agentleFS
Barricadetrecharm99Barricadetrecharm99/ruvnet-ruflo/AGENTS.md

ruvnet-ruflo

AGENTS.md2 starsChanged 45 days agoMITView on GitHub

For OpenAI Codex CLI - Agentic AI Foundation standard Skills: $skill-name | Config: .agents/config.toml 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 is the coordination ledger and policy decision point. Codex agents are the executors. Coordination records do…

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3 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions3 projects use a version of this.

    Word for word · 3

    1. ruvnet/claude-flow★ 80k100% same
    2. ruvnet/ruflo★ 79k100% same
    3. Soulcynics404/AgentForge★ 1100% same

    Edited · 0

    None found.

    Wrote their own version · 0

    None found.

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.

    Of the AGENTS.md files we read, the 31,774 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.

  • In this repositoryOne other file it gives its agents.

The file

Show its rules and text

We split this AGENTS.md into the rules it gives an agent

18 rules. About 1 is common, 13 are distinctive, and 4 are very specific to this project.

  • ≈1

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈13

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 4

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  • could be automatic: a setting could enforce it
  1. Very specific:

    Use guidance_brain({ mode: "recommend", task: "..." }) to select Ruflo capabilities from the live MCP registry.

    line 34
  2. Distinctive:

    Test focused, regression, and failure paths.

    line 44
  3. Distinctive:

    Never run two writers in one worktree.

    line 54
  4. Distinctive:

    Do not commit, push, merge, release, or remove worktrees unless authorized.

    line 60
  5. Distinctive:

    If tracked repository instructions define a collaboration harness, start its session only after assigning an isolated worktree.

    line 66
  6. Very specific:

    Only the CLI publish receives the helper-signing configuration from ruv-dev.

    line 95
  7. Very specific:

    Run node scripts/audit-umbrella-version-lockstep.mjs, verify all three registry versions, and align latest, alpha, and v3alpha.

    line 97
  8. Distinctive:

    Do what is asked; nothing more, nothing less

    line 382
  9. Distinctive:

    NEVER create files unless absolutely necessary

    line 383
  10. Distinctive:

    ALWAYS prefer editing existing files

    line 384
  11. Distinctive:

    NEVER save to root folder

    line 385
  12. Common:

    NEVER commit secrets or .env files

    line 386
  13. Distinctive:

    ALWAYS read a file before editing it

    line 387
  14. Distinctive:

    NEVER wait for claude-flow to "do work" - it doesn't execute, YOU do

    line 388
  15. Distinctive:

    Use claude-flow commands to TRACK progress, not to EXECUTE tasks

    line 389
  16. Very specific:

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

    line 555
  17. Distinctive:

    Use MCP tools directly - faster than CLI commands:

    line 605
  18. Distinctive:

    When claude-flow is added as MCP server, Codex can call tools directly:

    line 685

≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
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:

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

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

# 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

ComponentRoleExamples
CODEXEXECUTESWrite files, run tests, create code, shell commands
claude-flowORCHESTRATESTrack 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)

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)

# 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 initStart writing code
agent spawnContinue implementation
task createExecute the task yourself
swarm startBegin actual work

When to Use Claude-Flow Commands

Use CaseClaude-Flow CommandThen Codex Does
Track progressmemory store --key "step1" --value "done"Continue to next step
Multi-step taskstask create --description "step 2"Execute step 2
Store resultsmemory store --key "output" --value "..."Move on
Coordinateswarm initStart working

Hello World - Correct Pattern

# 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)

# 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

TaskExact Command
Init hierarchical swarmnpx claude-flow swarm init --topology hierarchical --max-agents 8
Init mesh swarmnpx claude-flow swarm init --topology mesh --max-agents 5
Init V3 mode (15 agents)npx claude-flow swarm init --v3-mode
Spawn codernpx claude-flow agent spawn --type coder --name coder-1
Spawn testernpx claude-flow agent spawn --type tester --name tester-1
Spawn coordinatornpx claude-flow agent spawn --type coordinator --name coord-1
Spawn architectnpx claude-flow agent spawn --type architect --name arch-1
Spawn reviewernpx claude-flow agent spawn --type reviewer --name rev-1
Spawn researchernpx claude-flow agent spawn --type researcher --name res-1
Start swarmnpx claude-flow swarm start --objective "task" --strategy development
Check swarm statusnpx claude-flow swarm status
List agentsnpx claude-flow agent list
Stop swarmnpx claude-flow swarm stop

Agent Types (Use with --type)

TypePurpose
coordinatorOrchestrates other agents
coderWrites code
testerWrites tests
reviewerReviews code
architectDesigns systems
researcherAnalyzes requirements
security-architectSecurity design
performance-engineerOptimization

Task Commands

ActionCommand
Create tasknpx claude-flow task create --type implementation --description "desc"
List tasksnpx claude-flow task list
Assign tasknpx claude-flow task assign TASK_ID --agent AGENT_NAME
Task statusnpx claude-flow task status TASK_ID
Cancel tasknpx claude-flow task cancel TASK_ID

Memory Commands

ActionCommand
Storenpx claude-flow memory store --key "key" --value "value" --namespace patterns
Searchnpx claude-flow memory search --query "search terms"
Listnpx claude-flow memory list --namespace patterns
Retrievenpx claude-flow memory retrieve --key "key"

🚀 SWARM RECIPES

Recipe 1: Hello World Test (COMPLETE EXAMPLE)

Step 1: Setup coordination (returns instantly - don't stop!)

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)

# ✅ 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)

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)

# 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)

# 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)

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)

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)

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)

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

DirectoryPurpose
/srcSource code
/testsTest files
/docsDocumentation
/configConfiguration
/scriptsUtility 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

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

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

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

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

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

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

TopologyUse CaseCommand Flag
hierarchicalCoordinated teams, anti-drift--topology hierarchical
meshPeer-to-peer, equal agents--topology mesh
hierarchical-meshHybrid (recommended for V3)--topology hierarchical-mesh
ringSequential processing--topology ring
starCentral coordinator--topology star
adaptiveDynamic 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

CLAUDE_FLOW_CONFIG=./claude-flow.config.json
CLAUDE_FLOW_LOG_LEVEL=info
CLAUDE_FLOW_MEMORY_BACKEND=hybrid

🔗 SKILLS

Invoke with $skill-name:

SkillPurpose
$swarm-orchestrationMulti-agent coordination
$memory-managementPattern storage/retrieval
$sparc-methodologyStructured development
$security-auditSecurity scanning
$performance-analysisProfiling
$github-automationCI/CD management
$hive-mindByzantine consensus
$neural-trainingPattern 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.

# 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

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

MCP Tools Available

Once added, Codex can use these tools via MCP:

Coordination:

ToolPurpose
swarm_initInitialize swarm (topology, maxAgents)
swarm_statusCheck swarm state
agent_spawnRegister agent roles
agent_statusCheck agent state
task_orchestrateCoordinate multi-agent tasks

Learning & Memory (USE THESE!):

ToolPurposeWhen
memory_searchSemantic vector searchBEFORE every task
memory_storeStore patterns with embeddingsAFTER success
memory_retrieveGet by exact keyWhen key is known
neural_trainTrain on patternsPeriodic improvement
neural_statusCheck learning stateDebugging

Hive Mind (Advanced):

ToolPurpose
hive-mind_initByzantine consensus swarm
hive-mind_spawnSpawn hive workers
hive-mind_broadcastMessage 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

ToolPurposeWhen to Use
memory_searchFind similar past patternsBEFORE starting any task
memory_storeSave successful patternsAFTER completing a task
memory_retrieveGet specific pattern by keyWhen you know the exact key
neural_trainTrain on successful patternsAfter 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)

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

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

📚 SUPPORT

Remember: Codex executes, claude-flow orchestrates!

Download now (ZIP)

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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.