Upgrade all team-* skills from mechanical v3→v4 API renames to deep v4 tool integration with skill-adaptive patterns: - list_agents: health checks in handleResume, cleanup verification in handleComplete, added to allowed-tools and coordinator toolbox - Named targeting: task_name uses task-id (e.g. EXPLORE-001) instead of generic <role>-worker, enabling send_message/assign_task by name - Message semantics: send_message for supplementary cross-agent context vs assign_task for triggering work, with skill-specific examples - Model selection: per-role reasoning_effort guidance matching each skill's actual roles (not generic boilerplate) - timeout_ms: added to all wait_agent calls, timed_out handling in all 18 monitor.md files - Skill-adaptive v4 sections: ultra-analyze N-parallel coordination, lifecycle-v4 supervisor assign_task/send_message distinction, brainstorm ideator parallel patterns, iterdev generator-critic loops, frontend-debug iterative debug assign_task, perf-opt benchmark context sharing, executor lightweight trimmed v4, etc. 60 files changed across 20 team skills (SKILL.md, monitor.md, role.md) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
12 KiB
name, description, allowed-tools
| name | description | allowed-tools |
|---|---|---|
| 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". | spawn_agent(*), wait_agent(*), send_message(*), assign_task(*), close_agent(*), list_agents(*), report_agent_job_result(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), request_user_input(*) |
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 assign_task-driven
| |
+-- wait_agent --------+
|
collect results
Role Registry
| Role | Path | Prefix | Inner Loop |
|---|---|---|---|
| coordinator | roles/coordinator/role.md | -- | -- |
| analyst | roles/analyst/role.md | RESEARCH-* | false |
| writer | roles/writer/role.md | DRAFT-* | true |
| planner | roles/planner/role.md | PLAN-* | true |
| executor | roles/executor/role.md | IMPL-* | true |
| tester | roles/tester/role.md | TEST-* | false |
| reviewer | roles/reviewer/role.md | REVIEW-, QUALITY-, IMPROVE-* | false |
| supervisor | roles/supervisor/role.md | CHECKPOINT-* | false |
Role Router
Parse $ARGUMENTS:
- Has
--role <name>-> Readroles/<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, assign_task |
ALLOWED | Orchestration |
list_agents |
ALLOWED | Agent health check |
request_user_input |
ALLOWED | User interaction |
mcp__ccw-tools__team_msg |
ALLOWED | Message bus |
Read/Write on .workflow/.team/ files |
ALLOWED | Session state |
Read on roles/, commands/, specs/, templates/ |
ALLOWED | Loading own instructions |
Read/Grep/Glob on project source code |
BLOCKED | 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 commands |
BLOCKED | 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:
TLV4 - Session path:
.workflow/.team/TLV4-<slug>-<date>/ - State file:
<session>/tasks.json - Discovery files:
<session>/discoveries/{task_id}.json - CLI 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_context: false,
items: [
{ type: "text", text: `## 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).` },
{ type: "text", text: `## Task Context
task_id: <task-id>
title: <task-title>
description: <task-description>
pipeline_phase: <pipeline-phase>` },
{ type: "text", text: `## Upstream Context
<prev_context>` }
]
})
Supervisor Spawn Template
Supervisor is a resident agent (independent from team_worker). Spawned once during session init, woken via assign_task for each CHECKPOINT task.
Spawn (Phase 2 -- once per session)
supervisorId = spawn_agent({
agent_type: "team_supervisor",
task_name: "supervisor",
fork_context: false,
items: [
{ type: "text", text: `## 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 assign_task.` }
]
})
Wake (per CHECKPOINT task)
assign_task({
target: "supervisor",
items: [
{ type: "text", text: `## Checkpoint Request
task_id: <CHECKPOINT-NNN>
scope: [<upstream-task-ids>]
pipeline_progress: <done>/<total> tasks completed` }
]
})
wait_agent({ targets: ["supervisor"], timeout_ms: 300000 })
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_context: false,
model: "<model-override>",
reasoning_effort: "<effort-level>",
items: [...]
})
Wave Execution Engine
For each wave in the pipeline:
- Load state -- Read
<session>/tasks.json, filter tasks for current wave - Skip failed deps -- Mark tasks whose dependencies failed/skipped as
skipped - Build upstream context -- For each task, gather findings from
context_fromtasks via tasks.json anddiscoveries/{id}.json - Separate task types -- Split into regular tasks and CHECKPOINT tasks
- Spawn regular tasks -- For each regular task, call
spawn_agent({ agent_type: "team_worker", items: [...] }), collect agent IDs - Wait --
wait_agent({ targets: [...], timeout_ms: 900000 }) - Collect results -- Read
discoveries/{task_id}.jsonfor each agent, update tasks.json status/findings/error, thenclose_agent({ target })each worker - Execute checkpoints -- For each CHECKPOINT task,
assign_taskto supervisor,wait_agent, read checkpoint report fromartifacts/, parse verdict - Handle block -- If verdict is
block, prompt user viarequest_user_inputwith options: Override / Revise upstream / Abort - Persist -- Write updated state to
<session>/tasks.json
User Commands
| Command | Action |
|---|---|
check / status |
View execution status graph |
resume / continue |
Advance to next step |
revise <TASK-ID> [feedback] |
Revise specific task |
feedback <text> |
Inject feedback for revision |
recheck |
Re-run quality check |
improve [dimension] |
Auto-improve weakest dimension |
v4 Agent Coordination
Message Semantics
| Intent | API | Example |
|---|---|---|
| Queue supplementary info (don't interrupt) | send_message |
Send planning results to running implementers |
| Wake resident supervisor for checkpoint | assign_task |
Trigger CHECKPOINT-* evaluation on supervisor |
| Supervisor reports back to coordinator | send_message |
Supervisor sends checkpoint verdict as supplementary info |
| Check running agents | list_agents |
Verify agent + supervisor health during resume |
CRITICAL: The supervisor is a resident agent woken via assign_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", items: [...] })-- queue planning context to running implementerassign_task({ target: "supervisor", items: [...] })-- 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:
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
- specs/pipelines.md -- Pipeline definitions and task registry
- specs/quality-gates.md -- Quality gate criteria and scoring
- specs/knowledge-transfer.md -- Artifact and state transfer protocols
Session Directory
.workflow/.team/TLV4-<slug>-<date>/
├── 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" |