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

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The file

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

11 rules. About 1 is common, 6 are distinctive, and 4 are very specific to this project.

  • ≈1

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈6

    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. Distinctive:

    Do what is asked; nothing more, nothing less

    line 309
  2. Distinctive:

    NEVER create files unless absolutely necessary

    line 310
  3. Distinctive:

    ALWAYS prefer editing existing files

    line 311
  4. Distinctive:

    NEVER save to root folder

    line 312
  5. Common:

    NEVER commit secrets or .env files

    line 313
  6. Distinctive:

    ALWAYS read a file before editing it

    line 314
  7. Very specific:

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

    line 315
  8. Very specific:

    Use fidgetflo commands to TRACK progress, not to EXECUTE tasks

    line 316
  9. Very specific:

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

    line 482
  10. Distinctive:

    Use MCP tools directly - faster than CLI commands:

    line 532
  11. Very specific:

    When fidgetflo is added as MCP server, Codex can call tools directly:

    line 612

≈ “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

FidgetFlo V3 - Agent Guide

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


📢 TL;DR - READ THIS FIRST

╔═══════════════════════════════════════════════════════════════════════════╗
║  1. fidgetflo = LEDGER (tracks state, stores memory, coordinates)       ║
║  2. Codex = EXECUTOR (writes code, runs commands, creates files)          ║
║  3. NEVER stop after calling fidgetflo - IMMEDIATELY continue working   ║
║  4. If you need something BUILT/EXECUTED, YOU do it, not fidgetflo      ║
║  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

🚨 CRITICAL: CODEX DOES THE WORK, FIDGETFLO ORCHESTRATES

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

❌ WRONG: Expecting fidgetflo to execute tasks

npx fidgetflo swarm start --objective "Build API"
# WRONG: Waiting for fidgetflo to build the API
# Claude-flow does NOT execute code!

✅ CORRECT: Codex executes, fidgetflo tracks

# 1. Tell fidgetflo what you're doing (optional coordination)
npx fidgetflo swarm init --topology hierarchical --max-agents 1
npx fidgetflo 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 fidgetflo what you did (optional)
npx fidgetflo memory store --key "api-created" --value "src/api.ts" --namespace results

The Division of Labor

ComponentRoleExamples
CODEXEXECUTESWrite files, run tests, create code, shell commands
fidgetfloORCHESTRATESTrack agents, store memory, coordinate tasks

⛔ DON'T STOP AFTER CALLING FIDGETFLO

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

❌ WRONG Pattern (Stopping)

npx fidgetflo swarm init --topology hierarchical
npx fidgetflo agent spawn --type coder --name worker-1
npx fidgetflo 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 fidgetflo swarm init --topology hierarchical
npx fidgetflo 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 fidgetflo memory store --key "result" --value "Hello World printed" --namespace results

The Rule

After ANY fidgetflo 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 FidgetFlo Commands

Use CaseFidgetFlo 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 fidgetflo 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 fidgetflo 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 fidgetflo swarm init --topology hierarchical --max-agents 8
npx fidgetflo agent spawn --type coordinator --name coord-1
npx fidgetflo agent spawn --type coder --name coder-1
npx fidgetflo agent spawn --type coder --name coder-2
npx fidgetflo agent spawn --type tester --name tester-1
npx fidgetflo agent spawn --type reviewer --name reviewer-1
npx fidgetflo swarm start --objective "Your task here" --strategy development

Common Swarm Patterns

TaskExact Command
Init hierarchical swarmnpx fidgetflo swarm init --topology hierarchical --max-agents 8
Init mesh swarmnpx fidgetflo swarm init --topology mesh --max-agents 5
Init V3 mode (15 agents)npx fidgetflo swarm init --v3-mode
Spawn codernpx fidgetflo agent spawn --type coder --name coder-1
Spawn testernpx fidgetflo agent spawn --type tester --name tester-1
Spawn coordinatornpx fidgetflo agent spawn --type coordinator --name coord-1
Spawn architectnpx fidgetflo agent spawn --type architect --name arch-1
Spawn reviewernpx fidgetflo agent spawn --type reviewer --name rev-1
Spawn researchernpx fidgetflo agent spawn --type researcher --name res-1
Start swarmnpx fidgetflo swarm start --objective "task" --strategy development
Check swarm statusnpx fidgetflo swarm status
List agentsnpx fidgetflo agent list
Stop swarmnpx fidgetflo 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 fidgetflo task create --type implementation --description "desc"
List tasksnpx fidgetflo task list
Assign tasknpx fidgetflo task assign TASK_ID --agent AGENT_NAME
Task statusnpx fidgetflo task status TASK_ID
Cancel tasknpx fidgetflo task cancel TASK_ID

Memory Commands

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

🚀 SWARM RECIPES

Recipe 1: Hello World Test (COMPLETE EXAMPLE)

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

npx fidgetflo swarm init --topology mesh --max-agents 5
npx fidgetflo 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 fidgetflo 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 fidgetflo swarm init --topology hierarchical --max-agents 5
for i in 1 2 3 4 5; do
  npx fidgetflo 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 fidgetflo memory store --key "concurrent-result" --value "5 workers completed" --namespace results

Recipe 1b: Hello World (Single Command Block)

# All-in-one execution
npx fidgetflo swarm init --topology mesh --max-agents 5 && \
npx fidgetflo agent spawn --type coder --name hello-main && \
npx fidgetflo 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 fidgetflo memory store --key "hello-world-result" --value "Success" --namespace results

Recipe 2: Feature Implementation (6 Agents)

npx fidgetflo swarm init --topology hierarchical --max-agents 8
npx fidgetflo agent spawn --type coordinator --name lead
npx fidgetflo agent spawn --type architect --name arch
npx fidgetflo agent spawn --type coder --name impl-1
npx fidgetflo agent spawn --type coder --name impl-2
npx fidgetflo agent spawn --type tester --name test
npx fidgetflo agent spawn --type reviewer --name review
npx fidgetflo swarm start --objective "Implement [feature]" --strategy development

Recipe 3: Bug Fix (4 Agents)

npx fidgetflo swarm init --topology hierarchical --max-agents 4
npx fidgetflo agent spawn --type coordinator --name lead
npx fidgetflo agent spawn --type researcher --name debug
npx fidgetflo agent spawn --type coder --name fix
npx fidgetflo agent spawn --type tester --name verify
npx fidgetflo swarm start --objective "Fix [bug]" --strategy development

Recipe 4: Security Audit (3 Agents)

npx fidgetflo swarm init --topology hierarchical --max-agents 4
npx fidgetflo agent spawn --type coordinator --name lead
npx fidgetflo agent spawn --type security-architect --name audit
npx fidgetflo agent spawn --type reviewer --name review
npx fidgetflo swarm start --objective "Security audit" --strategy development

Recipe 5: V3 Full Coordination (15 Agents)

npx fidgetflo swarm init --v3-mode
npx fidgetflo swarm coordinate --agents 15

📋 BEHAVIORAL RULES

  • YOU (CODEX) execute tasks - fidgetflo 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 fidgetflo to "do work" - it doesn't execute, YOU do
  • Use fidgetflo 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 fidgetflo swarm init [--topology TYPE] [--max-agents N] [--v3-mode]
npx fidgetflo swarm start --objective "task" --strategy [development|research]
npx fidgetflo swarm status [SWARM_ID]
npx fidgetflo swarm stop [SWARM_ID]
npx fidgetflo swarm scale --count N
npx fidgetflo swarm coordinate --agents N

Agent Commands

npx fidgetflo agent spawn --type TYPE --name NAME
npx fidgetflo agent list [--filter active|idle|busy]
npx fidgetflo agent status AGENT_ID
npx fidgetflo agent stop AGENT_ID
npx fidgetflo agent metrics [AGENT_ID]
npx fidgetflo agent health
npx fidgetflo agent logs AGENT_ID

Task Commands

npx fidgetflo task create --type TYPE --description "desc"
npx fidgetflo task list [--all]
npx fidgetflo task status TASK_ID
npx fidgetflo task assign TASK_ID --agent AGENT_NAME
npx fidgetflo task cancel TASK_ID
npx fidgetflo task retry TASK_ID

Memory Commands

npx fidgetflo memory store --key KEY --value VALUE [--namespace NS]
npx fidgetflo memory search --query "terms" [--namespace NS]
npx fidgetflo memory list [--namespace NS]
npx fidgetflo memory retrieve --key KEY [--namespace NS]
npx fidgetflo memory init [--force]

Hooks Commands

npx fidgetflo hooks pre-task --description "task"
npx fidgetflo hooks post-task --task-id ID --success true
npx fidgetflo hooks route --task "task"
npx fidgetflo hooks session-start --session-id ID
npx fidgetflo hooks session-end --export-metrics true
npx fidgetflo hooks worker list
npx fidgetflo hooks worker dispatch --trigger audit

System Commands

npx fidgetflo init [--wizard] [--codex] [--full]
npx fidgetflo daemon start
npx fidgetflo daemon stop
npx fidgetflo daemon status
npx fidgetflo doctor [--fix]
npx fidgetflo status
npx fidgetflo 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

FIDGETFLO_CONFIG=./fidgetflo.config.json
FIDGETFLO_LOG_LEVEL=info
FIDGETFLO_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 fidgetflo init --codex, the MCP server is automatically registered with Codex.

# Verify MCP is registered:
codex mcp list

# Expected output:
# Name         Command  Args                   Status
# fidgetflo  npx      fidgetflo mcp start  enabled

# If not present, add manually:
codex mcp add fidgetflo -- npx fidgetflo mcp start

Test MCP Connection

# Test MCP server starts correctly:
npx fidgetflo 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 fidgetflo memory search --query "keywords" --namespace patterns
npx fidgetflo memory store --key "pattern-x" --value "what worked" --namespace patterns

Coordination via MCP

When fidgetflo 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.fidgetflo]
command = "npx"
args = ["fidgetflo", "mcp", "start"]
enabled = true

📚 SUPPORT

Remember: Codex executes, fidgetflo orchestrates!

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