agent-teams
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.zipInstalls 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)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
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:
| Surface | What it is | Use when |
|---|---|---|
| Plain subagents (Task tool) | Delegated workers inside one session, own context, return a summary | A 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-managed | Split 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-checks | Job outgrows a handful of subagents: codebase-wide audit, large migration, cross-checked research |
Agent view (claude agents) | Dispatch + monitor background sessions | Several 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
## Parallelizationsection ofCLAUDE.mdfor 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
| Teammate | Role | Model | Isolation |
|---|---|---|---|
| Architect | Design & planning | opus | — |
| Builder | Implementation | sonnet | worktree |
| Validator | Code quality | sonnet | worktree |
| Tester | UX quality | sonnet | worktree |
| Scribe | Documentation | haiku | — |
Recommended team size: 3–5 teammates for optimal coordination.
SharedTaskList
Tasks follow this lifecycle:
pending → in_progress → completed
→ failed
- Dependencies: Tasks can have
blockedByarrays - 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
| Hook | Purpose | Exit Code 2 |
|---|---|---|
TeammateIdle | Fires when teammate about to go idle | Teammate continues working |
TaskCompleted | Fires when task marked complete | Prevents completion, sends feedback |
When to Use Agent Teams vs Standard Orchestration
| Scenario | Use Agent Teams? |
|---|---|
| Large feature with independent modules | YES |
| Multiple parallel investigations | YES |
| Small bug fix | NO — overhead not worth it |
| API change (strict sequence required) | NO — sequential workflow needed |
| Research task | NO — 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
- Break work into truly independent tasks
- Define clear dependencies with
blockedBy - Keep team size to 3–5 teammates
- Use worktree isolation for all building/testing teammates
- 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.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| agent-teams (this skill) | 0 | 1mo | No flags | Advanced |
| autonomous-agents | 10 | 6mo | No flags | Advanced |
| agent-goal-planner | 2 | 6mo | No flags | Advanced |
| planner | 1 | 6mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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