Experimental orchestration tool for coordinating multiple AI agents working in parallel on shared coding tasks.

Install

mkdir -p .claude/skills/agent-teams && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15983" && unzip -o skill.zip -d .claude/skills/agent-teams && rm skill.zip

Installs to .claude/skills/agent-teams

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Experimental Agent Teams orchestration — run CC_GodMode agents as parallel teammates with SharedTaskList coordination (requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1)
167 charsno explicit “when” trigger
Advanced

Key capabilities

  • Coordinate multiple background AI sessions
  • Manage a shared task list among agents
  • Enable inter-agent messaging
  • Assign tasks to teammate agents
  • Synchronize progress of multiple agents
  • Track task lifecycle from pending to completed or failed

How it works

A lead agent assigns work to teammate agents who independently claim, execute, and report tasks from a shared queue, coordinating through inter-agent messaging.

Inputs & outputs

You give it
A project requiring multiple coordinated tasks
You get back
Completed tasks by multiple agents, managed through a shared task list

When to use agent-teams

  • Divide a large feature into smaller, parallel coding tasks
  • Assign specific project components to distinct AI agents
  • Manage persistent teammates working on a shared repository
  • Synchronize multi-agent progress for complex feature development

About this skill

Agent Teams Orchestration (Experimental)

Status: Experimental — OFF by default (requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1) When to use: Large features where multiple teammates can work truly in parallel and the user explicitly accepts the token cost

What Are Agent Teams?

Agent Teams are coordinated background sessions with a shared task list, inter-agent messaging, and a lead/manager that assigns tasks and keeps workers in sync. Instead of the Orchestrator calling agents sequentially via Task tool, a lead agent dispatches work and teammates claim, execute, and report tasks from the shared queue independently.

This surface is experimental and off by default — enable it only by setting CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in your environment or settings.json.

How This Relates to the Other Parallelization Surfaces

GodMode maps onto four parallelization surfaces. Choose the right one for the job:

SurfaceWhat it isUse when
Plain subagents (Task tool)Delegated workers inside one session, own context, return a summaryA side task would flood the main context; up to ~10 run concurrently, the rest queue
Agent teams (this skill)Coordinated sessions, shared task list, inter-agent messaging, lead-managedSplit a project, assign pieces, keep workers in sync — persistent teammates, not one-off tasks
Dynamic workflows (skills/dynamic-workflows/)Orchestrator-written script fans out to tens–hundreds of subagents + adversarial cross-checksJob outgrows a handful of subagents: codebase-wide audit, large migration, cross-checked research
Agent view (claude agents)Dispatch + monitor background sessionsSeveral independent hand-off tasks you check on later (research preview)

Decision guidance:

  • Use plain subagents for one-off in-session side tasks (the default, always available).
  • Use agent teams when you need persistent, coordinated teammates kept in sync via a shared task list across a multi-part project.
  • Use dynamic workflows when a job outgrows a handful of subagents and needs fan-out at scale plus adversarial verification — trigger with the word "workflow" in a prompt or enable ultracode.
  • See also the ## Parallelization section of CLAUDE.md for the cost guardrail and concurrency tiers that apply across all surfaces.

Enabling Agent Teams

Add to your environment or settings.json:

{
  "env": {
    "CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS": "1"
  }
}

Team Composition

TeammateRoleModelIsolation
ArchitectDesign & planningopus
BuilderImplementationsonnetworktree
ValidatorCode qualitysonnetworktree
TesterUX qualitysonnetworktree
ScribeDocumentationhaiku

Recommended team size: 3–5 teammates for optimal coordination.

SharedTaskList

Tasks follow this lifecycle:

pending → in_progress → completed
                     → failed
  • Dependencies: Tasks can have blockedBy arrays
  • Claiming: File-locking prevents race conditions
  • Auto-pickup: After completing a task, teammate picks next unblocked task

Example Task Flow

{
  "tasks": [
    {"id": "1", "name": "Design auth module", "assignee": "architect", "status": "completed"},
    {"id": "2", "name": "Implement auth API", "assignee": "builder", "blockedBy": ["1"], "status": "in_progress"},
    {"id": "3", "name": "Implement auth UI", "assignee": "builder", "blockedBy": ["1"], "status": "in_progress"},
    {"id": "4", "name": "Validate auth code", "assignee": "validator", "blockedBy": ["2", "3"], "status": "pending"},
    {"id": "5", "name": "Test auth UX", "assignee": "tester", "blockedBy": ["2", "3"], "status": "pending"}
  ]
}

Hooks for Agent Teams

HookPurposeExit Code 2
TeammateIdleFires when teammate about to go idleTeammate continues working
TaskCompletedFires when task marked completePrevents completion, sends feedback

When to Use Agent Teams vs Standard Orchestration

ScenarioUse Agent Teams?
Large feature with independent modulesYES
Multiple parallel investigationsYES
Small bug fixNO — overhead not worth it
API change (strict sequence required)NO — sequential workflow needed
Research taskNO — single agent sufficient

Limitations

  • No session resumption with in-process teammates
  • Task status can lag
  • Only one team per session
  • No nested teams
  • Token usage: ~15x standard
  • Shutdown can be slow

Use skills/departments/ first when the problem is ownership and routing. Use Agent Teams only when the implementation work itself can safely run in parallel.

Best Practices

  1. Break work into truly independent tasks
  2. Define clear dependencies with blockedBy
  3. Keep team size to 3–5 teammates
  4. Use worktree isolation for all building/testing teammates
  5. Reserve standard orchestration for sequential workflows (API changes)

When not to use it

  • For small bug fixes due to overhead
  • For API changes requiring strict sequential workflow
  • For research tasks where a single agent is sufficient

Limitations

  • No session resumption with in-process teammates
  • Task status can lag
  • Only one team per session

How it compares

This workflow enables persistent, coordinated teammates working in parallel on a shared task list, unlike sequential task execution by a single orchestrator.

Compared to similar skills

agent-teams side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
agent-teams (this skill)01moNo flagsAdvanced
autonomous-agents106moNo flagsAdvanced
agent-goal-planner26moNo flagsAdvanced
planner16moNo flagsIntermediate

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Example prompts that trigger this skill in your AI assistant.

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