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".
62
53%
Does it follow best practices?
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Optimize this skill with Tessl
npx tessl skill review --optimize ./.codex/skills/team-ultra-analyze/SKILL.mdDeep collaborative analysis: explore -> analyze -> discuss -> synthesize. Supports Quick/Standard/Deep pipeline modes with configurable depth (N parallel agents). Discussion loops enable user-guided progressive understanding.
Skill(skill="team-ultra-analyze", args="<topic>")
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SKILL.md (this file) = Router
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+--------------+--------------+
| |
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
[team-worker agents, each loads roles/<role>/role.md]
Pipeline (Standard mode):
[EXPLORE-1..N](parallel) -> [ANALYZE-1..N](parallel) -> DISCUSS-001 -> SYNTH-001
Pipeline (Deep mode):
[EXPLORE-1..N] -> [ANALYZE-1..N] -> DISCUSS-001 -> ANALYZE-fix -> DISCUSS-002 -> ... -> SYNTH-001
Pipeline (Quick mode):
EXPLORE-001 -> ANALYZE-001 -> SYNTH-001| Role | Path | Prefix | Inner Loop |
|---|---|---|---|
| coordinator | roles/coordinator/role.md | — | — |
| explorer | roles/explorer/role.md | EXPLORE-* | false |
| analyst | roles/analyst/role.md | ANALYZE-* | false |
| discussant | roles/discussant/role.md | DISCUSS-* | false |
| synthesizer | roles/synthesizer/role.md | SYNTH-* | false |
Parse $ARGUMENTS:
--role <name> → Read roles/<name>/role.md, execute Phase 2-4--role → roles/coordinator/role.md, execute entry routerCoordinator 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.
UAN.workflow/.team/UAN-<slug>-<date>/ultra-analyzeccw cli --mode analysis (read-only), ccw cli --mode write (modifications)mcp__ccw-tools__team_msg(session_id=<session-id>, ...)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: <topic-description>
inner_loop: 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.
| 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: [...]
})| Command | Action |
|---|---|
check / status | Output execution status diagram, do not advance pipeline |
resume / continue | Check worker status, advance to next pipeline step |
.workflow/.team/UAN-{slug}-{YYYY-MM-DD}/
+-- .msg/messages.jsonl # Message bus log
+-- .msg/meta.json # Session metadata + cross-role state
+-- discussion.md # Understanding evolution and discussion timeline
+-- explorations/ # Explorer output
| +-- exploration-001.json
| +-- exploration-002.json
+-- analyses/ # Analyst output
| +-- analysis-001.json
| +-- analysis-002.json
+-- discussions/ # Discussant output
| +-- discussion-round-001.json
+-- conclusions.json # Synthesizer output
+-- wisdom/ # Cross-task knowledge
| +-- learnings.md
| +-- decisions.md
| +-- conventions.md
| +-- issues.md| 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 |
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 completeUse 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 independentlyWorkers are spawned with task_name: "<task-id>" enabling direct addressing:
send_message({ target: "ANALYZE-001", items: [...] }) -- queue supplementary exploration findingsclose_agent({ target: "EXPLORE-001" }) -- cleanup by name after wait_agent returnsWhen pipeline completes, coordinator presents:
request_user_input({
questions: [{
question: "Ultra-Analyze 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" }
]
}]
})| Choice | Action |
|---|---|
| Archive & Clean | Update session status="completed" -> output final summary |
| Keep Active | Update session status="paused" -> output resume instructions |
| Export Results | request_user_input for target path -> copy deliverables -> Archive & Clean |
| Scenario | Resolution |
|---|---|
| Unknown --role value | Error with role registry list |
| Role file not found | Error with expected path (roles/{name}/role.md) |
| Discussion loop stuck >5 rounds | Force synthesis, offer continuation |
| CLI tool unavailable | Fallback chain: gemini -> codex -> manual analysis |
| Explorer agent fails | Continue with available context, note limitation |
| Fast-advance conflict | Coordinator reconciles on next callback |
| Completion action fails | Default to Keep Active |
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