team-coordinate

name	team-coordinate
description	Universal team coordination skill with dynamic role generation. Uses team-worker agent architecture with role-spec files. Only coordinator is built-in -- all worker roles are generated at runtime as role-specs and spawned via team-worker agent. Beat/cadence model for orchestration. Triggers on "Team Coordinate ".
allowed-tools	spawn_agent(*), wait_agent(*), send_message(*), followup_task(*), close_agent(*), list_agents(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), mcp__ccw-tools__team_msg(*)

Team Coordinate

Universal team coordination skill: analyze task -> generate role-specs -> dispatch -> execute -> deliver. Only the coordinator is built-in. All worker roles are dynamically generated as lightweight role-spec files and spawned via the team-worker agent.

Architecture

+---------------------------------------------------+
|  Skill(skill="team-coordinate")                 |
|  args="task description"                           |
+-------------------+-------------------------------+
                    |
         Orchestration Mode (auto -> coordinator)
                    |
              Coordinator (built-in)
              Phase 0-5 orchestration
                    |
    +-------+-------+-------+-------+
    v       v       v       v       v
 [team-worker agents, each loaded with a dynamic role-spec]
  (roles generated at runtime from task analysis)

  CLI Tools (callable by any worker):
    ccw cli --mode analysis  - analysis and exploration
    ccw cli --mode write     - code generation and modification

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, followup_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. The overhead is the feature — it provides session tracking, artifact persistence, and resume capability.

---

Shared Constants

Constant	Value
Session prefix	TC
Session path	.workflow/.team/TC-<date>-<slug>/
Worker agent	team-worker
Message bus	mcp__ccw-tools__team_msg(session_id=<session-id>, ...)
CLI analysis	ccw cli --mode analysis
CLI write	ccw cli --mode write
Max roles	5

Role Router

This skill is coordinator-only. Workers do NOT invoke this skill -- they are spawned as team-worker agents directly.

Input Parsing

Parse $ARGUMENTS. No --role needed -- always routes to coordinator.

Role Registry

Only coordinator is statically registered. All other roles are dynamic, stored as role-specs in session.

Role	File	Type
coordinator	roles/coordinator/role.md	built-in orchestrator
(dynamic)	<session>/role-specs/<role-name>.md	runtime-generated role-spec

CLI Tool Usage

Workers can use CLI tools for analysis and code operations:

Tool	Purpose
ccw cli --mode analysis	Analysis, exploration, pattern discovery
ccw cli --mode write	Code generation, modification, refactoring

Dispatch

Always route to coordinator. Coordinator reads roles/coordinator/role.md and executes its phases.

Orchestration Mode

User just provides task description.

Invocation: Skill(skill="team-coordinate", args="task description")

Lifecycle:

User provides task description
  -> coordinator Phase 1: task analysis (detect capabilities, build dependency graph)
  -> coordinator Phase 2: generate role-specs + initialize session
  -> coordinator Phase 3: create task chain from dependency graph
  -> coordinator Phase 4: spawn first batch workers (background) -> STOP
  -> Worker executes -> callback -> coordinator advances next step
  -> Loop until pipeline complete -> Phase 5 report + completion action

User Commands (wake paused coordinator):

Command	Action
check / status	Output execution status graph, no advancement
resume / continue	Check worker states, advance next step
revise <TASK-ID> [feedback]	Revise specific task with optional feedback
feedback <text>	Inject feedback into active pipeline
improve [dimension]	Auto-improve weakest quality dimension

---

Coordinator Spawn Template

v2 Worker Spawn (all roles)

When coordinator spawns workers, use team-worker agent with role-spec path:

spawn_agent({
  agent_type: "team_worker",
  task_name: "<task-id>",
  fork_turns: "none",
  message: `## Role Assignment
role: <role>
role_spec: <session-folder>/role-specs/<role>.md
session: <session-folder>
session_id: <session-id>
requirement: <task-description>
inner_loop: <true|false>

Read role_spec file to load Phase 2-4 domain instructions.

## Task Context
task_id: <task-id>
title: <task-title>
description: <task-description>
pipeline_phase: <pipeline-phase>

## Upstream Context
<prev_context>`
})

After spawning, use wait_agent({ timeout_ms: 1800000 }) to collect results. If result.timed_out, send STATUS_CHECK via followup_task (wait 3 min), then FINALIZE with interrupt (wait 3 min), then mark timed_out and close agents. Use close_agent({ target: <name> }) each worker.

Inner Loop roles (role has 2+ serial same-prefix tasks): Set inner_loop: true. The team-worker agent handles the loop internally.

Single-task roles: Set inner_loop: false.

---

Model Selection Guide

Roles are dynamically generated at runtime. Select model/reasoning_effort based on the generated role's responsibility_type:

responsibility_type	model	reasoning_effort	Rationale
exploration	(default)	medium	Read-heavy, less reasoning needed
analysis	(default)	high	Deep analysis requires full reasoning
implementation	(default)	high	Code generation needs precision
synthesis	(default)	medium	Aggregation over generation
review	(default)	high	Quality assessment needs deep reasoning

Map each generated role's responsibility_type (from team-session.json#roles) to the table above.

Override model/reasoning_effort in spawn_agent when cost optimization is needed:

spawn_agent({
  agent_type: "team_worker",
  task_name: "<task-id>",
  fork_turns: "none",
  model: "<model-override>",
  reasoning_effort: "<effort-level>",
  message: "..."
})

v4 Agent Coordination

Message Semantics

Intent	API	Example
Queue supplementary info (don't interrupt)	send_message	Send upstream task findings to a running downstream worker
Not used in this skill	followup_task	No resident agents -- all workers are one-shot
Check running agents	list_agents	Verify agent health during resume

Note: Since roles are dynamically generated, the coordinator must resolve task prefixes and role names from team-session.json#roles at runtime. There are no hardcoded role-specific examples.

fork_turns Strategy

fork_turns: "none" is the default. Consider fork_turns: "all" only when:

• Runtime analysis reveals the task requires deep familiarity with the full conversation context
• The dynamically-generated role-spec indicates the worker needs project-wide understanding
• The coordinator has already accumulated significant context about the codebase

This decision should be made per-task during Phase 4 based on the role's responsibility_type.

Agent Health Check

Use list_agents({}) in handleResume and handleComplete:

// Reconcile session state with actual running agents
const running = list_agents({})
// Compare with team-session.json active_workers
// 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: "<TASK-ID>", message: "..." }) -- queue upstream context without interrupting
• close_agent({ target: "<TASK-ID>" }) -- cleanup by name

Completion Action

When pipeline completes (all tasks done), coordinator presents an interactive choice:

functions.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 team" },
      { label: "Keep Active", description: "Keep session for follow-up work" },
      { label: "Export Results", description: "Export deliverables to target directory, then clean" }
    ]
  }]
})

Action Handlers

Choice	Steps
Archive & Clean	Update session status="completed" -> output final summary with artifact paths
Keep Active	Update session status="paused" -> output: "Resume with: Skill(skill='team-coordinate', args='resume')"
Export Results	functions.request_user_input(target path) -> copy artifacts to target -> Archive & Clean

---

Specs Reference

Spec	Purpose
specs/pipelines.md	Dynamic pipeline model, task naming, dependency graph
specs/role-spec-template.md	Template for dynamic role-spec generation
specs/quality-gates.md	Quality thresholds and scoring dimensions
specs/knowledge-transfer.md	Context transfer protocols between roles

---

Session Directory

.workflow/.team/TC-<date>-<slug>/
+-- team-session.json           # Session state + dynamic role registry
+-- task-analysis.json          # Phase 1 output: capabilities, dependency graph
+-- role-specs/                 # Dynamic role-spec definitions (generated Phase 2)
|   +-- <role-1>.md             # Lightweight: frontmatter + Phase 2-4 only
|   +-- <role-2>.md
+-- artifacts/                  # All MD deliverables from workers
|   +-- <artifact>.md
+-- .msg/                       # Team message bus + state
|   +-- messages.jsonl          # Message log
|   +-- meta.json               # Session metadata + cross-role state
+-- wisdom/                     # Cross-task knowledge
|   +-- learnings.md
|   +-- decisions.md
|   +-- issues.md
+-- explorations/               # Shared explore cache
|   +-- cache-index.json
|   +-- explore-<angle>.json
+-- discussions/                # Inline discuss records
|   +-- <round>.md

team-session.json Schema

{
  "session_id": "TC-<date>-<slug>",
  "task_description": "<original user input>",
  "status": "active | paused | completed",
  "team_name": "<team-name>",
  "roles": [
    {
      "name": "<role-name>",
      "prefix": "<PREFIX>",
      "responsibility_type": "<type>",
      "inner_loop": false,
      "role_spec": "role-specs/<role-name>.md"
    }
  ],
  "pipeline": {
    "dependency_graph": {},
    "tasks_total": 0,
    "tasks_completed" 
  
   
   
   
   

---

Session Resume

Coordinator supports resume / continue for interrupted sessions:

1. Scan .workflow/.team/TC-*/team-session.json for active/paused sessions
2. Multiple matches -> request_user_input for selection
3. Audit task states -> reconcile session state <-> task status
4. Reset in_progress -> pending (interrupted tasks)
5. Rebuild team and spawn needed workers only
6. Create missing tasks, set dependencies
7. Kick first executable task -> Phase 4 coordination loop

---

Error Handling

Scenario	Resolution
Unknown command	Error with available command list
Dynamic role-spec not found	Error, coordinator may need to regenerate
Command file not found	Fallback to inline execution
CLI tool fails	Worker proceeds with direct implementation, logs warning
Explore cache corrupt	Clear cache, re-explore
Fast-advance spawns wrong task	Coordinator reconciles on next callback
capability_gap reported	Coordinator generates new role-spec via handleAdapt
Completion action fails	Default to Keep Active, log warning