO 27001 audits, security assessments\n- gdpr-dsgvo-expert - GDPR/DSGVO compliance, data privacy\n- soc2-compliance - SOC 2 Type I/II compliance, trust service criteria, audit readiness\n\n**Total:** 14 specialized compliance skills for medical device industry\n\n## Compliance Frameworks\n\n### ISO 13485 (Medical Device Quality Management)\n\n**Managed by:** quality-manager-qms-iso13485, qms-audit-expert\n\n**Key Areas:**\n- Management responsibility\n- Resource management\n- Product realization\n- Measurement, analysis, improvement\n\n**Tools:**\n- QMS process mapping\n- Document control systems\n- Change management workflows\n\n### ISO 14971 (Medical Device Risk Management)\n\n**Managed by:** risk-management-specialist\n\n**Key Areas:**\n- Risk analysis and evaluation\n- Risk control measures\n- Residual risk evaluation\n- Risk management review\n\n**Tools:**\n- Risk assessment templates\n- FMEA/FMECA analysis\n- Risk-benefit analysis\n\n### MDR 2017/745 (EU Medical Device Regulation)\n\n**Managed by:** mdr-745-specialist\n\n**Key Areas:**\n- Technical documentation (Annex II, III)\n- Clinical evaluation (Annex XIV)\n- Post-market surveillance\n- UDI (Unique Device Identification)\n\n### FDA Regulations (US Medical Device Compliance)\n\n**Managed by:** fda-consultant-specialist\n\n**Key Areas:**\n- 510(k) premarket notification\n- PMA (Premarket Approval)\n- QSR (Quality System Regulation)\n- Post-market reporting\n\n### ISO 27001 (Information Security Management)\n\n**Managed by:** information-security-manager-iso27001, isms-audit-expert\n\n**Key Areas:**\n- ISMS establishment and maintenance\n- Risk assessment and treatment\n- Security controls (Annex A)\n- Continuous improvement\n\n### GDPR/DSGVO (Data Protection)\n\n**Managed by:** gdpr-dsgvo-expert\n\n**Key Areas:**\n- Data protection impact assessment (DPIA)\n- Privacy by design\n- Data subject rights\n- Breach notification\n\n## Regulatory Workflows\n\n### Workflow 1: New Medical Device Development\n\n```\n1. Risk Management (ISO 14971) → risk-management-specialist\n2. QMS Process Setup (ISO 13485) → quality-manager-qms-iso13485\n3. Technical Documentation (MDR) → mdr-745-specialist\n4. FDA Submission → fda-consultant-specialist\n5. Clinical Evaluation → regulatory-affairs-head\n```\n\n### Workflow 2: QMS Audit Preparation\n\n```\n1. Internal Audit → qms-audit-expert\n2. CAPA Implementation → capa-officer\n3. Document Review → quality-documentation-manager\n4. Management Review → quality-manager-qmr\n5. Certification Audit → qms-audit-expert\n```\n\n### Workflow 3: Data Protection Compliance\n\n```\n1. GDPR Assessment → gdpr-dsgvo-expert\n2. ISMS Implementation → information-security-manager-iso27001\n3. Security Audit → isms-audit-expert\n4. Continuous Monitoring → information-security-manager-iso27001\n```\n\n## Integration Patterns\n\n**RA/QM ↔ Engineering:** Regulatory requirements inform technical design decisions\n\n**RA/QM ↔ Product:** Compliance requirements shape product features and roadmap\n\n**RA/QM ↔ Security:** ISO 27001 aligns with security engineering practices\n\n## Additional Resources\n\n- **RA/QM Overview:** `README.md`\n- **Complete Skills Collection:** `final-complete-skills-collection.md`\n- **Start Here:** `START_HERE.md` (if exists)\n- **Main Documentation:** `../CLAUDE.md`\n\n---\n\n**Last Updated:** May 10, 2026\n**Skills Deployed:** 14/14 RA/QM skills production-ready\n**Focus:** Medical device compliance (ISO 13485, MDR, FDA, ISO 27001, GDPR)\n\n<!-- File: research-ops/CLAUDE.md (Tokens: ~1320 | Category: claude-rule) -->\n# Research Operations — Domain Guide\n\nThis file provides domain-specific guidance for skills in `research-ops/`.\n\n## Purpose\n\nThe Research Operations domain ships skills that help **R&D leads, clinical study teams, R&D finance/controllers, market-research analysts, and product-research / ResearchOps teams** plan, fund, scope, and synthesize research across enterprise workstreams. This is the **enterprise / cross-functional counterpart** to the academic `research/` domain (litreview, grants, patent, syllabus, pulse, dossier, notebooklm).\n\nIt is **not regulatory submission** (`ra-qm-team`), **not corporate financial close/valuation** (`finance/financial-analysis`), **not funding discovery** (`research/grants`), **not persona/journey/live-experiment design** (`product-team`), and **not campaign analytics** (`marketing-skill`).\n\n## Skills (v2.9.0)\n\n| Skill | Purpose | `context: fork`? |\n|---|---|---|\n| `research-ops-skills` | Domain orchestrator — routes to 4 sub-skills | YES |\n| `clinical-research` | Study design: protocol synopsis + endpoint selection + sample-size/power + phase-gating | NO |\n| `research-finance` | R&D program budgeting + burn/runway + F&A rate modeling + capitalize-vs-expense routing | NO |\n| `market-research` | TAM/SAM/SOM (both methods) + survey/sampling design + segmentation + CI synthesis | NO |\n| `product-research` | Study design + saturation/sample method + insight repository synthesis | NO |\n\n## Hard rules (domain-specific)\n\n1. **clinical-research: outputs are study-design RECOMMENDATIONS signed by a named clinician/biostatistician/regulatory owner.** Power/sample-size is an ESTIMATE with stated assumptions — never presented as clinical fact. Every tool prints an \"ESTIMATE — confirm with a biostatistician\" banner.\n2. **research-finance: every budget output surfaces its assumptions block.** Capitalize-vs-expense routes to a NAMED finance owner and never auto-decides accounting treatment.\n3. **market-research: TAM/SAM/SOM always shows method (top-down AND bottoms-up) + assumptions.** Never a single unsourced number.\n4. **product-research: never fabricates user insight.** Sample-size/saturation guidance is method-based and surfaces confidence; single-source claims are flagged as anecdotes, not insights.\n5. **Stdlib-only Python.** Deterministic logic, no LLM calls in scripts.\n6. **Industry tuning** via `--profile` on every scoring tool.\n7. **Matt Pocock grill discipline** — `/cs-grill-research-ops` interrogates the plan against the research canon (ICH E9, IAS 38, Cochran, Nielsen, Kotler) before any sub-skill runs.\n8. **Onboarding-first + customization-in-use.** Each sub-skill ships `scripts/onboard.py` (its own question set) + `scripts/config_loader.py`. Answers persist to `~/.config/research-ops/<skill>.json` (global) or `./.research-ops/<skill>.json` (project) and are consumed by every tool (CLI flags override; `RESEARCH_OPS_NO_CONFIG=1` bypasses). Customization must change behavior, not sit as decoration.\n9. **Autoresearch is opt-in + isolated.** Each sub-skill ships `scripts/ar_evaluator.py` — a per-skill, locked ground-truth bridge to `engineering/autoresearch-agent`. A loop is invoked ONLY on explicit user request and only edits the skill's input file, never the evaluator. No cross-skill coupling.\n\n## Build pattern\n\nPath-B contract per skill: SKILL.md + 3 stdlib scoring scripts + 3 references (each citing 5-7 sources) + 1 asset template, **plus** 3 integration scripts — `onboard.py` (questionnaire), `config_loader.py` (customization loader, project→global→defaults precedence), and `ar_evaluator.py` (isolated autoresearch bridge). SKILL.md includes a \"Forcing-question library\" section (cited-canon grilling, one question at a time) and the \"Onboarding & customization\" + \"Optimize with autoresearch (opt-in)\" sections.\n\n## Agent + command pattern\n\n- `cs-research-ops-orchestrator` — evidence-first R&D operations lead. Voice: \"What decision does this research drive, and what's your confidence — show me the method and the assumptions before the number.\"\n- `/cs-research-ops <inquiry>` — top-level router\n- `/cs-grill-research-ops <plan>` — Matt-style grilling first\n- `/cs-clinical-research`, `/cs-research-finance`, `/cs-market-research`, `/cs-product-research` — direct per-skill invocation\n\n## Anti-patterns (domain-level)\n\n- ❌ Skills that overlap `ra-qm-team` (regulatory/QM submission) — clinical-research designs the **study**, not the submission\n- ❌ Skills that overlap `finance/financial-analysis` (close/valuation) — research-finance manages **R&D program spend**\n- ❌ Skills that overlap `research/grants` (funding discovery) — research-finance manages **money already won**\n- ❌ Skills that overlap `product-team` (persona/journey/live experiments) — product-research is **method + repository discipline**\n- ❌ Skills that overlap `marketing-skill` (campaign analytics) — market-research is **upstream methodology**\n- ❌ A market size stated as a single unsourced number\n- ❌ A clinical power/endpoint output presented as fact rather than an estimate with a named owner\n- ❌ A product insight asserted from a single participant\n\n## References\n\n- Master plan: `documentation/implementation/research-ops-expansion-plan.md`\n- Matt Pocock derivation: `engineering/grill-with-docs`\n- Academic counterpart: `research/` (litreview, grants, patent)\n- Regulatory complement: `ra-qm-team`\n- Corporate-finance complement: `finance/financial-analysis`\n- Product complement: `product-team`\n\n<!-- File: standards/CLAUDE.md (Tokens: ~1063 | Category: claude-rule) -->\n# Standards Library - Claude Code Guidance\n\nThis guide explains how to use the standards library for consistent quality across all skills and agents.\n\n## Standards Overview\n\n**Location:** `standards/`\n\n**Available Standards:**\n1. **communication/** - Communication principles and response protocols\n2. **quality/** - Code quality, testing, and validation standards\n3. **git/** - Git workflow, conventional commits, branching strategy\n4. **documentation/** - Markdown quality, structure consistency, living docs\n5. **security/** - Secret detection, dependency security, input validation\n\n## When to Reference Standards\n\n### Communication Standards\n\n**Reference when:**\n- Writing agent documentation\n- Creating SKILL.md files\n- Drafting user-facing content\n- Providing technical guidance\n\n**Key Principles:**\n- Absolute honesty - Direct assessments without cushioning\n- Zero fluff - Eliminate vague statements\n- Pragmatic focus - Actionable suggestions only\n- File economy - Edit existing files vs creating new ones\n\n**Location:** `communication/communication-standards.md`\n\n### Quality Standards\n\n**Reference when:**\n- Creating Python automation tools\n- Writing agent workflows\n- Implementing skill features\n- Testing integration points\n\n**Key Areas:**\n- Python tool quality (PEP 8, type hints, docstrings)\n- Agent workflow clarity (minimum 3 workflows documented)\n- Testing requirements (functional, integration, documentation)\n- Completion criteria (zero defect handoff, validation requirements)\n\n**Location:** `quality/quality-standards.md`\n\n### Git Workflow Standards\n\n**Reference when:**\n- Committing code changes\n- Creating feature branches\n- Tagging releases\n- Writing commit messages\n\n**Commit Format:**\n```bash\n<type>[optional scope]: <description>\n\n[optional body]\n\n[optional footer(s)]\n```\n\n**Types:** feat, fix, docs, style, refactor, perf, test, chore, ci\n\n**Examples:**\n```bash\nfeat(agents): implement cs-content-creator agent\nfix(seo-optimizer): correct keyword density calculation\ndocs(README): add agent catalog section\n```\n\n**Location:** `git/git-workflow-standards.md`\n\n### Documentation Standards\n\n**Reference when:**\n- Writing SKILL.md files\n- Creating agent documentation\n- Updating README files\n- Writing reference guides\n\n**Best Practices:**\n- Max 200 lines per CLAUDE.md file\n- Markdown formatting standards (headings, lists, code blocks)\n- Living documentation (README, CLAUDE, AGENTS updated regularly)\n- Link validation (no 404s, no broken references)\n\n**Location:** `documentation/documentation-standards.md`\n\n### Security Standards\n\n**Reference when:**\n- Writing Python scripts\n- Handling user input\n- Managing dependencies\n- Committing code\n\n**Critical Checks:**\n- No hardcoded API keys, passwords, or tokens\n- Environment variables for sensitive data\n- Input validation for all user input\n- Dependency security audits\n\n**Location:** `security/security-standards.md`\n\n## Standards Application Workflow\n\n### For New Skills\n\n```bash\n# 1. Reference communication standards\ncat standards/communication/communication-standards.md\n\n# 2. Review quality standards for Python tools\ncat standards/quality/quality-standards.md\n\n# 3. Follow documentation standards for SKILL.md\ncat standards/documentation/documentation-standards.md\n\n# 4. Apply security standards to scripts\ncat standards/security/security-standards.md\n\n# 5. Use git standards for commits\ncat standards/git/git-workflow-standards.md\n```\n\n### For New Agents\n\n```bash\n# 1. Communication: Write clear, actionable agent docs\n# 2. Quality: Minimum 3 workflows, tested relative paths\n# 3. Documentation: Follow agent template structure\n# 4. Git: Conventional commit with feat(agents) scope\n```\n\n## Standards Hierarchy\n\n**Priority Order:**\n1. **Security** - Non-negotiable, always enforced\n2. **Quality** - Zero defect handoff required\n3. **Git** - Conventional commits for all changes\n4. **Documentation** - Living docs stay current\n5. **Communication** - Clear, pragmatic, actionable\n\n## Standards Compliance Checklist\n\n### Before Committing Code\n\n- [ ] Communication: Documentation is clear and actionable\n- [ ] Quality: All tests passing, code reviewed\n- [ ] Git: Conventional commit message format\n- [ ] Documentation: Living docs updated if needed\n- [ ] Security: No secrets, input validated, dependencies secure\n\n### Before Creating PR\n\n- [ ] All standards compliance checks passed\n- [ ] Related documentation updated\n- [ ] Examples tested and working\n- [ ] No broken links or references\n\n## Related Documentation\n\n- **Main CLAUDE.md:** `../CLAUDE.md`\n- **Agent Development:** `../agents/CLAUDE.md`\n- **Domain Skills:** See navigation map in main CLAUDE.md\n\n---\n\n**Last Updated:** November 5, 2025\n**Standards Count:** 5 comprehensive standards\n**Enforcement:** Required for all skills and agents\n\n<!-- File: templates/CLAUDE.md (Tokens: ~374 | Category: claude-rule) -->\n# Templates - Claude Code Guidance\n\nThis guide explains the template system for agents, commands, and standardized workflows.\n\n## Template Purpose\n\n**Location:** `templates/`\n\n**Purpose:** Reusable templates for consistent agent development, slash command creation, and workflow automation across all domains.\n\n## Available Templates\n\n### Agent Templates\n\n**Location:** `templates/agent-template.md`\n\n**Usage:** Starting point for creating new cs-* agents\n\n**Contains:**\n- YAML frontmatter structure\n- Required markdown sections\n- Workflow documentation format\n- Integration examples pattern\n\n**When to Use:** Creating any new agent in `agents/` directory\n\n### Command Templates and Workflow Templates\n\nNot yet created. There is no command template or workflow template file in `templates/` today — when creating slash commands, copy an existing command in `commands/` (e.g. `commands/cs-backend-review.md` for the argument-hint + gate pattern) instead of looking for a template here.\n\n## Template Usage Pattern\n\n```bash\n# 1. Copy template\ncp templates/agent-template.md agents/domain/cs-new-agent.md\n\n# 2. Customize for your agent\nvim agents/domain/cs-new-agent.md\n\n# 3. Follow template structure exactly\n\n# 4. Test relative paths and integrations\n\n# 5. Commit with conventional commit\ngit commit -m \"feat(agents): implement cs-new-agent from template\"\n```\n\n## Related Documentation\n\n- **Agent Development:** `../agents/CLAUDE.md` - Comprehensive agent creation guide\n- **Standards:** `../standards/CLAUDE.md` - Quality and consistency standards\n- **Main Documentation:** `../CLAUDE.md` - Repository overview\n\n---\n\n**Last Updated:** November 5, 2025\n**Purpose:** Consistent templates for rapid agent and workflow development\n\n<!-- File: .gemini/skills/changelog/SKILL.md (Tokens: ~5 | Category: anthropic-skill) -->\n../../../commands/changelog.md\n\n<!-- File: .gemini/skills/chaos-experiment/SKILL.md (Tokens: ~8 | Category: anthropic-skill) -->\n../../../commands/chaos-experiment.md\n\n<!-- File: .gemini/skills/competitive-matrix/SKILL.md (Tokens: ~7 | Category: anthropic-skill) -->\n../../../commands/competitive-matrix.md\n\n<!-- File: .gemini/skills/content-strategist/SKILL.md (Tokens: ~9 | Category: anthropic-skill) -->\n../../../agents/personas/content-strategist.md\n\n<!-- File: .gemini/skills/cs-aeo/SKILL.md (Tokens: ~9 | Category: anthropic-skill) -->\n../../../agents/marketing/cs-aeo.md\n\n<!-- File: .gemini/skills/cs-agile-product-owner/SKILL.md (Tokens: ~9 | Category: anthropic-skill) -->\n../../../agents/product/cs-agile-product-owner.md\n\n<!-- File: .gemini/skills/cs-backend-engineer/SKILL.md (Tokens: ~9 | Category: anthropic-skill) -->\n../../../agents/engineering/cs-backend-engineer.md\n\n<!-- File: .gemini/skills/cs-backend-review/SKILL.md (Tokens: ~6 | Category: anthropic-skill) -->\n../../../commands/cs-backend-review.md\n\n<!-- File: .gemini/skills/cs-ceo-advisor/SKILL.md (Tokens: ~10 | Category: anthropic-skill) -->\n../../../agents/c-level/cs-ceo-advisor.md\n\n<!-- File: .gemini/skills/cs-content-creator/SKILL.md (Tokens: ~9 | Category: anthropic-skill) -->\n../../../agents/marketing/cs-content-creator.md\n\n<!-- File: .gemini/skills/cs-cto-advisor/SKILL.md (Tokens: ~11 | Category: anthropic-skill) -->\n../../../agents/c-level/cs-cto-advisor.md\n\n<!-- ... +2629 more modular skills available via /api/skills/alirezarezvani/claude-skills?path={path} -->\n</yakaai_skills>"}