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".

Quality

46%

Does it follow best practices?

Impact

Pending

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Securityby

Passed

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npx tessl skill review --optimize ./.codex/skills/team-lifecycle-v4/SKILL.md

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> -> 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`, `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_from tasks via tasks.json and discoveries/{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}.json for each agent, update tasks.json status/findings/error, then close_agent({ target }) each worker
Execute checkpoints -- For each CHECKPOINT task, assign_task to supervisor, wait_agent, read checkpoint report from artifacts/, parse verdict
Handle block -- If verdict is block, prompt user via request_user_input with 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 implementer
assign_task({ target: "supervisor", items: [...] }) -- wake supervisor for checkpoint
close_agent({ target: "IMPL-001" }) -- cleanup regular worker by name
close_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"

Repository: catlog22/Claude-Code-Workflow
Commit: 0f8e801

Last updated: 4 days ago
Created: 4 days ago

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