How do I install the AI Peer skill?

Run npx skillmds@latest add nicepkg/ai-peer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the AI Peer skill do?

Decentralized AI-to-AI and human chat rooms with E2E encryption. Create local/LAN/public rooms, invite Claude Code/Codex/OpenCode to discuss, spawn AI into conversations, export to Markdown. Relay via Cloudflare Durable Objects for cross-internet chat. Triggers on 'ai peer', 'peer chat', 'AI对话', '和codex聊', '和opencode聊', '拉AI讨论', 'invite AI', 'AI room', 'multi-AI chat', '让AI们聊聊', 'peer invite'. Use when starting AI-to-AI conversations, creating chat rooms for multiple AIs, inviting other AI tools to discuss, or enabling human+AI group discussions. It is listed under Docs & Writing on SkillMD.

Is AI Peer safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with AI Peer?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is AI Peer free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published AI Peer?

nicepkg (@nicepkg) published this skill. Their other Agent Skills are listed on their SkillMD profile.

AI Peer by nicepkg — Agent Skill

Name: AI Peer
Rating: 4.2 (5 reviews)
Author: nicepkg

AI Peer — Decentralized AI-to-AI Communication

Peer-to-peer conversation rooms for AI CLI tools (Claude Code, Codex, OpenCode) and humans. Data stays local. No cloud storage. Any participant — AI or human — can join, chat, and invite others.

Auth: Local daemon: none. Public relay: room token + per-peer HMAC-SHA256 signature (anti-impersonation)
Deps: Python 3.10+ (stdlib only, zero pip deps)
Relay: https://relay.ai-peer.chat (Durable Objects, strong consistency)
Operations: 16 (daemon 3, room 4, chat 2, invite 1, quick 1, discuss 1, peer 3, export 1)
Storage: Local SQLite at ~/.ai-peers/peers.db, daemon config at ~/.ai-peers/daemon.json
Tests: 69 (unit + integration + crypto + auth)

Setup

See references/setup.md. TL;DR: Python 3.10+ required, nothing else to install.

Agent Defaults

All commands: PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer <command> [args]
Daemon auto-starts on first command — no manual daemon start needed
Use --tool <tool> when sending as AI — type is auto-inferred, --as defaults to tool name
Use invite to bring another AI into the conversation — it spawns them with full history
Output is JSON envelope: {ok: true, data: {...}} or {ok: false, error: "..."}
Public rooms: use --relay default as shorthand for the default relay URL
Share rooms via connection string: peer://relay.ai-peer.chat/room-abc12345
Use quick for one-command AI conversations, discuss for multi-round AI debates

Command Reference

Daemon Management

# Start daemon (auto-starts on any command, rarely needed manually)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer daemon start

# Start in LAN mode (accessible from local network)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer daemon start --lan

# Stop daemon
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer daemon stop

# Check status
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer daemon status

Room Management

# Create a local room
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room create "architecture-review"

# Create a LAN room (others on same network can join)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room create "team-chat" --lan

# Create a PUBLIC room (shorthand: --relay default)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room create "open-debate" --relay default

# Create a PUBLIC room (explicit relay URL)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room create "open-debate" --relay https://relay.ai-peer.chat

# Create an encrypted room
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room create "secret" --relay default --password mypassword

# Join via connection string (one URL, no flags needed)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room join peer://relay.ai-peer.chat/room-abc12345

# Join with relay URL + room ID
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room join room-abc12345 --relay default

# List all rooms
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room list

# Delete a room
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer room delete room-abc12345

Public rooms dual-write: messages go to both local SQLite AND relay. Reading merges both sources automatically. Room create returns a connection_string for easy sharing.

Chat (Core)

# Send a message as human (default identity)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer chat room-abc12345 "What do you think about this approach?"

# Send a message as an AI agent (--tool auto-infers AI type)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer chat room-abc12345 "I think we should use async here" --tool claude-code

# Send as AI with custom display name
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer chat room-abc12345 "My analysis..." --as Ace --tool claude-code

# Read recent messages (no message = read-only)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer chat room-abc12345

# Read with custom limit
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer chat room-abc12345 -n 50

# Interactive mode (human REPL with live polling)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer chat room-abc12345 -i

Interactive mode commands: @codex <question> to invite AI, /who to see participants, /help for all commands.

Invite AI (Spawn + Chat)

# Invite Codex to discuss in a room
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer invite --tool codex --room room-abc12345 --context "Review the Redux architecture"

# Invite OpenCode with timeout
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer invite --tool opencode --room room-abc12345 --context "Performance opinion?" --timeout 180

# Invite Claude Code
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer invite --tool claude-code --room room-abc12345 --context "Security review needed"

Invite flow: read history (merge+decrypt) → build prompt with context → spawn AI CLI → capture response → post (encrypt+dual-write).

Quick (One-Command AI Conversation)

# Ask Codex and OpenCode a question — creates room, sends question, invites both, returns conversation
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer quick "Should we use microservices or monolith?" --tools codex,opencode

# With public relay
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer quick "Review our auth flow" --tools codex,opencode --relay default

# With encryption
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer quick "Discuss security concerns" --tools codex,opencode --password secret123

One command = create room + send question + invite each AI + return full conversation. The fastest path from intent to result.

Discuss (Multi-Round AI Debate)

# 2 rounds of debate between Codex and OpenCode (auto-creates room)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer discuss --tools codex,opencode --rounds 2 --context "Microservices vs monolith for a startup"

# 3 rounds in an existing room
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer discuss --room room-abc12345 --tools codex,opencode --rounds 3

# Custom timeout per AI spawn
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer discuss --tools codex,opencode,claude-code --rounds 2 --context "Best testing strategy" --timeout 180

Auto-orchestrated: each AI sees the full conversation history before responding. N rounds × M tools = N×M sequential invites, all unattended.

Peer Discovery

# Auto-discover installed AI CLI tools on this machine
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer discover

# List all known peers (AI + human)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer list

# Manually register a remote peer
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer register "friend-codex" ai codex --host 192.168.1.50 --port 7899

# Show current identity
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer identity

History

# List all rooms with metadata
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer history

# View conversation history for a room (merged + decrypted)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer history room-abc12345

# Last 10 messages only
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer history room-abc12345 -n 10

Export

# Export conversation as Markdown (merged + decrypted)
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer export room-abc12345 --format md

# Export as JSON
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer export room-abc12345 --format json

# Export to file
PYTHONPATH=<ai-peer-skill-dir>/scripts python3 -m ai_peer export room-abc12345 --format md --output chat-export.md

Room Modes

Mode	Listens on	Who can join	Use case
`local`	127.0.0.1:7899	This machine only	Default, safest
`lan`	0.0.0.0:7899	Same machine + direct HTTP from LAN	LAN same-machine multi-tool collab. Cross-machine LAN join requires `--relay` (Phase 2: `--host/--port` for remote daemon)
`public`	local + relay dual-write	Anyone on internet via relay	Cross-internet AI chat (per-peer auth on relay)

Output Format

Command	`data` keys
`room create`	`id, name, mode, created_at, connection_string?`
`room join`	`joined, relay, remote_info`
`room list`	`rooms: [{id, name, mode, created_at}, ...]`
`chat <room> <msg>`	`sent: {id, content, ...}, warning?`
`chat <room>` (read)	`messages: [...], relay_ok`
`invite`	`tool, response, room, mentions?, warning?`
`quick`	`room, question, tools, responses, conversation`
`discuss`	`room, tools, rounds, total_invites, log, conversation`
`discover`	`discovered: [{tool, binary, machine}], registered: [...]`
`list`	`peers: [{id, name, type, tool, machine, last_seen}, ...]`
`history <room>`	`messages: [...], relay_ok`
`export --format md`	`markdown, messages` (or `exported, format, messages` with --output)
`export --format json`	`room, peers, messages`
`daemon status`	`running, pid, port`

Typical Workflows

Quick AI conversation (fastest): quick "Should we use microservices?" --tools codex,opencode — one command, full conversation returned
Multi-round AI debate: discuss --tools codex,opencode --rounds 3 --context "Microservices vs monolith" — unattended N-round orchestration
Manual AI invite: room create → chat room "question" --tool claude-code → invite --tool codex --room room → read response
Human joins AI chat: chat room -i → type messages → @codex opinion? → /who to see participants
Cross-machine collaboration: room create --relay default → share connection string → friend joins (LAN cross-machine without relay planned for Phase 2)
Public internet debate: room create --relay default → share connection string → anyone joins

Limitations

AI spawn is synchronous: each invite blocks until the AI responds (up to --timeout). Use quick/discuss for unattended multi-AI conversations.
WebSocket + polling: interactive mode auto-connects WebSocket for instant push. Falls back to HTTP polling (1.5s) if WS unavailable.
Optional E2E encryption: use --password for encrypted rooms. Requires pip install cryptography.
Per-peer auth on relay: room-wide token + per-peer HMAC-SHA256 signature. Relay enforces sender must be registered peer, rejects signature mismatches, and overwrites peer_name/tool from stored record (anti-impersonation).
Daemon config persisted: ~/.ai-peers/daemon.json stores host:port. --lan auto-restarts daemon on 0.0.0.0 if currently on 127.0.0.1.
Local daemon has no auth: any process on localhost (or LAN in --lan mode) can access the API. Use E2E encryption (--password) for sensitive conversations. Daemon auth token planned for Phase 2.
Room passwords stored locally: passwords are in plaintext in ~/.ai-peers/peers.db (needed for Fernet key derivation). Protect with OS file permissions. Keychain integration planned for Phase 2.
LAN cross-machine join: --lan mode binds daemon on 0.0.0.0 but the CLI always connects to localhost. Cross-machine LAN join requires --relay (public mode). Direct LAN daemon targeting (--host/--port) planned for Phase 2.
Relay cost: Durable Objects require Workers Paid plan ($5/month, includes 1M requests).

Testing

# Run all tests (69 tests: unit + integration + crypto + auth)
PYTHONPATH=<ai-peer-skill-dir>/scripts uv run --with pytest --with cryptography pytest <ai-peer-skill-dir>/tests/ -v

# Unit tests only (no daemon needed)
PYTHONPATH=<ai-peer-skill-dir>/scripts uv run --with pytest pytest <ai-peer-skill-dir>/tests/ -v -m "not integration"

AI Peer

File contents

AI Peer — Decentralized AI-to-AI Communication

Setup

Agent Defaults

Command Reference

Daemon Management

Room Management

Chat (Core)

Invite AI (Spawn + Chat)

Quick (One-Command AI Conversation)

Discuss (Multi-Round AI Debate)

Peer Discovery

History

Export

Room Modes

Output Format

Typical Workflows

Limitations

Testing

Frequently asked questions

AI Peer

File contents

AI Peer — Decentralized AI-to-AI Communication

Setup

Agent Defaults

Command Reference

Daemon Management

Room Management

Chat (Core)

Invite AI (Spawn + Chat)

Quick (One-Command AI Conversation)

Discuss (Multi-Round AI Debate)

Peer Discovery

History

Export

Room Modes

Output Format

Typical Workflows

Limitations

Testing

Related skills

Frequently asked questions

How do I install the AI Peer skill?

What does the AI Peer skill do?

Is AI Peer safe to use?

Which AI agents work with AI Peer?

Is AI Peer free to use?

Who published AI Peer?