ruflo (Agent Skills)

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🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

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Documentation Agent Skills & Rules MCP Server API Specification

AGENTS.md

# Claude Flow V3 - Agent Guide

> **For OpenAI Codex CLI** - Agentic AI Foundation standard
> Skills: `$skill-name` | Config: `.agents/config.toml`

---

## 📢 TL;DR - READ THIS FIRST

```
╔═══════════════════════════════════════════════════════════════════════════╗
║  1. claude-flow = LEDGER (tracks state, stores memory, coordinates)       ║
║  2. Codex = EXECUTOR (writes code, runs commands, creates files)          ║
║  3. NEVER stop after calling claude-flow - IMMEDIATELY continue working   ║
║  4. If you need something BUILT/EXECUTED, YOU do it, not claude-flow      ║
║  5. ALWAYS search memory BEFORE starting: memory search --query "task"    ║
║  6. ALWAYS store patterns AFTER success: memory store --namespace patterns║
╚═══════════════════════════════════════════════════════════════════════════╝
```

**Workflow (Use MCP Tools):**
1. `memory_search(query="task keywords")` → LEARN from past patterns (score > 0.7 = use it)
2. `swarm_init(topology="hierarchical")` → coordination record (instant)
3. **YOU write the code / run the commands** ← THIS IS WHERE WORK HAPPENS
4. `memory_store(key="pattern-x", value="what worked", namespace="patterns")` → REMEMBER for next time

---

## Ruflo Policy-Governed Concurrent Codex Workflow

Ruflo is the coordination ledger and policy decision point. Codex agents are
the executors. Coordination records do not write code or run tests.

Use `guidance_brain({ mode: "recommend", task: "..." })` to select Ruflo
capabilities from the live MCP registry. A registered tool is not necessarily
configured, reachable, healthy, or authorized. If it is unavailable, continue
with compatible guidance tools, CLI discovery, and repository instructions.

1. Recall relevant AgentDB memory and ADRs.
2. Inspect source, runtime, dependencies, policy, and health.
3. Route to the smallest capable topology, agents, skills, and tools.
4. Plan acceptance criteria, safety envelope, ownership, and validation.
5. Execute with Codex workers in isolated scopes; Ruflo records coordination.
6. Test focused, regression, and failure paths.
7. Validate types, security, policy, compatibility, and artifact integrity.
8. Benchmark a source-bound candidate against a source-bound baseline.
9. Optimize only measured bottlenecks without weakening safety.
10. Bind claims and evidence into exact source/build receipts.
11. Reconcile handoffs and disclose unresolved limitations.
12. Publish only through a separately authorized release gate.

Hard invariants:

- Never run two writers in one worktree.
- Delegation may only reduce tools, servers, namespaces, network, spend,
  concurrency, expiry, and depth.
- Policy denial cancels dependent work before side effects.
- MetaHarness may evaluate candidates concurrently, but only ADR-322A may
  promote them and MetaHarness may never expand its own SafetyEnvelope.
- Do not commit, push, merge, release, or remove worktrees unless authorized.
- Existing installations migrate in `legacy` policy mode; use `observe` before
  switching to `enforce`.

Repository harness integration:

- If tracked repository instructions define a collaboration harness, start its
  session only after assigning an isolated worktree.
- Inspect existing claims, acquire exact paths/resources/ports, renew leases,
  check acknowledged inbox messages at integration boundaries, and release ownership on
  handoff or exit.
- A repository lease coordinates ownership; it does not grant authorization.
  Protected work still requires the ADR-324/325 action capability and current
  fencing epoch.
- In-memory reference adapters demonstrate semantics; they are not distributed,
  restart-durable release authorities.
- Heartbeats and lease expiry establish liveness; a PID is diagnostic only.
- `HEAD` alone is not an exact source-state identity in a dirty worktree.
  Release evidence must bind a clean commit or an immutable snapshot of tracked
  and untracked changes.

Useful checks:

```bash
npx ruflo policy status
npx ruflo policy verify
npx ruflo metaharness flywheel status
```

Repository release contract:

- The stable public train is exactly `@claude-flow/cli`, `claude-flow`, and
  `ruflo`; internal `@claude-flow/*` components are bundled and are not part of
  a normal standalone publish.
- Publish from a clean, reviewed source state in that order.
- Only the CLI publish receives the helper-signing configuration from
  `ruv-dev`; use the existing authenticated npm session for publication.
- Run `node scripts/audit-umbrella-version-lockstep.mjs`, verify all three
  registry versions, and align `latest`, `alpha`, and `v3alpha`.

---

## 🚨 CRITICAL: CODEX DOES THE WORK, CLAUDE-FLOW ORCHESTRATES

```
┌─────────────────────────────────────────────────────────────┐
│  CLAUDE-FLOW = ORCHESTRATOR (tracks state, coordinates)     │
│  CODEX = WORKER (writes code, runs commands, implements)    │
└─────────────────────────────────────────────────────────────┘
```

### ❌ WRONG: Expecting claude-flow to execute tasks
```bash
npx claude-flow swarm start --objective "Build API"
# WRONG: Waiting for claude-flow to build the API
# Claude-flow does NOT execute code!
```

### ✅ CORRECT: Codex executes, claude-flow tracks
```bash
# 1. Tell claude-flow what you're doing (optional coordination)
npx claude-flow swarm init --topology hierarchical --max-agents 1
npx claude-flow agent spawn --type coder --name codex-worker

# 2. YOU (CODEX) DO THE ACTUAL WORK:
mkdir -p src
cat > src/api.ts << 'EOF'
export function hello() { return "Hello World"; }
EOF

# 3. Report to claude-flow what you did (optional)
npx claude-flow memory store --key "api-created" --value "src/api.ts" --namespace results
```

### The Division of Labor

| Component | Role | Examples |
|-----------|------|----------|
| **CODEX** | EXECUTES | Write files, run tests, create code, shell commands |
| **claude-flow** | ORCHESTRATES | Track agents, store memory, coordinate tasks |

---

## ⛔ DON'T STOP AFTER CALLING CLAUDE-FLOW

```
┌─────────────────────────────────────────────────────────────────────────┐
│  ❌ WRONG: Call claude-flow → STOP → Wait for results                   │
│  ✅ RIGHT: Call claude-flow → IMMEDIATELY continue → YOU do the work    │
└─────────────────────────────────────────────────────────────────────────┘
```

### ❌ WRONG Pattern (Stopping)
```bash
npx claude-flow swarm init --topology hierarchical
npx claude-flow agent spawn --type coder --name worker-1
npx claude-flow swarm start --objective "Build hello world"
# WRONG: Codex stops here and waits for something to happen
# Nothing will happen! Claude-flow doesn't execute code!
```

### ✅ CORRECT Pattern (Continue Immediately)
```bash
# Step 1: Coordination (optional)
npx claude-flow swarm init --topology hierarchical
npx claude-flow agent spawn --type coder --name worker-1

# Step 2: IMMEDIATELY DO THE WORK YOURSELF - DON'T WAIT!
echo 'console.log("Hello World!");' > hello.js
node hello.js

# Step 3: Report what you did
npx claude-flow memory store --key "result" --value "Hello World printed" --namespace results
```

### The Rule
**After ANY claude-flow command, IMMEDIATELY continue with your own work.**

Claude-flow commands return instantly. They create coordination RECORDS only.
You must ALWAYS follow up with YOUR OWN execution.

| After This... | IMMEDIATELY Do This... |
|---------------|----------------------|
| `swarm init` | Start writing code |
| `agent spawn` | Continue implementation |
| `task create` | Execute the task yourself |
| `swarm start` | Begin actual work |

---

### When to Use Claude-Flow Commands

| Use Case | Claude-Flow Command | Then Codex Does |
|----------|---------------------|-----------------|
| Track progress | `memory store --key "step1" --value "done"` | Continue to next step |
| Multi-step tasks | `task create --description "step 2"` | Execute step 2 |
| Store results | `memory store --key "output" --value "..."` | Move on |
| Coordinate | `swarm init` | Start working |

### Hello World - Correct Pattern

```bash
# STEP 1: Optional - register with orchestrator
npx claude-flow swarm init --topology mesh --max-agents 1

# STEP 2: CODEX DOES THE WORK
echo 'console.log("Hello World!");' > hello.js
node hello.js

# STEP 3: Optional - report completion
npx claude-flow memory store --key "hello-result" --value "printed Hello World" --namespace results
```

**REMEMBER: If you need something DONE, YOU do it. Claude-flow just tracks.**

---

## ⚡ QUICK COMMANDS (NO DISCOVERY NEEDED)

### Spawn N-Agent Swarm (Copy-Paste Ready)

```bash
# 5-AGENT SWARM - Run these commands in sequence:
npx claude-flow swarm init --topology hierarchical --max-agents 8
npx claude-flow agent spawn --type coordinator --name coord-1
npx claude-flow agent spawn --type coder --name coder-1
npx claude-flow agent spawn --type coder --name coder-2
npx claude-flow agent spawn --type tester --name tester-1
npx claude-flow agent spawn --type reviewer --name reviewer-1
npx claude-flow swarm start --objective "Your task here" --strategy development
```

### Common Swarm Patterns

| Task | Exact Command |
|------|---------------|
| Init hierarchical swarm | `npx claude-flow swarm init --topology hierarchical --max-agents 8` |
| Init mesh swarm | `npx claude-flow swarm init --topology mesh --max-agents 5` |
| Init V3 mode (15 agents) | `npx claude-flow swarm init --v3-mode` |
| Spawn coder | `npx claude-flow agent spawn --type coder --name coder-1` |
| Spawn tester | `npx claude-flow agent spawn --type tester --name tester-1` |
| Spawn coordinator | `npx claude-flow agent spawn --type coordinator --name coord-1` |
| Spawn architect | `npx claude-flow agent spawn --type architect --name arch-1` |
| Spawn reviewer | `npx claude-flow agent spawn --type reviewer --name rev-1` |
| Spawn researcher | `npx claude-flow agent spawn --type researcher --name res-1` |
| Start swarm | `npx claude-flow swarm start --objective "task" --strategy development` |
| Check swarm status | `npx claude-flow swarm status` |
| List agents | `npx claude-flow agent list` |
| Stop swarm | `npx claude-flow swarm stop` |

### Agent Types (Use with `--type`)

| Type | Purpose |
|------|---------|
| `coordinator` | Orchestrates other agents |
| `coder` | Writes code |
| `tester` | Writes tests |
| `reviewer` | Reviews code |
| `architect` | Designs systems |
| `researcher` | Analyzes requirements |
| `security-architect` | Security design |
| `performance-engineer` | Optimization |

### Task Commands

| Action | Command |
|--------|---------|
| Create task | `npx claude-flow task create --type implementation --description "desc"` |
| List tasks | `npx claude-flow task list` |
| Assign task | `npx claude-flow task assign TASK_ID --agent AGENT_NAME` |
| Task status | `npx claude-flow task status TASK_ID` |
| Cancel task | `npx claude-flow task cancel TASK_ID` |

### Memory Commands

| Action | Command |
|--------|---------|
| Store | `npx claude-flow memory store --key "key" --value "value" --namespace patterns` |
| Search | `npx claude-flow memory search --query "search terms"` |
| List | `npx claude-flow memory list --namespace patterns` |
| Retrieve | `npx claude-flow memory retrieve --key "key"` |

---

## 🚀 SWARM RECIPES

### Recipe 1: Hello World Test (COMPLETE EXAMPLE)

**Step 1: Setup coordination** (returns instantly - don't stop!)
```bash
npx claude-flow swarm init --topology mesh --max-agents 5
npx claude-flow agent spawn --type coder --name hello-main
# ⚠️ DON'T STOP HERE - CONTINUE IMMEDIATELY TO STEP 2
```

**Step 2: YOU (Codex) execute the task** (THIS IS THE REAL WORK)
```bash
# ✅ YOU create the file
echo 'console.log("Hello World from Swarm!");' > /tmp/hello-swarm.js

# ✅ YOU execute it
node /tmp/hello-swarm.js
# Output: Hello World from Swarm!
```

**Step 3: Report completion** (optional - store results)
```bash
npx claude-flow memory store --key "hello-world-result" --value "Executed: Hello World from Swarm!" --namespace results
```

### Recipe 1b: 5-Agent Concurrent Hello World (COMPLETE)
```bash
# COORDINATION (instant - creates records only)
npx claude-flow swarm init --topology hierarchical --max-agents 5
for i in 1 2 3 4 5; do
  npx claude-flow agent spawn --type coder --name "worker-$i"
done

# ⚠️ NOW YOU DO THE ACTUAL CONCURRENT WORK:
for i in 1 2 3 4 5; do
  (echo "Worker $i: Hello World!" && sleep 0.$i) &
done
wait
echo "All 5 workers completed!"

# REPORT (optional)
npx claude-flow memory store --key "concurrent-result" --value "5 workers completed" --namespace results
```

### Recipe 1b: Hello World (Single Command Block)
```bash
# All-in-one execution
npx claude-flow swarm init --topology mesh --max-agents 5 && \
npx claude-flow agent spawn --type coder --name hello-main && \
npx claude-flow swarm start --objective "Print hello world" --strategy development && \
echo 'console.log("Hello World from Swarm!");' > /tmp/hello-swarm.js && \
node /tmp/hello-swarm.js && \
npx claude-flow memory store --key "hello-world-result" --value "Success" --namespace results
```

### Recipe 2: Feature Implementation (6 Agents)
```bash
npx claude-flow swarm init --topology hierarchical --max-agents 8
npx claude-flow agent spawn --type coordinator --name lead
npx claude-flow agent spawn --type architect --name arch
npx claude-flow agent spawn --type coder --name impl-1
npx claude-flow agent spawn --type coder --name impl-2
npx claude-flow agent spawn --type tester --name test
npx claude-flow agent spawn --type reviewer --name review
npx claude-flow swarm start --objective "Implement [feature]" --strategy development
```

### Recipe 3: Bug Fix (4 Agents)
```bash
npx claude-flow swarm init --topology hierarchical --max-agents 4
npx claude-flow agent spawn --type coordinator --name lead
npx claude-flow agent spawn --type researcher --name debug
npx claude-flow agent spawn --type coder --name fix
npx claude-flow agent spawn --type tester --name verify
npx claude-flow swarm start --objective "Fix [bug]" --strategy development
```

### Recipe 4: Security Audit (3 Agents)
```bash
npx claude-flow swarm init --topology hierarchical --max-agents 4
npx claude-flow agent spawn --type coordinator --name lead
npx claude-flow agent spawn --type security-architect --name audit
npx claude-flow agent spawn --type reviewer --name review
npx claude-flow swarm start --objective "Security audit" --strategy development
```

### Recipe 5: V3 Full Coordination (15 Agents)
```bash
npx claude-flow swarm init --v3-mode
npx claude-flow swarm coordinate --agents 15
```

---

## 📋 BEHAVIORAL RULES

- **YOU (CODEX) execute tasks** - claude-flow only orchestrates
- Do what is asked; nothing more, nothing less
- NEVER create files unless absolutely necessary
- ALWAYS prefer editing existing files
- NEVER save to root folder
- NEVER commit secrets or .env files
- ALWAYS read a file before editing it
- NEVER wait for claude-flow to "do work" - it doesn't execute, YOU do
- Use claude-flow commands to TRACK progress, not to EXECUTE tasks

## 📁 FILE ORGANIZATION

| Directory | Purpose |
|-----------|---------|
| `/src` | Source code |
| `/tests` | Test files |
| `/docs` | Documentation |
| `/config` | Configuration |
| `/scripts` | Utility scripts |

## 🎯 WHEN TO USE SWARMS

**USE SWARM:**
- Multiple files (3+)
- New feature implementation
- Cross-module refactoring
- API changes with tests
- Security-related changes
- Performance optimization

**SKIP SWARM:**
- Single file edits
- Simple bug fixes (1-2 lines)
- Documentation updates
- Configuration changes

---

## 🔧 CLI REFERENCE

### Swarm Commands
```bash
npx claude-flow swarm init [--topology TYPE] [--max-agents N] [--v3-mode]
npx claude-flow swarm start --objective "task" --strategy [development|research]
npx claude-flow swarm status [SWARM_ID]
npx claude-flow swarm stop [SWARM_ID]
npx claude-flow swarm scale --count N
npx claude-flow swarm coordinate --agents N
```

### Agent Commands
```bash
npx claude-flow agent spawn --type TYPE --name NAME
npx claude-flow agent list [--filter active|idle|busy]
npx claude-flow agent status AGENT_ID
npx claude-flow agent stop AGENT_ID
npx claude-flow agent metrics [AGENT_ID]
npx claude-flow agent health
npx claude-flow agent logs AGENT_ID
```

### Task Commands
```bash
npx claude-flow task create --type TYPE --description "desc"
npx claude-flow task list [--all]
npx claude-flow task status TASK_ID
npx claude-flow task assign TASK_ID --agent AGENT_NAME
npx claude-flow task cancel TASK_ID
npx claude-flow task retry TASK_ID
```

### Memory Commands
```bash
npx claude-flow memory store --key KEY --value VALUE [--namespace NS]
npx claude-flow memory search --query "terms" [--namespace NS]
npx claude-flow memory list [--namespace NS]
npx claude-flow memory retrieve --key KEY [--namespace NS]
npx claude-flow memory init [--force]
```

### Hooks Commands
```bash
npx claude-flow hooks pre-task --description "task"
npx claude-flow hooks post-task --task-id ID --success true
npx claude-flow hooks route --task "task"
npx claude-flow hooks session-start --session-id ID
npx claude-flow hooks session-end --export-metrics true
npx claude-flow hooks worker list
npx claude-flow hooks worker dispatch --trigger audit
```

### System Commands
```bash
npx claude-flow init [--wizard] [--codex] [--full]
npx claude-flow daemon start
npx claude-flow daemon stop
npx claude-flow daemon status
npx claude-flow doctor [--fix]
npx claude-flow status
npx claude-flow mcp start
```

---

## 🔌 TOPOLOGIES

| Topology | Use Case | Command Flag |
|----------|----------|--------------|
| `hierarchical` | Coordinated teams, anti-drift | `--topology hierarchical` |
| `mesh` | Peer-to-peer, equal agents | `--topology mesh` |
| `hierarchical-mesh` | Hybrid (recommended for V3) | `--topology hierarchical-mesh` |
| `ring` | Sequential processing | `--topology ring` |
| `star` | Central coordinator | `--topology star` |
| `adaptive` | Dynamic switching | `--topology adaptive` |

## 🤖 AGENT TYPES

### Core
`coordinator`, `coder`, `tester`, `reviewer`, `architect`, `researcher`

### Specialized
`security-architect`, `security-auditor`, `memory-specialist`, `performance-engineer`

### Swarm Coordination
`hierarchical-coordinator`, `mesh-coordinator`, `adaptive-coordinator`

### Consensus
`byzantine-coordinator`, `raft-manager`, `gossip-coordinator`

---

## ⚙️ CONFIGURATION

### Default Swarm Config
- Topology: `hierarchical`
- Max Agents: 8
- Strategy: `specialized`
- Consensus: `raft`
- Memory: `hybrid`

### Environment Variables
```bash
CLAUDE_FLOW_CONFIG=./claude-flow.config.json
CLAUDE_FLOW_LOG_LEVEL=info
CLAUDE_FLOW_MEMORY_BACKEND=hybrid
```

---

## 🔗 SKILLS

Invoke with `$skill-name`:

| Skill | Purpose |
|-------|---------|
| `$swarm-orchestration` | Multi-agent coordination |
| `$memory-management` | Pattern storage/retrieval |
| `$sparc-methodology` | Structured development |
| `$security-audit` | Security scanning |
| `$performance-analysis` | Profiling |
| `$github-automation` | CI/CD management |
| `$hive-mind` | Byzantine consensus |
| `$neural-training` | Pattern learning |

---

---

## 🔌 MCP INTEGRATION (Learning & Coordination)

Codex doesn't have native hooks like Claude Code, but uses **MCP (Model Context Protocol)** for learning and coordination.

### MCP Auto-Registration

When you run `npx claude-flow init --codex`, the MCP server is **automatically registered** with Codex.

```bash
# Verify MCP is registered:
codex mcp list

# Expected output:
# Name         Command  Args                   Status
# claude-flow  npx      claude-flow mcp start  enabled

# If not present, add manually:
codex mcp add claude-flow -- npx claude-flow mcp start
```

### Test MCP Connection
```bash
# Test MCP server starts correctly:
npx claude-flow mcp start --test
```

### MCP Tools Available
Once added, Codex can use these tools via MCP:

**Coordination:**
| Tool | Purpose |
|------|---------|
| `swarm_init` | Initialize swarm (topology, maxAgents) |
| `swarm_status` | Check swarm state |
| `agent_spawn` | Register agent roles |
| `agent_status` | Check agent state |
| `task_orchestrate` | Coordinate multi-agent tasks |

**Learning & Memory (USE THESE!):**
| Tool | Purpose | When |
|------|---------|------|
| `memory_search` | Semantic vector search | BEFORE every task |
| `memory_store` | Store patterns with embeddings | AFTER success |
| `memory_retrieve` | Get by exact key | When key is known |
| `neural_train` | Train on patterns | Periodic improvement |
| `neural_status` | Check learning state | Debugging |

**Hive Mind (Advanced):**
| Tool | Purpose |
|------|---------|
| `hive-mind_init` | Byzantine consensus swarm |
| `hive-mind_spawn` | Spawn hive workers |
| `hive-mind_broadcast` | Message all workers |

### Self-Learning via MCP Tools (PREFERRED)

Use MCP tools directly - faster than CLI commands:

**BEFORE starting any task - SEARCH for patterns:**
```
Use tool: memory_search
  query: "keywords related to your task"
  namespace: "patterns"
```

**AFTER completing successfully - STORE the pattern:**
```
Use tool: memory_store
  key: "pattern-[descriptive-name]"
  value: "What worked: approach, code patterns, gotchas"
  namespace: "patterns"
```

### MCP Learning Workflow (Use This!)

```
1. LEARN: memory_search(query="task keywords", namespace="patterns")
   → If score > 0.7, USE that pattern

2. COORDINATE: swarm_init(topology="hierarchical")
   → agent_spawn(type="coder", name="worker-1")

3. EXECUTE: YOU write the code, run commands, create files

4. REMEMBER: memory_store(key="pattern-x", value="what worked", namespace="patterns")
```

### MCP Tools for Learning

| Tool | Purpose | When to Use |
|------|---------|-------------|
| `memory_search` | Find similar past patterns | BEFORE starting any task |
| `memory_store` | Save successful patterns | AFTER completing a task |
| `memory_retrieve` | Get specific pattern by key | When you know the exact key |
| `neural_train` | Train on successful patterns | After multiple successes |

### Example: Learning-Enabled Task

```
STEP 1 - LEARN:
Use tool: memory_search
  query: "validation utility function"
  namespace: "patterns"

→ Found: pattern-email-validator (score: 0.82)
→ Use this pattern as reference!

STEP 2 - COORDINATE:
Use tool: swarm_init with topology="hierarchical", maxAgents=3

STEP 3 - EXECUTE:
YOU create the files:
  echo 'export function validate(x) { ... }' > /tmp/validator.js
  node --test /tmp/validator.js

STEP 4 - REMEMBER:
Use tool: memory_store
  key: "pattern-phone-validator"
  value: "Phone validation: regex /^\+?[\d\s-]{10,}$/, normalize first, test edge cases"
  namespace: "patterns"
```

### Vector Search Tips
- Searches are SEMANTIC (meaning-based, not just keywords)
- Score > 0.7 = strong match, use that pattern
- Score 0.5-0.7 = partial match, adapt as needed
- Store DETAILED values for better future retrieval

### CLI Fallback (if MCP unavailable)
```bash
npx claude-flow memory search --query "keywords" --namespace patterns
npx claude-flow memory store --key "pattern-x" --value "what worked" --namespace patterns
```

### Coordination via MCP

When claude-flow is added as MCP server, Codex can call tools directly:
```
Use tool: swarm_init with topology="hierarchical"
Use tool: memory_store with key="result" value="success"
```

### config.toml MCP Setup
```toml
# ~/.codex/config.toml
[mcp_servers.claude-flow]
command = "npx"
args = ["claude-flow", "mcp", "start"]
enabled = true
```

---

## 📚 SUPPORT

- Docs: https://github.com/ruvnet/claude-flow
- Issues: https://github.com/ruvnet/claude-flow/issues

**Remember: Codex executes, claude-flow orchestrates!**

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