Skip to main content
team-lifecycle-v4 Full lifecycle team skill with clean architecture. SKILL.md is a universal router — all roles read it. Beat model is coordinator-only. Structure is roles/ + specs/ + templates/. Triggers on "team lifecycle v4".
Ir a la instalación Skills Marketplace Descubre y explora habilidades de IA creadas por la comunidad.
Ocupaciones relacionadas SOC
Basado en la clasificación ocupacional SOC
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Mostrar detalles del prompt Un comando directo omite el prompt de revisión. Revisa el origen antes de ejecutarlo.
npx skills add https://github.com/catlog22/Claude-Code-Workflow --skill team-lifecycle-v4El comando permanece en una sola línea. Desplázate horizontalmente para revisarlo antes de copiarlo.
¿Prefieres una copia local? Descarga los archivos que SkillsMP tiene disponibles ahora.
Descargar Zip Descargando... Explorador de archivos
26 archivos Más de este repositorio CCW command help system. Search, browse, recommend commands, skills, teams. Triggers "ccw-help", "ccw-issue".
Lightweight execution engine - multi-mode input, task grouping, batch execution, chain to workflow-lite-test-review
Lightweight planning skill - task analysis, multi-angle exploration, clarification, adaptive planning, confirmation, and execution handoff
name team-lifecycle-v4 description Full lifecycle team skill with clean architecture. SKILL.md is a universal router — all roles read it. Beat model is coordinator-only. Structure is roles/ + specs/ + templates/. Triggers on "team lifecycle v4". allowed-tools spawn_agent(*), wait_agent(*), send_message(*), followup_task(*), close_agent(*), list_agents(*), report_agent_job_result(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), request_user_input(*), mcp__ccw-tools__team_msg(*)
Team Lifecycle v4
Orchestrate multi-agent software development: specification -> planning -> implementation -> testing -> review.
Architecture
Skill(skill="team-lifecycle-v4", args="task description")
|
SKILL.md (this file) = Router
|
+--------------+--------------+
| |
no --role flag --role <name>
| |
Coordinator Worker
roles/coordinator/role.md roles/<name>/role.md
|
+-- analyze -> dispatch -> spawn -> wait -> collect
|
+--------+---+--------+
v v v
spawn_agent ... spawn_agent
(team_worker) (team_supervisor)
per-task resident agent
lifecycle followup_task-driven
| |
+-- wait_agent --------+
|
collect results
Role Registry
Role Path Prefix Inner Loop coordinator
Role Router
Has --role <name> -> Read roles/<name>/role.md, execute Phase 2-4
No --role -> roles/coordinator/role.md, execute entry router
Delegation Lock Coordinator is a PURE ORCHESTRATOR. It coordinates, it does NOT do.
Before calling ANY tool, apply this check:
Tool Call Verdict Reason spawn_agent, wait_agent, close_agent, send_message, followup_taskALLOWED Orchestration list_agentsALLOWED Agent health check request_user_inputALLOWED User interaction mcp__ccw-tools__team_msgALLOWED Message bus Read/Write on .workflow/.team/ filesALLOWED Session state Read on roles/, commands/, specs/, templates/ALLOWED Loading own instructions Read/Grep/Glob on project source codeBLOCKED Delegate to worker Edit on any file outside .workflow/BLOCKED Delegate to worker Bash("ccw cli ...")BLOCKED Only workers call CLI Bash running build/test/lint commandsBLOCKED Delegate to worker
If a tool call is BLOCKED : STOP. Create a task, spawn a worker.
No exceptions for "simple" tasks. Even a single-file read-and-report MUST go through spawn_agent.
Shared Constants
Session prefix : TLV4Session path : .workflow/.team/TLV4-<date>-<slug>/State file : <session>/tasks.jsonDiscovery files : <session>/discoveries/{task_id}.jsonCLI tools : ccw cli --mode analysis (read-only), ccw cli --mode write (modifications)
Worker Spawn Template Coordinator spawns workers using this template:
spawn_agent({
agent_type: "team_worker",
task_name: "<task-id>",
fork_turns: "none",
message: `## Role Assignment
role: <role>
role_spec: <skill_root>/roles/<role>/role.md
session: <session-folder>
session_id: <session-id>
requirement: <task-description>
inner_loop: <true|false>
Read role_spec file (<skill_root>/roles/<role>/role.md) to load Phase 2-4 domain instructions.
Execute built-in Phase 1 (task discovery) -> role Phase 2-4 -> built-in Phase 5 (report).
## Task Context
task_id: <task-id>
title: <task-title>
description: <task-description>
pipeline_phase: <pipeline-phase>
## Upstream Context
<prev_context>`
})
Supervisor Spawn Template Supervisor is a resident agent (independent from team_worker). Spawned once during session init, woken via followup_task for each CHECKPOINT task.
Spawn (Phase 2 -- once per session) supervisorId = spawn_agent({
agent_type: "team_supervisor",
task_name: "supervisor",
fork_turns: "none",
message: `## Role Assignment
role: supervisor
role_spec: <skill_root>/roles/supervisor/role.md
session: <session-folder>
session_id: <session-id>
requirement: <task-description>
Read role_spec file (<skill_root>/roles/supervisor/role.md) to load checkpoint definitions.
Init: load baseline context, report ready, go idle.
Wake cycle: orchestrator sends checkpoint requests via followup_task.`
})
Wake (per CHECKPOINT task) followup_task({
target: "supervisor",
message: `## Checkpoint Request
task_id: <CHECKPOINT-NNN>
scope: [<upstream-task-ids>]
pipeline_progress: <done>/<total> tasks completed`
})
wait_agent({ timeout_ms: 1800000 }) // 30 min — apply timeout cascade if timed_out
Shutdown (pipeline complete) close_agent({ target: "supervisor" })
Model Selection Guide Role model reasoning_effort Rationale Analyst (RESEARCH-*) (default) medium Read-heavy exploration, less reasoning needed Writer (DRAFT-*) (default) high Spec writing requires precision and completeness Planner (PLAN-*) (default) high Architecture decisions need full reasoning Executor (IMPL-*) (default) high Code generation needs precision Tester (TEST-*) (default) high Test generation requires deep code understanding Reviewer (REVIEW-, QUALITY- , IMPROVE-*) (default) high Deep analysis for quality assessment Supervisor (CHECKPOINT-*) (default) medium Gate checking, report aggregation
Override model/reasoning_effort in spawn_agent when cost optimization is needed:
spawn_agent({
agent_type: "team_worker",
task_name: "<task-id>",
fork_turns: "none",
model: "<model-override>",
reasoning_effort: "<effort-level>",
message: "..."
})
Wave Execution Engine For each wave in the pipeline:
Load state -- Read <session>/tasks.json, filter tasks for current waveSkip failed deps -- Mark tasks whose dependencies failed/skipped as skippedBuild upstream context -- For each task, gather findings from context_from tasks via tasks.json and discoveries/{id}.jsonSeparate task types -- Split into regular tasks and CHECKPOINT tasksSpawn regular tasks -- For each regular task, call spawn_agent({ agent_type: "team_worker", message: "..." }), collect agent IDsWait -- wait_agent({ timeout_ms: 1800000 }) — apply timeout cascade if timed_outCollect results -- Read discoveries/{task_id}.json for each agent, update tasks.json status/findings/error, then close_agent({ target }) each workerExecute checkpoints -- For each CHECKPOINT task, followup_task to supervisor, wait_agent, read checkpoint report from artifacts/, parse verdictHandle block -- If verdict is block, prompt user via request_user_input with options: Override / Revise upstream / AbortPersist -- Write updated state to <session>/tasks.json
User Commands Command Action check / statusView execution status graph resume / continueAdvance to next step revise <TASK-ID> [feedback]Revise specific task feedback <text>Inject feedback for revision recheckRe-run quality check improve [dimension]Auto-improve weakest dimension
v4 Agent Coordination
Message Semantics Intent API Example Queue supplementary info (don't interrupt) send_messageSend planning results to running implementers Wake resident supervisor for checkpoint followup_taskTrigger CHECKPOINT-* evaluation on supervisor Supervisor reports back to coordinator send_messageSupervisor sends checkpoint verdict as supplementary info Check running agents list_agentsVerify agent + supervisor health during resume
CRITICAL : The supervisor is a resident agent woken via followup_task, NOT send_message. Regular workers complete and are closed; the supervisor persists across checkpoints. See "Supervisor Spawn Template" above.
Agent Health Check Use list_agents({}) in handleResume and handleComplete:
// Reconcile session state with actual running agents
const running = list_agents({})
// Compare with tasks.json active_agents
// Reset orphaned tasks (in_progress but agent gone) to pending
// ALSO check supervisor: if supervisor missing but CHECKPOINT tasks pending -> respawn
Named Agent Targeting Workers are spawned with task_name: "<task-id>" enabling direct addressing:
send_message({ target: "IMPL-001", message: "..." }) -- queue planning context to running implementerfollowup_task({ target: "supervisor", message: "..." }) -- wake supervisor for checkpointclose_agent({ target: "IMPL-001" }) -- cleanup regular worker by nameclose_agent({ target: "supervisor" }) -- shutdown supervisor at pipeline end
Completion Action When pipeline completes, coordinator presents:
functions.request_user_input({
questions: [{
question: "Pipeline complete. What would you like to do?",
header: "Completion",
multiSelect: false,
options: [
{ label: "Archive & Clean (Recommended)", description: "Archive session, clean up resources" },
{ label: "Keep Active", description: "Keep session for follow-up work" },
{ label: "Export Results", description: "Export deliverables to target directory" }
]
}]
})
Specs Reference
Session Directory .workflow/.team/TLV4-<date>-<slug>/
├── tasks.json # Task state (JSON)
├── discoveries/ # Per-task findings ({task_id}.json)
├── spec/ # Spec phase outputs
├── plan/ # Implementation plan
├── artifacts/ # All deliverables
├── wisdom/ # Cross-task knowledge
├── explorations/ # Shared explore cache
└── discussions/ # Discuss round records
Error Handling Scenario Resolution Unknown command Error with available command list Role not found Error with role registry CLI tool fails Worker fallback to direct implementation Supervisor crash Respawn with recovery: true, auto-rebuilds from existing reports Supervisor not ready for CHECKPOINT Spawn/respawn supervisor, wait for ready, then wake Completion action fails Default to Keep Active Worker timeout Mark task as failed, continue wave Discovery file missing Mark task as failed with "No discovery file produced"
