refactor: deep Codex v4 API conversion for all 20 team skills

Upgrade all team-* skills from mechanical v3→v4 API renames to deep
v4 tool integration with skill-adaptive patterns:

- list_agents: health checks in handleResume, cleanup verification in
  handleComplete, added to allowed-tools and coordinator toolbox
- Named targeting: task_name uses task-id (e.g. EXPLORE-001) instead
  of generic <role>-worker, enabling send_message/assign_task by name
- Message semantics: send_message for supplementary cross-agent context
  vs assign_task for triggering work, with skill-specific examples
- Model selection: per-role reasoning_effort guidance matching each
  skill's actual roles (not generic boilerplate)
- timeout_ms: added to all wait_agent calls, timed_out handling in
  all 18 monitor.md files
- Skill-adaptive v4 sections: ultra-analyze N-parallel coordination,
  lifecycle-v4 supervisor assign_task/send_message distinction,
  brainstorm ideator parallel patterns, iterdev generator-critic loops,
  frontend-debug iterative debug assign_task, perf-opt benchmark
  context sharing, executor lightweight trimmed v4, etc.

60 files changed across 20 team skills (SKILL.md, monitor.md, role.md)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
catlog22
2026-03-27 22:25:32 +08:00
parent 3d39ac6ac8
commit 88ea7fc6d7
60 changed files with 2318 additions and 215 deletions

View File

@@ -1,7 +1,7 @@
---
name: team-ultra-analyze
description: Deep collaborative analysis team skill. All roles route via this SKILL.md. Beat model is coordinator-only (monitor.md). Structure is roles/ + specs/. Triggers on "team ultra-analyze", "team analyze".
allowed-tools: spawn_agent(*), wait_agent(*), send_input(*), close_agent(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*)
allowed-tools: 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(*)
---
# Team Ultra Analyze
@@ -62,7 +62,8 @@ Before calling ANY tool, apply this check:
| Tool Call | Verdict | Reason |
|-----------|---------|--------|
| `spawn_agent`, `wait_agent`, `close_agent`, `send_input` | ALLOWED | Orchestration |
| `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 |
@@ -93,6 +94,8 @@ 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>
@@ -116,7 +119,29 @@ pipeline_phase: <pipeline-phase>` },
})
```
After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ id })` each worker.
After spawning, use `wait_agent({ targets: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ target })` each worker.
### Model Selection Guide
| Role | model | reasoning_effort | Rationale |
|------|-------|-------------------|-----------|
| Explorer (EXPLORE-*) | (default) | medium | File reading and pattern scanning, less reasoning needed |
| Analyst (ANALYZE-*) | (default) | high | Deep analysis requires full reasoning |
| Discussant (DISCUSS-*) | (default) | high | Synthesis of multiple viewpoints, dialectic reasoning |
| Synthesizer (SYNTH-*) | (default) | medium | Aggregation and summary over generation |
Override model/reasoning_effort in spawn_agent when cost optimization is needed:
```
spawn_agent({
agent_type: "team_worker",
task_name: "<task-id>",
fork_context: false,
model: "<model-override>",
reasoning_effort: "<effort-level>",
items: [...]
})
```
## User Commands
@@ -148,6 +173,51 @@ After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect
| +-- issues.md
```
## v4 Agent Coordination
### Message Semantics
| Intent | API | Example |
|--------|-----|---------|
| Send exploration findings to running analysts | `send_message` | Queue upstream context without interrupting ANALYZE-* workers |
| Not used in this skill | `assign_task` | No resident agents -- all workers are one-shot |
| Check running agents | `list_agents` | Verify parallel explorer/analyst health during resume |
### Parallel Phase Coordination
Standard/Deep modes spawn N parallel agents in EXPLORE and ANALYZE phases. Use batch spawn + wait:
```
// EXPLORE phase: spawn N explorers in parallel
const explorerNames = ["EXPLORE-001", "EXPLORE-002", ..., "EXPLORE-00N"]
for (const name of explorerNames) {
spawn_agent({ agent_type: "team_worker", task_name: name, ... })
}
wait_agent({ targets: explorerNames, timeout_ms: 900000 })
// Collect all results, then spawn ANALYZE phase
// ANALYZE phase: send exploration context to analysts via items (not send_message)
// since analysts are spawned AFTER explorers complete
```
### Agent Health Check
Use `list_agents({})` in handleResume and handleComplete:
```
// Reconcile session state with actual running agents
const running = list_agents({})
// Compare with tasks.json active_agents
// Reset orphaned tasks (in_progress but agent gone) to pending
// Critical for parallel phases -- multiple agents may crash independently
```
### Named Agent Targeting
Workers are spawned with `task_name: "<task-id>"` enabling direct addressing:
- `send_message({ target: "ANALYZE-001", items: [...] })` -- queue supplementary exploration findings
- `close_agent({ target: "EXPLORE-001" })` -- cleanup by name after wait_agent returns
## Completion Action
When pipeline completes, coordinator presents: