name: 5FAN description: Five Brains Agentic Network — emotional intelligence skill for Intercom. Five brains (Hear, Inspyre, Flow, You, View) scan emotion, track habits, reflect identity, reconnect purpose, and curate perspective. Runs local-first on P2P via Trac Network. Other agents invoke individual brains or the full swarm over sidechannels. Built for character-driven brands, wellness apps, recovery platforms, kids products, and communities where how you talk to the user matters. trac_address: trac1wtsn8ru2ryknk36rd6glp2tfj0dawnh2gkjrg90gzqvwes65v78qmwjuzq

5FAN

Description

5FAN (Five Brains Agentic Network) is a skill for autonomous agents on Trac Network's Intercom. It adds emotional intelligence to any app — five specialized brains scan every message in parallel, a consensus pipeline synthesizes their insights, and an LLM (or template fallback) generates a response that makes the user feel seen.

5FAN runs on top of Intercom. For P2P networking, sidechannels, SC-Bridge, contracts, and wallet details, refer to the Intercom SKILL.md (https://github.com/Trac-Systems/intercom/blob/main/SKILL.md). This document covers only 5FAN-specific setup, configuration, and operation.

Support

References:

• Repository: https://github.com/joeatang/5FAN
• Architecture: see ARCHITECTURE.md in this repo
• Intercom (base layer): https://github.com/Trac-Systems/intercom
• Intercom SKILL.md (P2P networking guide): https://github.com/Trac-Systems/intercom/blob/main/SKILL.md
• Issues: https://github.com/joeatang/5FAN/issues

Quick Reference

• Trac Address: trac1wtsn8ru2ryknk36rd6glp2tfj0dawnh2gkjrg90gzqvwes65v78qmwjuzq
• Entry Channel: 0000intercom
• Skill Channels: 5fan-skill-hear, 5fan-skill-inspyre, 5fan-skill-flow, 5fan-skill-you, 5fan-skill-view, 5fan-skill-swarm
• Discovery Channel: 5fan-skills (manifest broadcast every 5 min)
• Brains: Hear (emotion), Inspyre (values), Flow (habits), You (identity), View (synthesis)
• LLM Fallback Chain: Local (LM Studio/Ollama) → Cloud (Groq/OpenRouter/Together.ai) → Templates (200+ per brain, always works)

Dependency on Intercom

5FAN is an Intercom app. It requires a running Intercom peer to function. Do not try to run 5FAN with native Node — use Pear runtime only, as specified in the Intercom SKILL.md.

Before setting up 5FAN, the agent must have access to the Intercom SKILL.md for:

• Pear runtime installation and Node version requirements (22.x or 23.x, avoid 24.x)
• Peer startup flags (--peer-store-name, --msb-store-name, --subnet-channel, --subnet-bootstrap, --dht-bootstrap)
• SC-Bridge setup (WebSocket auth, token generation, JSON commands)
• Sidechannel policy (welcome, owner, invites, PoW)
• Wallet and keypair handling

If the human has not provided the Intercom SKILL.md, ask them to share it or fetch it from https://raw.githubusercontent.com/Trac-Systems/intercom/main/SKILL.md.

Prerequisites

Required (handled by Intercom SKILL.md)

1. Node.js 22.x or 23.x (avoid 24.x)
2. Pear Runtime (npm install -g pear && pear -v)

Required (5FAN-specific)

1. Clone and install 5FAN:

git clone https://github.com/joeatang/5FAN.git
cd 5FAN
npm install

Optional — Local LLM (recommended)

1. LM Studio (default, localhost:1234):

   • Download from https://lmstudio.ai/
   • Load any model and start the server
   • Verify: curl -s http://localhost:1234/v1/models | head -5

2. Ollama (alternative, localhost:11434):

ollama pull llama3.2:3b
ollama serve

Optional — Cloud LLM

1. API Key from Groq, OpenRouter, or Together.ai:

export FIVEFAN_LM_KEY=your_api_key
export FIVEFAN_LM_CLOUD_URL=https://api.groq.com/openai
export FIVEFAN_LM_CLOUD_MODEL=llama-3.3-70b-versatile

Important: 5FAN works without any LLM. Template fallback (200+ templates per brain) always responds. The LLM adds depth but is not required.

Running 5FAN

Use Pear runtime only (never native node). All Intercom peer flags apply — refer to the Intercom SKILL.md for the full flag reference.

Start Admin Peer

pear run . --peer-store-name admin --msb-store-name admin-msb --dht-bootstrap "node1.hyperdht.org:49737,node2.hyperdht.org:49737"

Start Joiner Peer

pear run . --peer-store-name peer2 --msb-store-name peer2-msb --dht-bootstrap "node1.hyperdht.org:49737,node2.hyperdht.org:49737" --subnet-bootstrap <admin-writer-key-hex>

The admin's writer key (hex) is printed in the startup banner. Copy it for joiners.

Join Entry Channel + Send Message

In the TTY (human fallback only):

join 0000intercom
send Hello, 5FAN!

All five brains scan the message. View curates consensus. LLM (or template) generates a response.

Agent Quick Start (SC-Bridge)

Autonomous agents must use SC-Bridge for all I/O — same as Intercom. See Intercom SKILL.md → "Agent Quick Start (SC‑Bridge Required)" for auth flow.

Once authenticated, send messages via WebSocket:

{ "type": "send", "channel": "0000intercom", "message": "Hello, 5FAN!" }

To invoke a specific brain skill:

{ "type": "join", "channel": "5fan-skill-hear" }
{ "type": "send", "channel": "5fan-skill-hear", "message": "{\"type\":\"skill:call\",\"skill\":\"hear\",\"callId\":\"001\",\"payload\":{\"text\":\"I feel lost today\"}}" }

The Five Brains

Consensus Pipeline

User Message
    │
    ├─→ Hear.scan()    ─→ { signal: 0.7, emotions: ['frustration'], category: 'pain' }
    ├─→ Inspyre.scan() ─→ { signal: 0.4, themes: ['growth'] }
    ├─→ Flow.scan()    ─→ { signal: 0.2, category: 'recovery' }
    ├─→ You.scan()     ─→ { signal: 0.3, markers: ['self-reflection'] }
    └─→ View.scan()    ─→ { signal: 0.5, category: 'perspective' }
                           │
              View.curateConsensus()
                           │
                           ▼
           { dominantBrain: 'hear',
             synthesisPrompt: '...',
             activeBrainCount: 4 }
                           │
                    ┌──────┴──────┐
                    │  LM Bridge  │
                    │ local→cloud │
                    │  →template  │
                    └──────┬──────┘
                           │
                           ▼
                  Broadcast response

Crisis override: if Hear detects crisis signals (suicidal ideation, self-harm), ALL other brain processing is overridden. Crisis response is deterministic (hardcoded keywords → immediate hotline resources). No LLM delay. Non-negotiable.

Skill Invocation Protocol

Every brain is an invocable skill on Intercom. Any agent on the network can invoke a single brain or the full 5-brain swarm over P2P sidechannels — no REST, no API keys, no cloud functions.

Channels

Message Types

Invoke a Single Brain

// Join the Hear skill channel
sidechannel.join('5fan-skill-hear');

// Send a skill:call
sidechannel.send('5fan-skill-hear', JSON.stringify({
  type: 'skill:call',
  skill: 'hear',
  callId: 'my-unique-id',
  payload: {
    text: 'I feel so alone today. Nobody checks in on me.',
    context: { userId: 'user123' }
  }
}));

// Listen for skill:result
sidechannel.on('5fan-skill-hear', (msg) => {
  const data = JSON.parse(msg);
  if (data.type === 'skill:result' && data.callId === 'my-unique-id') {
    console.log(data.result);
    // {
    //   signal: 0.85,
    //   category: 'pain',
    //   emotions: ['alone', 'lonely'],
    //   isCrisis: false,
    //   response: "That loneliness you're feeling — it's real.
    //              You don't have to carry it alone."
    // }
  }
});

Invoke the Full Swarm

All 5 brains scan → View curates consensus → LLM enriches:

sidechannel.join('5fan-skill-swarm');

sidechannel.send('5fan-skill-swarm', JSON.stringify({
  type: 'skill:call',
  skill: '5fan-swarm',
  callId: 'swarm-001',
  payload: {
    text: 'I keep quitting everything I start. What is wrong with me?',
    context: { userId: 'user456' }
  }
}));
// skill:result includes all 5 brain scans + dominant brain + LLM response

Chain Brains

Chain multiple brains in sequence — each brain's output feeds the next, with View synthesizing at the end:

sidechannel.send('5fan-skill-swarm', JSON.stringify({
  type: 'skill:chain',
  callId: 'chain-001',
  chain: ['hear', 'inspyre', 'view'],
  payload: { text: 'I want to give up on my business.' }
}));
// skill:chain-result returns each brain's result + View synthesis

Skill Manifests

Each brain has a skill.json in brains/<name>/skill.json — machine-readable:

{
  "skill": "hear",
  "encodes": "Emotional intelligence — a wise friend who listens without prescribing.",
  "domain": "Emotion detection, validation, and mirroring.",
  "tagline": "Your app does the job. Hear makes the user feel heard.",
  "accepts": { "text": "string (required)", "context": "object (optional)" },
  "returns": { "signal": "0-1", "category": "pain|joy|mixed|crisis|neutral", "response": "string" },
  "whenToUse": ["User expresses emotion", "Before delivering domain-specific advice"],
  "chainsWith": ["inspyre", "flow", "view", "5fan-swarm"]
}

Rate Limiting and Discovery

• Rate limit: 30 invocations per minute per channel per caller. Exceeded callers receive skill:error with code RATE_LIMITED.
• Discovery: join 5fan-skills to receive periodic manifest broadcasts (every 5 min). Or send skill:describe on any brain's skill channel to request its manifest on demand.

Configuration

config.js (master config)

FIVE_FAN: {
  enabled: true,              // Kill switch — false disables all 5FAN responses
  lm: {
    provider: 'auto',         // 'auto' | 'local' | 'cloud'
    host: '127.0.0.1',
    port: 1234,               // LM Studio default (Ollama: 11434)
    model: 'gemma-3-4b',      // Change to your loaded model
    cloudUrl: 'https://api.groq.com/openai',
    cloudModel: 'llama-3.3-70b-versatile',
    cloudApiKey: '',           // or set FIVEFAN_LM_KEY env var
    maxTokens: 200,
    temperature: 0.7,
  },
  features: {
    feedReplies:   true,      // Auto-reply to community posts
    trainer:       true,      // 1:1 conversation mode
    nudges:        true,      // Contextual nudges in responses
    proactive:     true,      // Scheduled community posts
    crossBrain:    true,      // Multi-brain consensus analysis
    userProfiling: true,      // Per-user word-frequency profiling
  },
  timezone: 'America/Los_Angeles',
}

Important: crossBrain: true must stay enabled for crisis detection to work. Hear's crisis scanner runs on every message only when crossBrain is on.

app-context.js (personality + system prompt)

This is the base system prompt that defines who 5FAN is. It gets enriched by brain-swarm.js's buildEnrichedPrompt() before being sent to the LLM.

• Customize: identity, app description, domain, brain names/descriptions, guided exercises
• Keep: core principles, crisis protocol, response framework, anti-patterns

When forking (see below), this is the primary file that changes the agent's personality.

LLM Provider Priority

All providers use the OpenAI Chat Completions API format. The system prompt is enriched with brain consensus analysis before being sent to any LLM.

File Structure

5FAN/
├── brains/
│   ├── 5fan.js              # Shared constants + helpers
│   ├── hear/                # Emotion scanning
│   │   ├── roleConfig.js    # Personality, keywords, templates (CUSTOMIZE)
│   │   ├── functions.js     # scan(), fulfill(), log() (KEEP)
│   │   ├── index.js         # shouldRespond(), handleMessage() (KEEP)
│   │   └── skill.json       # Agent-readable skill manifest (CUSTOMIZE)
│   ├── inspyre/             # Values alignment (same structure)
│   ├── flow/                # Habit tracking (same structure)
│   ├── you/                 # User profiling (same structure)
│   └── view/                # Consensus curation (+ curateConsensus)
│       └── skill.json
├── server/
│   ├── brain-swarm.js       # Parallel scan engine (KEEP)
│   ├── lm-bridge.js         # Multi-provider LLM bridge (KEEP)
│   ├── skill-server.js      # Skill invocation listener — P2P sidechannels (KEEP)
│   ├── feed-responder.js    # Community auto-reply (KEEP)
│   ├── proactive-scheduler.js # Scheduled posts (KEEP)
│   ├── trainer-api.js       # 1:1 conversation manager (KEEP)
│   └── routes.js            # Express REST API (KEEP)
├── skill-protocol.js        # Skill message types + channel naming + registry (KEEP)
├── config.js                # Feature flags + LLM config (CUSTOMIZE)
├── app-context.js           # System prompt identity (CUSTOMIZE)
├── user-profile.js          # Onboarding + profiles (KEEP)
├── intercom-swarm.js        # P2P brain swarm routing (KEEP)
├── lm-local.js              # Local LLM adapter (KEEP)
├── lm-cloud.js              # Cloud LLM adapter (KEEP)
├── index.js                 # Main Intercom entry point (KEEP)
├── ARCHITECTURE.md          # Detailed architecture diagrams
├── README.md                # Project overview + positioning
└── SKILL.md                 # This file

Typical Requests and How to Respond

When a human asks for something, translate it into the minimal set of actions. Ask for any missing details.

"Set up 5FAN." Pre-check: is the Intercom SKILL.md available in context? If not, ask the human to provide it. Answer: follow Prerequisites above (Node 22+, Pear, clone, npm install). Then start admin peer with Pear. If the human wants a local LLM: install LM Studio or Ollama first. If no LLM: 5FAN still works — template fallback is automatic.

"Fork 5FAN for my brand." Ask for: brand name, personality description, what the community is about, any specific trigger words. Answer: change 4 files:

Do not touch: brain-swarm.js, lm-bridge.js, skill-server.js, skill-protocol.js, intercom-swarm.js, trainer-api.js, feed-responder.js, proactive-scheduler.js, lm-local.js, lm-cloud.js, or any functions.js/index.js inside brains. These are the engine — they work regardless of personality.

"Add a new brain." Ask for: brain name, domain, what it scans for, template responses. Answer:

1. Create brains/<name>/ with: roleConfig.js, functions.js, index.js, skill.json
2. Register in brains/5fan.js → BRAINS constant
3. Register in skill-protocol.js → SKILL_REGISTRY
4. Import in server/brain-swarm.js → add to scan array View's curateConsensus() automatically incorporates new brain signals.

"Change the LLM provider." Ask for: which provider (local, cloud, or auto), model name, API key if cloud. Answer: edit config.js → FIVE_FAN.lm:

• Local only: provider: 'local', set port (1234 for LM Studio, 11434 for Ollama)
• Cloud only: provider: 'cloud', set cloudUrl, cloudModel, cloudApiKey
• Auto (recommended): provider: 'auto' — tries local → cloud → template

"Why is 5FAN not responding?" Checklist:

1. Is FIVE_FAN.enabled set to true in config.js?
2. Is crossBrain: true in config.js? (required for the brain swarm to scan)
3. Is the Intercom peer running? (check TTY or { "type": "stats" } via SC-Bridge)
4. Are both peers using the same --dht-bootstrap flags?
5. Is the LLM running? (curl -s http://localhost:1234/v1/models). If not, 5FAN still works in template mode — check for template-formatted responses.

"Invoke 5FAN from my agent." Answer: your agent needs a running Intercom peer with SC-Bridge enabled (see Intercom SKILL.md). Then:

1. Join a 5FAN skill channel: { "type": "join", "channel": "5fan-skill-hear" }
2. Send skill:call as the message payload
3. Listen for skill:result on the same channel For the full swarm: join 5fan-skill-swarm instead. For discovery: join 5fan-skills and listen for skill:manifest broadcasts.

"What brains are available?" Answer: 5 brains — Hear (emotion), Inspyre (values), Flow (habits), You (identity), View (synthesis). Each has a dedicated skill channel. The full swarm (5fan-skill-swarm) runs all 5 + consensus + LLM. Read brains/<name>/skill.json for detailed manifests.

Agent Control Surface

• Autonomous agents must use SC-Bridge for all I/O (same as Intercom).
• Do not use the interactive TTY unless a human explicitly requests it.
• Template mode is always available — do not claim 5FAN requires an LLM to function.
• Crisis detection is deterministic — Hear's keyword scanner fires before any LLM processing. Do not modify crisis keywords without explicit human approval.
• Do not generate new wallet keys for 5FAN. Use the peer wallet from stores/<peer-store-name>/db/keypair.json (see Intercom SKILL.md → Wallet Usage).

Output Contract (Agents Must Follow)

• When generating startup commands, print fully-expanded, copy-paste-safe commands (no unresolved placeholders).
• When showing config changes, show the exact lines to change in config.js or app-context.js.
• When forking for a brand, generate complete file contents for roleConfig.js and skill.json — not partial snippets.
• If the human asks to run 5FAN and no Intercom peer is running, generate a run script with the correct Pear flags and tell the human to execute it.

Troubleshooting

Peers don't see each other Both must use identical --dht-bootstrap flags. See Intercom SKILL.md → Configuration Flags.

Lock file errors

pkill -9 -f pear-runtime
cd ~/5FAN
find stores -name "LOCK" -delete

LLM not detected

curl -s http://localhost:1234/v1/models | head -5
curl -s http://localhost:11434/api/tags | head -5

Template mode works without any LLM — the agent always responds.

First LLM response is slow Normal — local models load into memory on first request. Subsequent responses: 1–3 seconds.

Crisis hotline not showing Ensure crossBrain: true in config so Hear always runs. Crisis response bypasses LLM entirely.

skill:call returns no response

1. Is the 5FAN peer running and joined to the skill channel?
2. Is skill-server.js initialized? (check startup logs for "Skill server started")
3. Is the calling agent on the same DHT bootstrap?
4. Rate limit: 30/min/channel/caller. Check for RATE_LIMITED errors.

Notes

• 5FAN must run via Pear runtime (never native node).
• All agent communication flows through the Trac Network / Intercom stack.
• The Intercom peer must stay running — closing the terminal stops networking.
• app-context.js is the system prompt, not the agent logic. The brains are the logic.
• View's curateConsensus() is the core of 5FAN — it decides which brain leads each response.

Version: 2.0.0 License: Apache-2.0