maestro-help
Maestro Flow 命令帮助系统。搜索命令、浏览技能、工作流推荐、新手引导。Triggers on "maestro-help", "帮助", "命令", "怎么用", "skill", "workflow", "maestro 怎么用".
Universal team coordination skill with dynamic role generation. Uses team-worker agent architecture with role-spec files. Only coordinator is built-in -- all worker roles are generated at runtime as role-specs and spawned via team-worker agent. Beat/cadence model for
Claude Code
$ npx -y skills add catlog22/maestro-flow --skill team-coordinate --agent claude-code
Codex
$ npx skills add catlog22/maestro-flow --skill team-coordinate -a codex -y
Cursor
$ npx skills add catlog22/maestro-flow --skill team-coordinate -a cursor -y
Gemini CLI
$ npx skills add catlog22/maestro-flow --skill team-coordinate -a gemini-cli -y
GitHub Copilot
$ npx skills add catlog22/maestro-flow --skill team-coordinate -a github-copilot -y
OpenCode
$ npx skills add catlog22/maestro-flow --skill team-coordinate -a opencode -y
Windsurf
$ npx skills add catlog22/maestro-flow --skill team-coordinate -a windsurf -y
name: team-coordinate disable-model-invocation: true description: Universal team coordination skill with dynamic role generation. Uses team-worker agent architecture with role-spec files. Only coordinator is built-in -- all worker roles are generated at runtime as role-specs and spawned via team-worker agent. Beat/cadence model for orchestration. Triggers on "Team Coordinate ". allowed-tools: TeamCreate(*), TeamDelete(*), SendMessage(*), TaskCreate(*), TaskUpdate(*), TaskList(*), TaskGet(*), Agent(*), AskUserQuestion(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), mcp__maestro__team_msg(*) session-mode: run
<required_reading> @~/.maestro/workflows/run-mode-lite.md </required_reading>
Universal team coordination skill: analyze task -> generate role-specs -> dispatch -> execute -> deliver. Only the **coordinator** is built-in. All worker roles are **dynamically generated** as lightweight role-spec files and spawned via the `team-worker` agent.
+---------------------------------------------------+
| Skill(skill="team-coordinate") |
| args="task description" |
+-------------------+-------------------------------+
|
Orchestration Mode (auto -> coordinator)
|
Coordinator (built-in)
Phase 0-5 orchestration
|
+-------+-------+-------+-------+
v v v v v
[team-worker agents, each loaded with a dynamic role-spec]
(roles generated at runtime from task analysis)
CLI Tools (callable by any worker):
maestro delegate --mode analysis - analysis and exploration
maestro delegate --mode write - code generation and modification| Constant | Value | |----------|-------| | Session prefix | `TC` | | Session path | `{run_dir}/work/team/` | | Worker agent | `team-worker` | | Message bus | `mcp__maestro__team_msg(session_id=<run-id>, ...)` | | CLI analysis | `maestro delegate --mode analysis` | | CLI write | `maestro delegate --mode write` | | Max roles | 5 |
This skill is **coordinator-only**. Workers do NOT invoke this skill -- they are spawned as `team-worker` agents directly.
Parse `$ARGUMENTS`. No `--role` needed -- always routes to coordinator.
Only coordinator is statically registered. All other roles are dynamic, stored as role-specs in session.
| Role | File | Type | |------|------|------| | coordinator | [roles/coordinator/role.md](roles/coordinator/role.md) | built-in orchestrator | | (dynamic) | `{run_dir}/work/team/role-specs/<role-name>.md` | runtime-generated role-spec |
Workers can use CLI tools for analysis and code operations:
| Tool | Purpose | |------|---------| | maestro delegate --mode analysis | Analysis, exploration, pattern discovery | | maestro delegate --mode write | Code generation, modification, refactoring |
Always route to coordinator. Coordinator reads `roles/coordinator/role.md` and executes its phases.
User just provides task description.
**Invocation**: `Skill(skill="team-coordinate", args="task description")`
**Lifecycle**:
User provides task description -> coordinator Phase 1: task analysis (detect capabilities, build dependency graph) -> coordinator Phase 2: generate role-specs + initialize session -> coordinator Phase 3: create task chain from dependency graph -> coordinator Phase 4: spawn first batch workers (background) -> STOP -> Worker executes -> SendMessage callback -> coordinator advances next step -> Loop until pipeline complete -> Phase 5 report + completion action
**User Commands** (wake paused coordinator):
| Command | Action | |---------|--------| | `check` / `status` | Output execution status graph, no advancement | | `resume` / `continue` | Check worker states, advance next step | | `revise <TASK-ID> [feedback]` | Revise specific task with optional feedback | | `feedback <text>` | Inject feedback into active pipeline | | `improve [dimension]` | Auto-improve weakest quality dimension |
---
When coordinator spawns workers, use `team-worker` agent with role-spec path:
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: {run_dir}/work/team/role-specs/<role>.md
session: {run_dir}/work/team
session_id: <run-id>
team_name: <team-name>
requirement: <task-description>
inner_loop: <true|false>
## Progress Milestones
session_id: <run-id>
Report progress via team_msg at natural phase boundaries (context loaded -> core work done -> verification).
Report blockers immediately via team_msg type="blocker".
Report completion via team_msg type="task_complete" after final SendMessage.
Read role_spec file to load Phase 2-4 domain instructions.
Execute built-in Phase 1 (task discovery) -> role-spec Phase 2-4 -> built-in Phase 5 (report).`
})**Inner Loop roles** (role has 2+ serial same-prefix tasks): Set `inner_loop: true`. The team-worker agent handles the loop internally.
**Single-task roles**: Set `inner_loop: false`.
---
When pipeline completes (all tasks done), coordinator presents an interactive choice:
AskUserQuestion({
questions: [{
question: "Team 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, then clean" }
]
}]
})| Choice | Steps | |-----
Intent-driven workflow orchestration for multi-agent AI development — adaptive lifecycle engine, self-reinforcing knowledge graph, and visual dashboard for Claude Code, Gemini, Codex & more
Maestro Flow 命令帮助系统。搜索命令、浏览技能、工作流推荐、新手引导。Triggers on "maestro-help", "帮助", "命令", "怎么用", "skill", "workflow", "maestro 怎么用".
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