Claude-Code-Workflow/.codex/skills/team-perf-opt/SKILL.md

name, description, allowed-tools

name	description	allowed-tools
team-perf-opt	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".	spawn_agent(*), wait_agent(*), send_message(*), assign_task(*), close_agent(*), list_agents(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), mcp__ace-tool__search_context(*)

Team Performance Optimization

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

Architecture

Skill(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

Role	Path	Prefix	Inner Loop
coordinator	roles/coordinator/role.md	—	—
profiler	roles/profiler/role.md	PROFILE-*	false
strategist	roles/strategist/role.md	STRATEGY-*	false
optimizer	roles/optimizer/role.md	IMPL-, FIX-	true
benchmarker	roles/benchmarker/role.md	BENCH-*	false
reviewer	roles/reviewer/role.md	REVIEW-, QUALITY-	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 Call	Verdict	Reason
spawn_agent, wait_agent, close_agent, send_message, assign_task	ALLOWED	Orchestration
list_agents	ALLOWED	Agent health check
request_user_input	ALLOWED	User interaction
mcp__ccw-tools__team_msg	ALLOWED	Message bus
Read/Write on .workflow/.team/ files	ALLOWED	Session state
Read on roles/, commands/, specs/	ALLOWED	Loading own instructions
Read/Grep/Glob on project source code	BLOCKED	Delegate to worker
Edit on any file outside .workflow/	BLOCKED	Delegate to worker
Bash("ccw cli ...")	BLOCKED	Only workers call CLI
Bash running build/test/lint commands	BLOCKED	Delegate 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: PERF-OPT
• Session path: .workflow/.team/PERF-OPT-<slug>-<date>/
• Team name: perf-opt
• 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:

spawn_agent({
  agent_type: "team_worker",
  task_name: "<task-id>",
  fork_context: false,
  items: [
    { type: "text", text: `## 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.` },

    { type: "text", text: `## Task Context
task_id: <task-id>
title: <task-title>
description: <task-description>
pipeline_phase: <pipeline-phase>` },

    { type: "text", text: `## Upstream Context
<prev_context>` }
  ]
})

After spawning, use wait_agent({ targets: [...], timeout_ms: 900000 }) to collect results, then close_agent({ target }) each worker.

Inner Loop roles (optimizer): Set inner_loop: true. Single-task roles (profiler, strategist, benchmarker, reviewer): Set inner_loop: false.

Model Selection Guide

Performance optimization is measurement-driven. Profiler and benchmarker need consistent context for before/after comparison.

Role	reasoning_effort	Rationale
profiler	high	Must identify subtle bottlenecks from profiling data
strategist	high	Optimization strategy requires understanding tradeoffs
optimizer	high	Performance-critical code changes need precision
benchmarker	medium	Benchmark execution follows defined measurement plan
reviewer	high	Must verify optimizations don't introduce regressions

Benchmark Context Sharing with fork_context

For before/after comparison, benchmarker should share context with profiler's baseline:

spawn_agent({
  agent_type: "team_worker",
  task_name: "BENCH-001",
  fork_context: true,   // Share context so benchmarker sees profiler's baseline metrics
  reasoning_effort: "medium",
  items: [...]
})

User Commands

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

Session Directory

.workflow/.team/PERF-OPT-<slug>-<date>/
+-- session.json                    # Session metadata + status + parallel_mode
+-- artifacts/
|   +-- 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
+-- discussions/                    # Discussion records
+-- .msg/messages.jsonl             # Team message bus
+-- .msg/meta.json                  # Session metadata

v4 Agent Coordination

Message Semantics

Intent	API	Example
Queue supplementary info (don't interrupt)	send_message	Send baseline metrics to running optimizer
Assign fix after benchmark regression	assign_task	Assign FIX task when benchmark shows regression
Check running agents	list_agents	Verify agent health during resume

Agent Health Check

Use list_agents({}) in handleResume and handleComplete:

// Reconcile session state with actual running agents
const running = list_agents({})
// Compare with session.json active tasks
// Reset orphaned tasks (in_progress but agent gone) to pending

Named Agent Targeting

Workers are spawned with task_name: "<task-id>" enabling direct addressing:

• send_message({ target: "IMPL-001", items: [...] }) -- send strategy details to optimizer
• assign_task({ target: "IMPL-001", items: [...] }) -- assign fix after benchmark regression
• close_agent({ target: "BENCH-001" }) -- cleanup after benchmarking completes

Baseline-to-Result Pipeline

Profiler baseline metrics flow through the pipeline and must reach benchmarker for comparison:

1. PROFILE-001 produces baseline-metrics.json in artifacts/
2. Coordinator includes baseline reference in upstream context for all downstream workers
3. BENCH-001 reads baseline and compares against post-optimization measurements
4. If regression detected, coordinator auto-creates FIX task with regression details

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

Scenario	Resolution
Unknown --role value	Error with role registry list
Role file not found	Error with expected path (roles/{name}/role.md)
Profiling tool not available	Fallback to static analysis methods
Benchmark regression detected	Auto-create FIX task with regression details
Review-fix cycle exceeds 3 iterations	Escalate to user
One branch IMPL fails	Mark that branch failed, other branches continue
Fast-advance conflict	Coordinator reconciles on next callback
Completion action fails	Default to Keep Active