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".
Unified team skill for performance optimization. Coordinator orchestrates pipeline, workers are team-worker agents. Supports single/fan-out/independent parallel modes. Triggers on "team perf-opt".
$ npx -y skills add catlog22/maestro-flow --skill team-perf-opt --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/team-perf-optContext preview
The summary Claude sees to decide when to auto-load this skill.
Unified team skill for performance optimization. Coordinator orchestrates pipeline, workers are team-worker agents. Supports single/fan-out/independent parallel modes. Triggers on "team perf-opt".
name: team-perf-opt disable-model-invocation: true description: Unified team skill for performance optimization. Coordinator orchestrates pipeline, workers are team-worker agents. Supports single/fan-out/independent parallel modes. Triggers on "team perf-opt". allowed-tools: Agent, TaskCreate, TaskList, TaskGet, TaskUpdate, TeamCreate, TeamDelete, SendMessage, AskUserQuestion, Read, Write, Edit, Bash, Glob, Grep, mcp__maestro__team_msg session-mode: run
<required_reading> @~/.maestro/workflows/run-mode-lite.md </required_reading>
Profile application performance, identify bottlenecks, design optimization strategies, implement changes, benchmark improvements, and review code quality.
Skill(skill="team-perf-opt", args="<task-description>")
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SKILL.md (this file) = Router
|
+--------------+--------------+
| |
no --role flag --role <name>
| |
Coordinator Worker
roles/coordinator/role.md roles/<name>/role.md
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+-- analyze -> dispatch -> spawn workers -> STOP
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+-------+-------+-------+-------+-------+
v v v v v
[profiler] [strategist] [optimizer] [benchmarker] [reviewer]
(team-worker agents)
Pipeline (Single mode):
PROFILE-001 -> STRATEGY-001 -> IMPL-001 -> BENCH-001 + REVIEW-001 (fix cycle)
Pipeline (Fan-out mode):
PROFILE-001 -> STRATEGY-001 -> [IMPL-B01..N](parallel) -> BENCH+REVIEW per branch
Pipeline (Independent mode):
[Pipeline A: PROFILE-A->STRATEGY-A->IMPL-A->BENCH-A+REVIEW-A]
[Pipeline B: PROFILE-B->STRATEGY-B->IMPL-B->BENCH-B+REVIEW-B] (parallel)| Role | Path | Prefix | Inner Loop | |------|------|--------|------------| | coordinator | [roles/coordinator/role.md](roles/coordinator/role.md) | — | — | | profiler | [roles/profiler/role.md](roles/profiler/role.md) | PROFILE-* | false | | strategist | [roles/strategist/role.md](roles/strategist/role.md) | STRATEGY-* | false | | optimizer | [roles/optimizer/role.md](roles/optimizer/role.md) | IMPL-*, FIX-* | true | | benchmarker | [roles/benchmarker/role.md](roles/benchmarker/role.md) | BENCH-* | false | | reviewer | [roles/reviewer/role.md](roles/reviewer/role.md) | REVIEW-*, QUALITY-* | false |
1. **Codebase docs**: If `.workflow/codebase/ARCHITECTURE.md` exists, read for module boundaries 2. **Specs (coding)**: `maestro load --type spec --category coding` — load coding constraints as shared context 3. **Wiki knowledge**: `maestro search "performance optimization profiling" --json` — top 5 entries as prior context 4. All optional — proceed without if unavailable
Parse `$ARGUMENTS`:
Coordinator spawns workers using this template:
Agent({
subagent_type: "team-worker",
description: "Spawn <role> worker",
team_name: "perf-opt",
name: "<role>",
run_in_background: true,
prompt: `## Role Assignment
role: <role>
role_spec: <skill_root>/roles/<role>/role.md
session: {run_dir}/work/team
session_id: <run-id>
team_name: perf-opt
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 (@<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).`
})**Inner Loop roles** (optimizer): Set `inner_loop` dynamically — `true` for single mode, `false` for fan-out/independent (parallel branches). **Single-task roles** (profiler, strategist, benchmarker, reviewer): Set `inner_loop: false`.
| Command | Action | |---------|--------| | `check` / `status` | Output execution status graph (branch-grouped), no advancement | | `resume` / `continue` | Check worker states, advance next step | | `revise <TASK-ID> [feedback]` | Create revision task + cascade downstream (scoped to branch) | | `feedback <text>` | Analyze feedback impact, create targeted revision chain | | `recheck` | Re-run quality check | | `improve [dimension]` | Auto-improve weakest dimension |
{run_dir}/work/team/
+-- team-session.json # Session metadata + status + parallel_mode
+-- {run_dir}/outputs/ # Run deliverables (via maestro run)
| +-- baseline-metrics.json # Profiler: before-optimization metrics
| +-- bottleneck-report.md # Profiler: ranked bottleneck findings
| +-- optimization-plan.md # Strategist: prioritized optimization plan
| +-- benchmark-results.json # Benchmarker: after-optimization metrics
| +-- review-report.md # Reviewer: code review findings
| +-- branches/B01/... # Fan-out branch artifacts
| +-- pipelines/A/... # Independent pipeline artifacts
+-- explorations/ # Shared explore cache
+-- wisdom/patterns.md # Discovered patterns and conventions
+-- {run_dir}/evidence/discussions/ # Discussion records
+-- .msg/messages.jsonlIntent-driven workflow orchestration for multi-agent AI development — adaptive lifecycle engine, self-reinforcing knowledge graph, and visual dashboard for Claude Code, Gemini, Codex & more
Repo: catlog22/maestro-flow
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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