Agent Teams

SkillProductivity

Select and coordinate multi-agent teams (topology kits, role-based squads, lifecycle, worktree isolation). Use this skill whenever launching parallel agents, designing a review board, running a debug council, scheduling an orchestrator-workers team, configuring agent tool restrictions, or deciding between solo and team execution. Triggers on: "launch a team", "parallel agents", "review board", "debug council", "architect-implementer-reviewer", "swarm", "multi-agent", "subagents for X", "team topology", "agent lifecycle".

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Agent Teams skill

What this skill tells your AI

The instructions your AI receives, as published by thelobbi/claude in plugins/claude-code-expert/skills/cc-agent-teams/SKILL.md and read by ahel’s review.

Multi-agent orchestration with explicit topologies, tool restrictions, worktree isolation, and lifecycle management.

When to use a team vs solo

SignalGo team
Task has 3+ independent subtasksyes
Quality-critical (security, compliance)yes (adds reviewer)
Cross-cutting refactor touching many filesyes
Debug with multiple plausible hypothesesyes (competing-hypotheses)
Straightforward feature in one moduleno (solo is cheaper)
Time-sensitive (parallel beats serial)yes

Rough guideline: team cost = 1.5–6× solo, so reserve teams for tasks where the parallel-or-specialist value justifies it.

Five ready-made topologies (fetch via MCP)

TopologySizeWhen
architect-implementer-reviewer3 (2 Opus + 1 Sonnet)Medium-to-large features with non-trivial design
frontend-backend-test-squad4 (3 Sonnet + 1 Opus)Full-stack features with clear UI/API/test split
competing-hypotheses-debug4 (3 Sonnet parallel + 1 Opus synth)Bugs with multiple plausible causes
security-performance-test-review-board4 parallel SonnetPR reviews where discipline specialists are cheaper than generalist
docs-migration-sprint4 (3 Sonnet writers + 1 Opus editor)Large doc migrations (framework version bumps, brand renames)

Fetch full kit via cc_kb_topology_kit(name) — includes composition, file ownership, coordination protocol, cost estimate, anti-patterns.

Shortlist for a specific task: cc_docs_team_topology_recommend(task, complexity, team_size).

Role-based subagents (general-purpose)

These agents are topology-agnostic — plug them into any topology:

AgentModelTools
cc-implementerSonnetRead, Edit, Write, Bash, Grep, Glob
cc-debuggerOpusRead, Grep, Glob, Bash (hypothesis protocol)
cc-migration-leadOpusRead + writes migration plan before any code
cc-dependency-auditorHaikuBash (pnpm/pip/cargo audit only)
cc-release-coordinatorSonnetRead, Write, Bash (semver + changelog + tag)
cc-audit-reviewerOpusRead, Grep, Glob (second-round review)
cc-security-compliance-advisorOpusRead, Grep, Glob, Bash (compliance scan)
cc-principal-engineer-strategistOpusRead, Grep, Glob (deep analysis)
cc-council-coordinatorOpusAgent, Read (fan-out/fan-in)
cc-team-orchestratorOpusAgent, Read, Write (delegation + lifecycle)

Coordination protocols

ProtocolUse
Serial (chain)Phase N+1 needs phase N's output verbatim (architect → implementer → reviewer)
Parallel (fan-out)Subtasks are independent; merge at end (review board, competing hypotheses)
BlackboardAgents read each other's evolving notes; coordinator synthesizes (council review)
Orchestrator-workersLead agent decomposes and spawns workers dynamically

Worktree isolation

Parallel agents often need isolated working copies to prevent interference. Use isolation: "worktree" on the Agent tool call, or manually git worktree add before launching.

When to isolate:

  • Parallel agents all edit the same file → yes, isolate
  • Parallel agents investigate (read-only) → no, shared repo is fine
  • Agents share state via a coordinator file (blackboard) → no isolation, but strict write-discipline

Coordination mechanics (current Agent-tool surface)

NeedHow
Spawn a teammateAgent tool with subagent_type, model, and a focused prompt. A built-in general-purpose agent is always available.
Address it later with context intactgive it a name/team_name, then SendMessage to that name/ID — a fresh Agent call instead starts a new context.
Run non-blockingrun_in_background: true (tool) / background: true (frontmatter); you're notified on completion. Launch independent agents in one message to run them concurrently.
Isolate the working copyisolation: "worktree" (see below).
Require a plan before it actsmode: "plan" on the spawn.
Cap runaway loopsmaxTurns in the agent definition.

The agent's final message is the only thing returned to the parent — relay what matters; the user doesn't see a teammate's transcript. Keep spawn prompts under ~400 words and prefer named specialists over generics (see cc-prompt-budget-preflight).

Fable 5 for long-horizon coordinators. When a team runs for hours (overnight builds, multi-wave migrations), put the coordinator on model: fable — Fable 5 reliably sustains ongoing messaging with long-running async subagents and doesn't drift across waves the way smaller orchestrators can. Workers stay on Sonnet; the tier premium (~2× Opus per token) only pays off on the coordinator role. Old "don't over-delegate" guardrails written for prior models should be relaxed on Fable — delegation is dependable there.

Lifecycle management

Long-running or idle agents waste tokens. cc-team-orchestrator agent handles this:

  • Health check active agents periodically.
  • Mark agents idle after N minutes of no activity.
  • Clean up completed worktrees if the agent made no changes.
  • Retain results (the agent's final message) for the coordinator even after cleanup.

MCP delegation

NeedTool
Fetch a topology kitcc_kb_topology_kit(name)
Recommend a topologycc_docs_team_topology_recommend(task, complexity, team_size)
Model for each rolecc_docs_model_recommend(task, budget)
Pattern for orchestrationcc_kb_pattern_template(name)

Anti-patterns

  • Launching a team for a task a solo agent could finish in under 5 tool calls → overhead dominates.
  • Parallel agents with identical system prompts → not actually parallel; just N×cost.
  • No coordinator → each agent reports separately; user has to synthesize.
  • Unbounded agent TTL → agents hang around consuming session tokens.
  • Team cost estimate skipped → teams regularly exceed budget; always estimate first via cc_docs_model_recommend.

Signals

GitHub stars
21
Forks
2
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
cc-agent-teams
Source
github.com/thelobbi/claude