Agent skill

Team Lifecycle V4

by catlog22 in catlog22/Claude-Code-Workflow

Full lifecycle team skill with clean architecture. An agent skill from catlog22/Claude-Code-Workflow.

MITAuto-check: notesDevelopment

Install Team Lifecycle V4

skills CLI
$ npx skills add catlog22/Claude-Code-Workflow --skill team-lifecycle-v4 -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install catlog22/Claude-Code-Workflow team-lifecycle-v4 --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/team-lifecycle-v4 .claude/skills/team-lifecycle-v4 && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
team-lifecycle-v4
GitHub stars
2.1k
Token cost
~3k tokens
SKILL.md length
762 words
Files
34
Skills in repo
82
Repo updated
First seen
Licence
MIT

At a glance

Full lifecycle team skill with clean architecture. An agent skill from catlog22/Claude-Code-Workflow.

  • Works in 10 steps: Load state -- Read /tasks.json, filter… → Skip failed deps -- Mark tasks whose… → Build upstream context -- For each task,… → …
  • Team lifecycle v4
  • SKILL.md covers Architecture, Role Registry, Role Router and Delegation Lock, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Team Lifecycle V4 is an agent skill from catlog22/Claude-Code-Workflow. 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".

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 41 other files (for example `MIGRATION-PLAN.md`, `instructions/agent-instruction.md` and `roles/analyst/role.md`).

It sits in Development, covering Design patterns. The repository describes itself as: JSON-driven multi-agent cadence-team development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution. The licence is MIT.

When your agent uses it

  • Team lifecycle v4
  • Tasks that involve Design patterns

Example prompts

  • “team lifecycle v4”
  • “/team-lifecycle-v4”

Requirements

  • Pre-approved tools (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(*)

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Load state -- Read /tasks.json, filter tasks for current wave
  2. Skip failed deps -- Mark tasks whose dependencies failed/skipped as skipped
  3. Build upstream context -- For each task, gather findings from context_from tasks via tasks.json and discoveries/{id}.json
  4. Separate task types -- Split into regular tasks and CHECKPOINT tasks
  5. Spawn regular tasks -- For each regular task, call spawn_agent({ agent_type: "team_worker", message: "..." }), collect agent IDs
  6. Wait -- wait_agent({ timeout_ms: 1800000 }) — apply timeout cascade if timed_out
  7. Collect results -- Read discoveries/{task_id}.json for each agent, update tasks.json status/findings/error, then close_agent({ target })…
  8. Execute checkpoints -- For each CHECKPOINT task, followup_task to supervisor, wait_agent, read checkpoint report from artifacts/, parse…
  9. Handle block -- If verdict is block, prompt user via request_user_input with options: Override / Revise upstream / Abort
  10. Persist -- Write updated state to /tasks.json

What it can do on your machine

Read from SKILL.md and the folder at commit 07491b0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • spawn_agent(*)
    • wait_agent(*)
    • send_message(*)
    • followup_task(*)
    • close_agent(*)
    • list_agents(*)
    • report_agent_job_result(*)
    • Read(*)
    • Write(*)
    • Edit(*)

    …and 5 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Team Lifecycle V4 loads about 3k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 762 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: spawn_agent(*), wait_agent(*), send_message(*), followup_task(*), close_agent(*), list_agents(*), re

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from catlog22/Claude-Code-Workflow at commit 07491b0, republished under its MIT licence (© catlog22). 762 words, ~2,979 tokens.

Download SKILL.mdSave it as .claude/skills/team-lifecycle-v4/SKILL.md (or your agent's skills folder). This skill also uses 33 other files; get the full folder from GitHub.
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

RolePathPrefixInner Loop
coordinatorroles/coordinator/role.md----
analystroles/analyst/role.mdRESEARCH-*false
writerroles/writer/role.mdDRAFT-*true
plannerroles/planner/role.mdPLAN-*true
executorroles/executor/role.mdIMPL-*true
testerroles/tester/role.mdTEST-*false
reviewerroles/reviewer/role.mdREVIEW-, QUALITY-, IMPROVE-*false
supervisorroles/supervisor/role.mdCHECKPOINT-*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 CallVerdictReason
spawn_agent, wait_agent, close_agent, send_message, followup_taskALLOWEDOrchestration
list_agentsALLOWEDAgent health check
request_user_inputALLOWEDUser interaction
mcp__ccw-tools__team_msgALLOWEDMessage bus
Read/Write on .workflow/.team/ filesALLOWEDSession state
Read on roles/, commands/, specs/, templates/ALLOWEDLoading own instructions
Read/Grep/Glob on project source codeBLOCKEDDelegate to worker
Edit on any file outside .workflow/BLOCKEDDelegate to worker
Bash("ccw cli ...")BLOCKEDOnly workers call CLI
Bash running build/test/lint commandsBLOCKEDDelegate 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-<date>-<slug>/
  • 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_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
Rolemodelreasoning_effortRationale
Analyst (RESEARCH-*)(default)mediumRead-heavy exploration, less reasoning needed
Writer (DRAFT-*)(default)highSpec writing requires precision and completeness
Planner (PLAN-*)(default)highArchitecture decisions need full reasoning
Executor (IMPL-*)(default)highCode generation needs precision
Tester (TEST-*)(default)highTest generation requires deep code understanding
Reviewer (REVIEW-, QUALITY-, IMPROVE-*)(default)highDeep analysis for quality assessment
Supervisor (CHECKPOINT-*)(default)mediumGate 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:

  1. Load state -- Read <session>/tasks.json, filter tasks for current wave
  2. Skip failed deps -- Mark tasks whose dependencies failed/skipped as skipped
  3. Build upstream context -- For each task, gather findings from context_from tasks via tasks.json and discoveries/{id}.json
  4. Separate task types -- Split into regular tasks and CHECKPOINT tasks
  5. Spawn regular tasks -- For each regular task, call spawn_agent({ agent_type: "team_worker", message: "..." }), collect agent IDs
  6. Wait -- wait_agent({ timeout_ms: 1800000 }) — apply timeout cascade if timed_out
  7. Collect results -- Read discoveries/{task_id}.json for each agent, update tasks.json status/findings/error, then close_agent({ target }) each worker
  8. Execute checkpoints -- For each CHECKPOINT task, followup_task to supervisor, wait_agent, read checkpoint report from artifacts/, parse verdict
  9. Handle block -- If verdict is block, prompt user via request_user_input with options: Override / Revise upstream / Abort
  10. Persist -- Write updated state to <session>/tasks.json
Show full SKILL.md (278 more words)Show less

User Commands

CommandAction
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
IntentAPIExample
Queue supplementary info (don't interrupt)send_messageSend planning results to running implementers
Wake resident supervisor for checkpointfollowup_taskTrigger CHECKPOINT-* evaluation on supervisor
Supervisor reports back to coordinatorsend_messageSupervisor sends checkpoint verdict as supplementary info
Check running agentslist_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 implementer
  • followup_task({ target: "supervisor", message: "..." }) -- 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:

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

ScenarioResolution
Unknown commandError with available command list
Role not foundError with role registry
CLI tool failsWorker fallback to direct implementation
Supervisor crashRespawn with recovery: true, auto-rebuilds from existing reports
Supervisor not ready for CHECKPOINTSpawn/respawn supervisor, wait for ready, then wake
Completion action failsDefault to Keep Active
Worker timeoutMark task as failed, continue wave
Discovery file missingMark task as failed with "No discovery file produced"

© catlog22, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 33 other files in .codex/skills/team-lifecycle-v4 of catlog22/Claude-Code-Workflow.

  • SKILL.md
  • MIGRATION-PLAN.md
  • instructions/agent-instruction.md
  • roles/analyst/role.md
  • roles/coordinator/commands/analyze.md
  • roles/coordinator/commands/dispatch.md
  • roles/coordinator/commands/monitor.md
  • roles/coordinator/role.md
  • roles/executor/commands/fix.md
  • roles/executor/commands/implement.md
  • roles/executor/role.md
  • roles/planner/role.md
  • roles/reviewer
  • … and 21 more

Open the folder on GitHubat commit 07491b0

Compare with similar skills

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Effect Client WrapperUsefulSoftwareCo/executor4.1k1 repos~1.4kAutomated safety check: PassMIT
Architecture PatternsKartikLabhshetwar/better-shot2.4k2 repos~1.4kAutomated safety check: PassCustom licence

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Categories

Questions about Team Lifecycle V4

What does Team Lifecycle V4 do?

Full lifecycle team skill with clean architecture. An agent skill from catlog22/Claude-Code-Workflow. Team Lifecycle V4 is an agent skill from catlog22/Claude-Code-Workflow. Full lifecycle team skill with clean architecture.

When should I use Team Lifecycle V4?

Team Lifecycle V4 fits situations like: team lifecycle v4; tasks that involve Design patterns.

How do I install Team Lifecycle V4 in Claude Code?

Run `npx skills add catlog22/Claude-Code-Workflow --skill team-lifecycle-v4 -a claude-code`. Or copy the skill folder (.codex/skills/team-lifecycle-v4 in catlog22/Claude-Code-Workflow) into .claude/skills/team-lifecycle-v4 in your project. Claude Code loads it when a task matches its description.

How do I install Team Lifecycle V4 in Codex?

Run `npx skills add catlog22/Claude-Code-Workflow --skill team-lifecycle-v4 -a codex`. Or copy the skill folder (.codex/skills/team-lifecycle-v4 in catlog22/Claude-Code-Workflow) into .agents/skills/team-lifecycle-v4 in your project. Codex loads it when a task matches its description.

Can I use Team Lifecycle V4 in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add catlog22/Claude-Code-Workflow --skill team-lifecycle-v4 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/team-lifecycle-v4, .gemini/skills/team-lifecycle-v4, .github/skills/team-lifecycle-v4 and .opencode/skills/team-lifecycle-v4 in your project.

What does Team Lifecycle V4 need to run?

SKILL.md names no scripts, command-line tools or credentials: Team Lifecycle V4 is instructions for the agent only. Its frontmatter pre-approves these 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(*).

Does Team Lifecycle V4 access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Team Lifecycle V4 safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Team Lifecycle V4 use?

Team Lifecycle V4 is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Team Lifecycle V4 use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Team Lifecycle V4?

Skills that share tags, products or a category with Team Lifecycle V4: Vercel Composition Patterns (supabase/supabase, 111k stars), Swiftui View Refactor (Dimillian/Skills, 4k stars), RTK Rust Design Patterns (rtk-ai/rtk, 83k stars) and Effect Client Wrapper (UsefulSoftwareCo/executor, 4.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Team Lifecycle V4?

catlog22 (a GitHub user) maintains it in catlog22/Claude-Code-Workflow, which has 2,130 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on June 18, 2026.

Source: catlog22/Claude-Code-Workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.