team-lifecycle-v4 — orchestration de workflows team-lifecycle-v4, maestro-flow, community, orchestration de workflows, ide skills, tableau de bord multi-agent, gestion de tâches, planification de projets

v1.0.0

À propos de ce Skill

Parfait pour les agents IA nécessitant une orchestration de workflow multi-agent simplifiée et une intégration de point de terminaison MCP pour la gestion du cycle de vie de développement de logiciels. Team Lifecycle v4 est un outil d'orchestration de workflows qui intègre MCP et propose un tableau de bord multi-agent

Fonctionnalités

Orchestration de workflows avec MCP
Tableau de bord multi-agent
CLI pour la gestion de tâches
Prise en charge de la planification et de la mise en œuvre de projets
Intégration avec des outils de testing et de révision

# Core Topics

catlog22 catlog22
[5]
[0]
Updated: 3/18/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 8/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
8/11
Quality Score
45
Canonical Locale
en
Detected Body Locale
en

Parfait pour les agents IA nécessitant une orchestration de workflow multi-agent simplifiée et une intégration de point de terminaison MCP pour la gestion du cycle de vie de développement de logiciels. Team Lifecycle v4 est un outil d'orchestration de workflows qui intègre MCP et propose un tableau de bord multi-agent

Pourquoi utiliser cette compétence

Permet aux agents d'orchestrer le développement de logiciels de la spécification à la revue, en exploitant les tableaux de bord multi-agents et l'intégration de point de terminaison MCP, tout en prenant en charge la gestion de flux de travail basée sur CLI et l'architecture basée sur Router.

Meilleur pour

Parfait pour les agents IA nécessitant une orchestration de workflow multi-agent simplifiée et une intégration de point de terminaison MCP pour la gestion du cycle de vie de développement de logiciels.

Cas d'utilisation exploitables for team-lifecycle-v4

Automatiser les flux de travail de développement de logiciels de la spécification à la revue
Intégrer des tableaux de bord multi-agents pour une collaboration et une visibilité améliorées
Optimiser les processus de test et de revue en utilisant l'intégration de point de terminaison MCP

! Sécurité et Limitations

  • Nécessite une gestion de flux de travail basée sur CLI
  • Limité à la gestion du cycle de vie de développement de logiciels
  • Dépendant de l'architecture basée sur Router

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is team-lifecycle-v4?

Parfait pour les agents IA nécessitant une orchestration de workflow multi-agent simplifiée et une intégration de point de terminaison MCP pour la gestion du cycle de vie de développement de logiciels. Team Lifecycle v4 est un outil d'orchestration de workflows qui intègre MCP et propose un tableau de bord multi-agent

How do I install team-lifecycle-v4?

Run the command: npx killer-skills add catlog22/maestro-flow/team-lifecycle-v4. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for team-lifecycle-v4?

Key use cases include: Automatiser les flux de travail de développement de logiciels de la spécification à la revue, Intégrer des tableaux de bord multi-agents pour une collaboration et une visibilité améliorées, Optimiser les processus de test et de revue en utilisant l'intégration de point de terminaison MCP.

Which IDEs are compatible with team-lifecycle-v4?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for team-lifecycle-v4?

Nécessite une gestion de flux de travail basée sur CLI. Limité à la gestion du cycle de vie de développement de logiciels. Dépendant de l'architecture basée sur Router.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add catlog22/maestro-flow/team-lifecycle-v4. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use team-lifecycle-v4 immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

team-lifecycle-v4

Install team-lifecycle-v4, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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 -> STOP
                                 |
                    +--------+---+--------+
                    v        v            v
             [team-worker]  ...    [team-supervisor]
              per-task               resident agent
              lifecycle              message-driven
                                     (woken via SendMessage)

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 -> Read roles/coordinator/role.md, execute entry router

Shared Constants

  • Session prefix: TLV4
  • Session path: .workflow/.team/TLV4-<slug>-<date>/
  • CLI tools: ccw cli --mode analysis (read-only), ccw cli --mode write (modifications)
  • Message bus: mcp__ccw-tools__team_msg(session_id=<session-id>, ...)

Worker Spawn Template

Coordinator spawns workers using this template:

Agent({
  subagent_type: "team-worker",
  description: "Spawn <role> worker",
  team_name: <team-name>,
  name: "<role>",
  run_in_background: true,
  prompt: `## Role Assignment
role: <role>
role_spec: <project>/.claude/skills/team-lifecycle-v4/roles/<role>/role.md
session: <session-folder>
session_id: <session-id>
team_name: <team-name>
requirement: <task-description>
inner_loop: <true|false>

Read role_spec file to load Phase 2-4 domain instructions.
Execute built-in Phase 1 (task discovery) -> role Phase 2-4 -> built-in Phase 5 (report).`
})

Supervisor Spawn Template

Supervisor is a resident agent (independent from team-worker). Spawned once during session init, woken via SendMessage for each CHECKPOINT task.

Spawn (Phase 2 -- once per session)

Agent({
  subagent_type: "team-supervisor",
  description: "Spawn resident supervisor",
  team_name: <team-name>,
  name: "supervisor",
  run_in_background: true,
  prompt: `## Role Assignment
role: supervisor
role_spec: <project>/.claude/skills/team-lifecycle-v4/roles/supervisor/role.md
session: <session-folder>
session_id: <session-id>
team_name: <team-name>
requirement: <task-description>

Read role_spec file to load checkpoint definitions.
Init: load baseline context, report ready, go idle.
Wake cycle: coordinator sends checkpoint requests via SendMessage.`
})

Wake (handleSpawnNext -- per CHECKPOINT task)

SendMessage({
  type: "message",
  recipient: "supervisor",
  content: `## Checkpoint Request
task_id: <CHECKPOINT-NNN>
scope: [<upstream-task-ids>]
pipeline_progress: <done>/<total> tasks completed`,
  summary: "Checkpoint request: <CHECKPOINT-NNN>"
})

Shutdown (handleComplete)

SendMessage({
  type: "shutdown_request",
  recipient: "supervisor",
  content: "Pipeline complete, shutting down supervisor"
})

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

Completion Action

When pipeline completes, coordinator presents:

AskUserQuestion({
  questions: [{
    question: "Pipeline complete. What would you like to do?",
    header: "Completion",
    multiSelect: false,
    options: [
      { label: "Archive & Clean (Recommended)", description: "Archive session, clean up team" },
      { 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-<slug>-<date>/
+-- team-session.json           # Session state + role registry
+-- spec/                       # Spec phase outputs
+-- plan/                       # Implementation plan + TASK-*.json
+-- artifacts/                  # All deliverables
+-- wisdom/                     # Cross-task knowledge
+-- explorations/               # Shared explore cache
+-- discussions/                # Discuss round records
+-- .msg/                       # Team message bus

Error Handling

ScenarioResolution
Unknown commandError with available command list
Role not foundError with role registry
CLI tool failsWorker fallback to direct implementation
Fast-advance conflictCoordinator reconciles on next callback
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

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