Team Perf Opt

Agent timeout: spawn_agent 异步执行且无内置超时 — 除明确短任务外一律 spawn_agent 后立即 wait_agent({ timeout_ms: 3600000 })（上限 1 小时）阻塞等待，绝不依赖 30000 默认值；timed_out: true 且 Agent 未完成时再次 wait_agent 续等，不丢弃。批量场景使用 spawn_agents_on_csv({ max_runtime_seconds: 3600, ... })。

Team Performance Optimization

Profile application performance, identify bottlenecks, design optimization strategies, implement changes, benchmark improvements, and review code quality.

Architecture

spawn_agent({ task_name: "team_perf_opt", message: "Execute skill team-perf-opt, 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 workers -> STOP
                                    |
                    +-------+-------+-------+-------+-------+
                    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 Registry

Pre-load (coordinator, before dispatch)

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

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

Shared Constants

• Session prefix: PERF-OPT
• Session path: {run_dir}/work/team/
• Team name: perf-opt
• CLI tools: maestro delegate --mode analysis (read-only), maestro delegate --mode write (modifications)
• Message bus: mcp__maestro__team_msg(session_id=<run-id>, ...)

Worker Spawn Template

Coordinator spawns workers using this template:

spawn_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 send_message.

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.

User Commands

Session Directory

{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.jsonl             # Team message bus
+-- .msg/meta.json                  # Session metadata

Completion Action

When the pipeline completes:

request_user_input({
  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 tasks and team resources" },
      { label: "Keep Active", description: "Keep session active for follow-up work or inspection" },
      { label: "Export Results", description: "Export deliverables to a specified location, then clean" }
    ]
  }]
})

Specs Reference

• specs/pipelines.md — Pipeline definitions and task registry
• specs/team-config.json — Team configuration

Error Handling