Repository: AndyMik90/Aperant
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CLAUDE.md
CLAUDE.md
This file provides guidance to Claude Code when working with this repository.
Auto Claude is an autonomous multi-agent coding framework that plans, builds, and validates software for you. It's a TypeScript-first Electron desktop application with a self-contained AI agent layer (Vercel AI SDK v6). A lightweight Python sidecar provides the optional Graphiti memory system.
Deep-dive reference: ARCHITECTURE.md | Frontend contributing: apps/desktop/CONTRIBUTING.md
Product Overview
Auto Claude is a desktop application (+ CLI) where users describe a goal and AI agents autonomously handle planning, implementation, and QA validation. All work happens in isolated git worktrees so the main branch stays safe.
Core workflow: User creates a task → Spec creation pipeline assesses complexity and writes a specification → Planner agent breaks it into subtasks → Coder agent implements (can spawn parallel subagents) → QA reviewer validates → QA fixer resolves issues → User reviews and merges.
Main features:
- Autonomous Tasks — Multi-agent pipeline (planner, coder, QA) that builds features end-to-end
- Kanban Board — Visual task management from planning through completion
- Agent Terminals — Up to 12 parallel AI-powered terminals with task context injection
- Insights — AI chat interface for exploring and understanding your codebase
- Roadmap — AI-assisted feature planning with strategic roadmap generation
- Ideation — Discover improvements, performance issues, and security vulnerabilities
- GitHub/GitLab Integration — Import issues, AI-powered investigation, PR/MR review and creation
- Changelog — Generate release notes from completed tasks
- Memory System — Graphiti-based knowledge graph retains insights across sessions
- Isolated Workspaces — Git worktree isolation for every build; AI-powered semantic merge
- Flexible Authentication — Use a Claude Code subscription (OAuth) or API profiles with any Anthropic-compatible endpoint (e.g., Anthropic API, z.ai for GLM models)
- Multi-Account Swapping — Register multiple Claude accounts; when one hits a rate limit, Auto Claude automatically switches to an available account
- Cross-Platform — Native desktop app for Windows, macOS, and Linux with auto-updates
Critical Rules
Vercel AI SDK only — All AI interactions use the Vercel AI SDK v6 (ai package) via the TypeScript agent layer in apps/desktop/src/main/ai/. NEVER use @anthropic-ai/sdk or anthropic.Anthropic() directly. Use createProvider() from ai/providers/factory.ts and streamText()/generateText() from the ai package. Provider-specific adapters (e.g., @ai-sdk/anthropic, @ai-sdk/openai) are managed through the provider registry.
i18n required — All frontend user-facing text uses react-i18next translation keys. Hardcoded strings in JSX/TSX break localization for non-English users. Add keys to both en/.json and fr/.json.
Platform abstraction — Never use process.platform directly. Import from apps/desktop/src/main/platform/. CI tests all three platforms.
No time estimates — Provide priority-based ordering instead of duration predictions.
PR target — Always target the develop branch for PRs, not main. Main is reserved for releases.
No console.log in production code — console.log output is invisible in bundled Electron apps. Use Sentry for error tracking in production; reserve console.log for development only.
Work Approach: Orchestrator-First
You are an orchestrator. Your primary role is to understand what needs to be done, break it into workstreams, and delegate execution to agent teams. This keeps your context window focused on coordination and decision-making rather than filling up with implementation details.
<orchestrator_pattern>
When given a task, follow this pattern:
1. Investigate first — Read the actual code before forming any hypothesis. Use targeted searches (Glob, Grep, Read) for simple lookups. For broader exploration, spawn an Explore agent.
2. Plan the approach — Identify what needs to change, which files are involved, and whether work can be parallelized. For multi-step tasks, create a task list to track workstreams.
3. Delegate execution — Spawn agent teams to do the implementation work. Each agent gets a clear, self-contained assignment with all the context it needs: relevant file paths, the specific change to make, and acceptance criteria. Run independent workstreams in parallel.
4. Verify and integrate — Review agent outputs, run tests, and ensure changes work together. Fix integration issues or spawn follow-up agents as needed.
</orchestrator_pattern>
When to delegate vs. do directly:
- Delegate: multi-file changes, research across the codebase, independent parallel workstreams, tasks that would consume significant context
- Do directly: single-file edits, simple bug fixes, quick lookups, tasks where you already have the context
Giving agents good assignments — Each agent works with a fresh context. Include: the specific goal, relevant file paths, code patterns to follow, and what "done" looks like. Agents perform better with explicit, complete instructions than with vague references to "the current task."
Minimal changes only — Prefer the simplest approach (e.g., prompt-only changes, single guard clause) before suggesting multi-component solutions. If the user asks for X, implement X — don't bundle additional fixes they didn't request.
Default to action — When the user's intent implies making changes, implement them rather than only suggesting. If something is unclear, read the relevant code to fill in the gaps rather than asking. Only ask when genuine ambiguity remains about what the user wants.
Context Management
Your context window will be automatically compacted as it approaches its limit, allowing you to continue working indefinitely. Do not stop tasks early due to context concerns — instead, persist progress and keep going.
For long-running tasks: Use git commits, task lists, and structured notes to track state. When context compacts, review git log and any progress files to re-orient. Focus on incremental progress — complete one component before moving to the next, and commit working states along the way.
Parallel tool calls — When reading multiple files, running independent searches, or executing unrelated commands, make all calls in parallel rather than sequentially. This significantly speeds up investigation and implementation.
Known Gotchas
Electron path resolution — For bug fixes in the Electron app, check path resolution differences between dev and production builds (app.isPackaged, process.resourcesPath). Paths that work in dev often break when Electron is bundled for production — verify both contexts.
Resetting PR Review State
To fully clear all PR review data so reviews run fresh, delete/reset these three things in .auto-claude/github/:
1. rm .auto-claude/github/pr/logs_*.json — review log files
2. rm .auto-claude/github/pr/review_*.json — review result files
3. Reset pr/index.json to {"reviews": [], "last_updated": null}
4. Reset bot_detection_state.json to {"reviewed_commits": {}} — this is the gatekeeper; without clearing it, the bot detector skips already-seen commits
Project Structure
autonomous-coding/
├── apps/
│ └── desktop/ # Electron desktop application (sole app)
│ ├── prompts/ # Agent system prompts (.md)
│ └── src/
│ ├── main/ # Electron main process
│ │ ├── ai/ # TypeScript AI agent layer (Vercel AI SDK v6)
│ │ │ ├── providers/ # Multi-provider registry + factory (9+ providers)
│ │ │ ├── tools/ # Builtin tools (Read, Write, Edit, Bash, Glob, Grep, etc.)
│ │ │ ├── security/ # Bash validator, command parser, path containment
│ │ │ ├── config/ # Agent configs (25+ types), phase config, model resolution
│ │ │ ├── session/ # streamText() agent loop, error classification, progress
│ │ │ ├── agent/ # Worker thread executor + bridge
│ │ │ ├── orchestration/ # Build pipeline (planner → coder → QA)
│ │ │ ├── runners/ # Utility runners (insights, roadmap, PR review, etc.)
│ │ │ ├── mcp/ # MCP client integration
│ │ │ ├── client/ # Client factory convenience constructors
│ │ │ └── auth/ # Token resolution (reuses claude-profile/)
│ │ ├── agent/ # Agent queue, process, state, events
│ │ ├── claude-profile/ # Multi-profile credentials, token refresh, usage
│ │ ├── terminal/ # PTY daemon, lifecycle, Claude integration
│ │ ├── platform/ # Cross-platform abstraction
│ │ ├── ipc-handlers/# 40+ handler modules by domain
│ │ ├── services/ # Session recovery, profile service
│ │ └── changelog/ # Changelog generation and formatting
│ ├── preload/ # Electron preload scripts (electronAPI bridge)
│ ├── renderer/ # React UI
│ │ ├── components/ # UI components (onboarding, settings, task, terminal, github, etc.)
│ │ ├── stores/ # 24+ Zustand state stores
│ │ ├── contexts/ # React contexts (ViewStateContext)
│ │ ├── hooks/ # Custom hooks (useIpc, useTerminal, etc.)
│ │ ├── styles/ # CSS / Tailwind styles
│ │ └── App.tsx # Root component
│ ├── shared/ # Shared types, i18n, constants, utils
│ │ ├── i18n/locales/# en/.json, fr/.json
│ │ ├── constants/ # themes.ts, etc.
│ │ ├── types/ # 19+ type definition files
│ │ └── utils/ # ANSI sanitizer, shell escape, provider detection
│ └── types/ # TypeScript type definitions
├── guides/ # Documentation
└── scripts/ # Build and utility scriptsCommands Quick Reference
Setup
npm run install:all # Install all dependencies from root
Or separately:
cd apps/desktop && npm installTesting
| Stack | Command | Tool |
|-------|---------|------|
| Frontend unit | cd apps/desktop && npm test | Vitest |
| Frontend E2E | cd apps/desktop && npm run test:e2e | Playwright |
Releases
node scripts/bump-version.js patch|minor|major # Bump version
git push && gh pr create --base main # PR to main triggers releaseSee RELEASE.md for full release process.
AI Agent Layer (apps/desktop/src/main/ai/)
All AI agent logic lives in TypeScript using the Vercel AI SDK v6. This replaces the previous Python claude-agent-sdk integration.
Architecture Overview
- Provider Layer (providers/) — Multi-provider support via createProviderRegistry(). Supports Anthropic, OpenAI, Google, Bedrock, Azure, Mistral, Groq, xAI, and Ollama. Provider-specific transforms handle thinking token normalization and prompt caching.
- Session Runtime (session/) — runAgentSession() uses streamText() with stopWhen: stepCountIs(N) for agentic tool-use loops. Includes error classification (429/401/400) and progress tracking.
- Worker Threads (agent/) — Agent sessions run in worker_threads to avoid blocking the Electron main process. The WorkerBridge relays postMessage() events to the existing AgentManagerEvents interface.
- Build Orchestration (orchestration/) — Full planner → coder → QA pipeline. Parallel subagent execution via Promise.allSettled().
- Tools (tools/) — 8 builtin tools (Read, Write, Edit, Bash, Glob, Grep, WebFetch, WebSearch) defined with Zod schemas via AI SDK tool().
- Security (security/) — Bash validator, command parser, and path containment ported from Python with identical allowlist behavior.
- Config (config/) — AGENT_CONFIGS registry (25+ agent types), phase-aware model resolution, thinking budgets.
Key Patterns
// Agent session using streamText()
import { streamText, stepCountIs } from 'ai';const result = streamText({
model: provider,
system: systemPrompt,
messages: conversationHistory,
tools: toolRegistry.getToolsForAgent(agentType),
stopWhen: stepCountIs(1000),
onStepFinish: ({ toolCalls, text, usage }) => {
progressTracker.update(toolCalls, text);
},
});
// Tool definition with Zod schema
import { tool } from 'ai';
import { z } from 'zod';
const readTool = tool({
description: 'Read a file from the filesystem',
inputSchema: z.object({
file_path: z.string(),
offset: z.number().optional(),
limit: z.number().optional(),
}),
execute: async ({ file_path, offset, limit }) => { / ... / },
});
Agent Prompts (apps/desktop/prompts/)
| Prompt | Purpose |
|--------|---------|
| planner.md | Implementation plan with subtasks |
| coder.md / coder_recovery.md | Subtask implementation / recovery |
| qa_reviewer.md / qa_fixer.md | Acceptance validation / issue fixes |
| spec_gatherer/researcher/writer/critic.md | Spec creation pipeline |
| complexity_assessor.md | AI-based complexity assessment |
Spec Directory Structure
Each spec in .auto-claude/specs/XXX-name/ contains: spec.md, requirements.json, context.json, implementation_plan.json, qa_report.md, QA_FIX_REQUEST.md
Memory System (Graphiti)
Graph-based semantic memory accessed via a Python MCP sidecar (lives outside apps/desktop/). The AI layer connects to it via createMCPClient from @ai-sdk/mcp. Configured through the Electron app's onboarding/settings UI. See ARCHITECTURE.md for details.
Frontend Development
Tech Stack
React 19, TypeScript (strict), Electron 39, Vercel AI SDK v6, Zustand 5, Tailwind CSS v4, Radix UI, xterm.js 6, Vite 7, Vitest 4, Biome 2, Motion (Framer Motion)
Path Aliases (tsconfig.json)
| Alias | Maps to |
|-------|---------|
| @/ | src/renderer/ |
| @shared/ | src/shared/ |
| @preload/ | src/preload/ |
| @features/ | src/renderer/features/ |
| @components/ | src/renderer/shared/components/ |
| @hooks/ | src/renderer/shared/hooks/ |
| @lib/ | src/renderer/shared/lib/ |
State Management (Zustand)
All state lives in src/renderer/stores/. Key stores:
- project-store.ts — Active project, project list
- task-store.ts — Tasks/specs management
- terminal-store.ts — Terminal sessions and state
- settings-store.ts — User preferences
- github/issues-store.ts, github/pr-review-store.ts — GitHub integration
- insights-store.ts, roadmap-store.ts, kanban-settings-store.ts
Main process also has stores: src/main/project-store.ts, src/main/terminal-session-store.ts
Styling
- Tailwind CSS v4 with @tailwindcss/postcss plugin
- 7 color themes (Default, Dusk, Lime, Ocean, Retro, Neo + more) defined in src/shared/constants/themes.ts
- Each theme has light/dark mode variants via CSS custom properties
- Utility: clsx + tailwind-merge via cn() helper
- Component variants: class-variance-authority (CVA)
IPC Communication
Main ↔ Renderer communication via Electron IPC:
- Handlers: src/main/ipc-handlers/ — organized by domain (github, gitlab, ideation, context, etc.)
- Preload: src/preload/ — exposes safe APIs to renderer
- Pattern: renderer calls via window.electronAPI.*, main handles in IPC handler modules
Agent Management (src/main/agent/)
The frontend manages agent lifecycle end-to-end:
- agent-queue.ts — Queue routing, prioritization, spec number locking
- agent-process.ts — Spawns worker threads via WorkerBridge for agent execution
- agent-state.ts — Tracks running agent state and status
- agent-events.ts — Agent lifecycle events and state transitions (structured events from worker threads)
Claude Profile System (src/main/claude-profile/)
Multi-profile credential management for switching between Claude accounts:
- credential-utils.ts — OS credential storage (Keychain/Windows Credential Manager)
- token-refresh.ts — OAuth token lifecycle and automatic refresh
- usage-monitor.ts — API usage tracking and rate limiting per profile
- profile-scorer.ts — Scores profiles by usage and availability
Terminal System (src/main/terminal/)
Full PTY-based terminal integration:
- pty-daemon.ts / pty-manager.ts — Background PTY process management
- terminal-lifecycle.ts — Session creation, cleanup, event handling
- claude-integration-handler.ts — Claude SDK integration within terminals
- Renderer: xterm.js 6 with WebGL, fit, web-links, serialize addons. Store: terminal-store.ts
Code Quality
Frontend
- Linting: Biome (
npm run lint / npm run lint:fix)- Type checking:
npm run typecheck (strict mode)- Pre-commit: Husky + lint-staged runs Biome on staged
.ts/.tsx/.js/.jsx/.json- Testing: Vitest + React Testing Library + jsdom
i18n Guidelines
All frontend UI text uses react-i18next. Translation files: apps/desktop/src/shared/i18n/locales/{en,fr}/*.json
Namespaces: common, navigation, settings, dialogs, tasks, errors, onboarding, welcome
import { useTranslation } from 'react-i18next';
const { t } = useTranslation(['navigation', 'common']);<span>{t('navigation:items.githubPRs')}</span> // CORRECT
<span>GitHub PRs</span> // WRONG
// With interpolation:
<span>{t('errors:task.parseError', { error })}</span>
When adding new UI text: add keys to ALL language files, use namespace:section.key format.
Cross-Platform
Supports Windows, macOS, Linux. CI tests all three.
Platform modules: apps/desktop/src/main/platform/
| Function | Purpose |
|----------|---------|
| isWindows() / isMacOS() / isLinux() | OS detection |
| getPathDelimiter() | ; (Win) or : (Unix) |
| findExecutable(name) | Cross-platform executable lookup |
| requiresShell(command) | .cmd/.bat shell detection (Win) |
Use findExecutable() and joinPaths() instead of hardcoded paths. See ARCHITECTURE.md for extended guide.
E2E Testing (Electron MCP)
QA agents can interact with the running Electron app via Chrome DevTools Protocol:
1. Start app: npm run dev:debug (debug mode for AI self-validation via Electron MCP)
2. Enable Electron MCP in settings
3. QA runs automatically through the TypeScript agent pipeline
Tools: take_screenshot, click_by_text, fill_input, get_page_structure, send_keyboard_shortcut, eval. See ARCHITECTURE.md for full capabilities.
Running the Application
Desktop app
npm start # Production build + run
npm run dev # Development mode with HMR
npm run dev:debug # Debug mode with verbose output
npm run dev:mcp # Electron MCP server for AI debuggingProject data: .auto-claude/specs/ (gitignored)
README.md
Aperant (formerly Auto Claude)
Autonomous multi-agent coding framework that plans, builds, and validates software for you.
---
Download
Stable Release
<!-- STABLE_VERSION_BADGE -->
<!-- STABLE_VERSION_BADGE_END -->
<!-- STABLE_DOWNLOADS -->
| Platform | Download |
|----------|----------|
| Windows | Auto-Claude-2.7.6-win32-x64.exe |
| macOS (Apple Silicon) | Auto-Claude-2.7.6-darwin-arm64.dmg |
| macOS (Intel) | Auto-Claude-2.7.6-darwin-x64.dmg |
| Linux | Auto-Claude-2.7.6-linux-x86_64.AppImage |
| Linux (Debian) | Auto-Claude-2.7.6-linux-amd64.deb |
| Linux (Flatpak) | Auto-Claude-2.7.6-linux-x86_64.flatpak |
<!-- STABLE_DOWNLOADS_END -->
Beta Release
⚠️ Beta releases may contain bugs and breaking changes. View all releases
<!-- BETA_VERSION_BADGE -->
<!-- BETA_VERSION_BADGE_END -->
<!-- BETA_DOWNLOADS -->
| Platform | Download |
|----------|----------|
| Windows | Aperant-2.8.0-beta.5-win32-x64.exe |
| macOS (Apple Silicon) | Aperant-2.8.0-beta.5-darwin-arm64.dmg |
| macOS (Intel) | Aperant-2.8.0-beta.5-darwin-x64.dmg |
| Linux | Aperant-2.8.0-beta.5-linux-x86_64.AppImage |
| Linux (Debian) | Aperant-2.8.0-beta.5-linux-amd64.deb |
| Linux (Flatpak) | Aperant-2.8.0-beta.5-linux-x86_64.flatpak |
<!-- BETA_DOWNLOADS_END -->
All releases include SHA256 checksums and VirusTotal scan results for security verification.
---
Requirements
- Claude Pro/Max subscription - Get one here
- Claude Code CLI - npm install -g @anthropic-ai/claude-code
- Git repository - Your project must be initialized as a git repo
---
Quick Start
1. Download and install the app for your platform
2. Open your project - Select a git repository folder
3. Connect Claude - The app will guide you through OAuth setup
4. Create a task - Describe what you want to build
5. Watch it work - Agents plan, code, and validate autonomously
---
Features
| Feature | Description |
|---------|-------------|
| Autonomous Tasks | Describe your goal; agents handle planning, implementation, and validation |
| Parallel Execution | Run multiple builds simultaneously with up to 12 agent terminals |
| Isolated Workspaces | All changes happen in git worktrees - your main branch stays safe |
| Self-Validating QA | Built-in quality assurance loop catches issues before you review |
| AI-Powered Merge | Automatic conflict resolution when integrating back to main |
| Memory Layer | Agents retain insights across sessions for smarter builds |
| GitHub/GitLab Integration | Import issues, investigate with AI, create merge requests |
| Linear Integration | Sync tasks with Linear for team progress tracking |
| Cross-Platform | Native desktop apps for Windows, macOS, and Linux |
| Auto-Updates | App updates automatically when new versions are released |
---
Interface
Kanban Board
Visual task management from planning through completion. Create tasks and monitor agent progress in real-time.
Agent Terminals
AI-powered terminals with one-click task context injection. Spawn multiple agents for parallel work.
Roadmap
AI-assisted feature planning with competitor analysis and audience targeting.
Additional Features
- Insights - Chat interface for exploring your codebase
- Ideation - Discover improvements, performance issues, and vulnerabilities
- Changelog - Generate release notes from completed tasks
---
Project Structure
Aperant/
├── apps/
│ └── desktop/ # Electron desktop application (TypeScript AI agent layer + UI)
├── guides/ # Additional documentation
└── scripts/ # Build utilities---
Development
Want to build from source or contribute? See CONTRIBUTING.md for complete development setup instructions.
For Linux-specific builds (Flatpak, AppImage), see guides/linux.md.
---
Security
Aperant uses a three-layer security model:
1. OS Sandbox - Bash commands run in isolation
2. Filesystem Restrictions - Operations limited to project directory
3. Dynamic Command Allowlist - Only approved commands based on detected project stack
All releases are:
- Scanned with VirusTotal before publishing
- Include SHA256 checksums for verification
- Code-signed where applicable (macOS)
---
Available Scripts
| Command | Description |
|---------|-------------|
| npm run install:all | Install all dependencies |
| npm start | Build and run the desktop app |
| npm run dev | Run in development mode with hot reload |
| npm run package | Package for current platform |
| npm run package:mac | Package for macOS |
| npm run package:win | Package for Windows |
| npm run package:linux | Package for Linux |
| npm run package:flatpak | Package as Flatpak (see guides/linux.md) |
| npm run lint | Run linter |
| npm test | Run frontend tests |
---
Contributing
We welcome contributions! Please read CONTRIBUTING.md for:
- Development setup instructions
- Code style guidelines
- Testing requirements
- Pull request process
---
Community
- Discord - Join our community
- Issues - Report bugs or request features
- Discussions - Ask questions
---
License
AGPL-3.0 - GNU Affero General Public License v3.0
Aperant is free to use. If you modify and distribute it, or run it as a service, your code must also be open source under AGPL-3.0.
Commercial licensing available for closed-source use cases.
---
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