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Agent Teams

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athola
agent-teams

Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.

Overview

Publisherathola
Repositoryclaude-night-market
Skill nameagent-teams
Stars
343
Forks
37
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by athola on GitHub. Read the source before you install it.

Installation

Install the Agent Teams AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/athola/claude-night-market/tree/master/plugins/conjure/skills/agent-teams
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/athola/claude-night-market.git /tmp/claude-night-market
mkdir -p .claude/skills
cp -r /tmp/claude-night-market/plugins/conjure/skills/agent-teams .claude/skills/agent-teams
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Teams in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Teams on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Teams is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent Teams Coordination

Overview

Claude Code Agent Teams enables multiple Claude CLI processes to collaborate on shared work through a filesystem-based coordination protocol. Each teammate runs as an independent claude process in a tmux pane, communicating via JSON files guarded by fcntl locks, with no database, daemon, or network layer.

This skill provides the patterns for orchestrating agent teams effectively.

When To Use

  • Parallel implementation across multiple files or modules
  • Multi-agent code review (one agent reviews, another implements fixes)
  • Large refactoring requiring coordinated changes across subsystems
  • Tasks with natural parallelism that benefit from concurrent agents

When NOT To Use

  • Single-file changes or small tasks (overhead exceeds benefit)
  • Tasks requiring tight sequential reasoning (agents coordinate loosely)
  • When claude CLI is not available or tmux is not installed

Prerequisites

bash
# Verify Claude Code CLI
claude --version

# Verify tmux (required for split-pane mode)
tmux -V

# Enable experimental feature (set by spawner automatically)
export CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1

Protocol Architecture

~/.claude/
  teams/<team-name>/
    config.json            # Team metadata + member roster
    inboxes/
      <agent-name>.json    # Per-agent message queue
      .lock                # fcntl exclusive lock
  tasks/<team-name>/
    1.json ... N.json      # Auto-incrementing task files
    .lock                  # fcntl exclusive lock

Design principles:

  • Filesystem is the database: JSON files, atomic writes via tempfile + os.replace
  • fcntl locking: Prevents concurrent read/write corruption on inboxes and tasks
  • Numbered tasks: Auto-incrementing IDs with sequential file naming
  • Loose coupling: Agents poll their own inbox; no push notifications

Quick Start

1. Create a Team

bash
# Programmatic team setup (via MCP or direct API)
# Team config written to ~/.claude/teams/<team-name>/config.json

The team config contains:

  • name, description, created_at (ms timestamp)
  • lead_agent_id, lead_session_id
  • members[]: array of LeadMember and TeammateMember objects

2. Spawn Teammates

Each teammate is a separate claude CLI process launched with identity flags:

bash
claude --agent-id "backend@my-team" \
       --agent-name "backend" \
       --team-name "my-team" \
       --agent-color "#FF6B6B" \
       --parent-session-id "$SESSION_ID" \
       --agent-type "general-purpose" \
       --model sonnet

See modules/spawning-patterns.md for tmux pane management and color assignment.

3. Create Tasks with Dependencies

json
{
  "id": "1",
  "subject": "Implement API endpoints",
  "description": "Create REST endpoints for user management",
  "status": "pending",
  "owner": null,
  "blocks": ["3"],
  "blocked_by": [],
  "metadata": {}
}

See modules/task-coordination.md for state machine and dependency management.

4. Coordinate via Messages

json
{
  "from": "team-lead",
  "text": "API endpoints are ready for integration testing",
  "timestamp": "2026-02-07T22:00:00Z",
  "read": false,
  "summary": "API ready"
}

See modules/messaging-protocol.md for message types and inbox operations.

Coordination Workflow

  1. agent-teams:team-created: Initialize team config and directories
  2. agent-teams:teammates-spawned: Launch agents in tmux panes
  3. agent-teams:tasks-assigned: Create tasks with dependencies, assign owners
  4. agent-teams:coordination-active: Agents claim tasks, exchange messages, mark completion
  5. agent-teams:team-shutdown: Graceful shutdown with approval protocol

Crew Roles

Each team member has a role that determines their capabilities and task compatibility. Five roles are defined: implementer (default), researcher, tester, reviewer, and architect. Roles constrain which risk tiers an agent can handle. See modules/crew-roles.md for the full capability matrix and role-risk compatibility table.

Team Formation

For mission-level team sizing, use the Team Formation rules from references/team-formation.md. This defines:

  • Role definitions: Coordinator (mission lead), Agents (task owners), Reviewer (adversarial challenger)
  • Team sizing rules: Simple (1), Moderate (2-4), Complex (5-7), Critical (5-10)
  • Maximum team size: 10 agents (coordination overhead limit)
  • File ownership rules: Prevent conflicts with clear ownership

See references/team-formation.md for full team sizing guidance and example team formations.

Health Monitoring

Team members can be monitored for health via heartbeat messages and claim expiry. The lead polls team health every 60s with a 2-stage stall detection protocol (health_check probe and 30s wait). Stalled agents have their tasks released and are restarted or replaced following the "replace don't wait" doctrine. See modules/health-monitoring.md for the full protocol and state machine.

Module Reference

  • team-management.md: Team lifecycle, config format, member management
  • messaging-protocol.md: Message types, inbox operations, locking patterns
  • task-coordination.md: Task CRUD, state machine, dependency cycle detection
  • spawning-patterns.md: tmux spawning, CLI flags, pane management
  • crew-roles.md: Role taxonomy, capability matrix, role-risk compatibility
  • health-monitoring.md: Heartbeat protocol, stall detection, automated recovery

Integration with Conjure

Agent Teams extends the conjure delegation model:

Conjure PatternAgent Teams Equivalent
delegation-core:task-assessedagent-teams:team-created
delegation-core:handoff-plannedagent-teams:tasks-assigned
delegation-core:results-integratedagent-teams:team-shutdown
External LLM executionTeammate agent execution

Use Skill(conjure:delegation-core) first to determine if the task benefits from multi-agent coordination vs. single-service delegation.

Delegation is on by default there, so the question a team formation answers is which shape of delegation fits, not whether to delegate. A teammate holding execution work delegates it the same way a single session would. A teammate holding design work keeps it, under the same Keep Local clauses.

When a teammate's delegation returns a fallback_reason, that teammate does the work itself and reports which providers it tried. It does not message the crew for a reassignment: no other teammate has a provider this one lacks, because the registry is machine-wide.

Worktree Isolation Alternative (Claude Code 2.1.49+)

For parallel agents that modify files, isolation: worktree provides a lightweight alternative to filesystem-based coordination. Each agent runs in its own temporary git worktree, eliminating the need for fcntl locking or inbox-based conflict avoidance on shared files.

  • When to prefer worktrees over agent teams messaging: Agents work on overlapping files but don't need mid-execution communication
  • When to prefer agent teams messaging: Agents need to coordinate discoveries or adjust plans based on each other's progress
  • Combine both: Use agent teams for coordination with isolation: worktree per teammate for filesystem safety

Troubleshooting

Common Issues

tmux not found Install via package manager: brew install tmux / apt install tmux

Stale lock files If an agent crashes mid-operation, lock files may persist. Remove .lock files manually from ~/.claude/teams/<team>/inboxes/ or ~/.claude/tasks/<team>/

Orphaned tasks Tasks claimed by a crashed agent stay in_progress indefinitely. Use modules/health-monitoring.md for heartbeat-based stall detection and automatic task release. The health monitoring protocol detects unresponsive agents within 60s and 30s probe window and releases their tasks for reassignment.

Message ordering Filesystem timestamp resolution varies (HFS+ = 1s granularity). Use numbered filenames or UUID-sorted names to avoid collision on rapid message bursts.

Model errors on Bedrock/Vertex/Foundry (pre-2.1.39) Teammate agents could use incorrect model identifiers on enterprise providers, causing 400 errors. Upgrade to Claude Code 2.1.39+ for correct model ID qualification across all providers.

Nested session guard (2.1.39+) If claude refuses to launch within an existing session, ensure you're using tmux pane splitting (not subshell invocation). The guard is intentional. See modules/spawning-patterns.md for details.

Exit Criteria

  • Team created with config and directories
  • Teammates spawned and registered in config
  • Tasks created with dependency graph (no cycles)
  • Agents coordinating via inbox messages
  • Graceful shutdown completed

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Agent Teams AI skill do?

Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.

Why use Agent Teams on TypingMind?

Because you install it once and use it with any model. Agent Teams is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Teams in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/athola/claude-night-market/tree/master/plugins/conjure/skills/agent-teams. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Agent Teams?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Teams?

As many as you like. As long as a model supports skills, you can use Agent Teams with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Teams AI skill free?

Yes. It is published on GitHub by athola under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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