team-issue

name	team-issue
description	Unified team skill for issue resolution. Uses team-worker agent architecture with role directories for domain logic. Coordinator orchestrates pipeline, workers are team-worker agents. Triggers on "team issue".
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__ace-tool__search_context(*), mcp__ccw-tools__team_msg(*)

Team Issue Resolution

Orchestrate issue resolution pipeline: explore context -> plan solution -> review (optional) -> marshal queue -> implement. Supports Quick, Full, and Batch pipelines with review-fix cycle.

Architecture

Skill(skill="team-issue", args="<issue-ids> [--mode=<mode>]")
                    |
         SKILL.md (this file) = Router
                    |
     +--------------+--------------+
     |                             |
  no --role flag              --role <name>
     |                             |
  Coordinator                  Worker
  roles/coordinator/role.md    roles/<name>/role.md
     |
     +-- clarify -> dispatch -> spawn workers -> STOP
                                    |
             +-------+-------+-------+-------+
             v       v       v       v       v
          [explor] [plann] [review] [integ] [imple]

Role Registry

Role	Path	Prefix	Inner Loop
coordinator	roles/coordinator/role.md	—	—
explorer	roles/explorer/role.md	EXPLORE-*	false
planner	roles/planner/role.md	SOLVE-*	false
reviewer	roles/reviewer/role.md	AUDIT-*	false
integrator	roles/integrator/role.md	MARSHAL-*	false
implementer	roles/implementer/role.md	BUILD-*	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, 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.

---

Shared Constants

• Session prefix: TISL
• Session path: .workflow/.team/TISL-<date>-<slug>/
• Team name: issue
• 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_turns: "none",
  message: `## Role Assignment
role: <role>
role_spec: <skill_root>/roles/<role>/role.md
session: <session-folder>
session_id: <session-id>
requirement: <task-description>
inner_loop: false

Read role_spec file (<skill_root>/roles/<role>/role.md) 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 }) each worker.

Parallel spawn (Batch mode, N explorer or M implementer instances):

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

Read role_spec file (<skill_root>/roles/<role>/role.md) 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 }) each worker.

Model Selection Guide

Role	model	reasoning_effort	Rationale
Explorer (EXPLORE-*)	(default)	medium	Context gathering, file reading, less reasoning
Planner (SOLVE-*)	(default)	high	Solution design requires deep analysis
Reviewer (AUDIT-*)	(default)	high	Code review and plan validation need full reasoning
Integrator (MARSHAL-*)	(default)	medium	Queue ordering and dependency resolution
Implementer (BUILD-*)	(default)	high	Code generation needs precision

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: "..."
})

User Commands

Command	Action
check / status	View execution status graph, no advancement
resume / continue	Check worker states, advance next step

Session Directory

.workflow/.team/TISL-<date>-<slug>/
├── session.json                    # Session metadata + pipeline + fix_cycles
├── task-analysis.json              # Coordinator analyze output
├── .msg/
│   ├── messages.jsonl              # Message bus log
│   └── meta.json                   # Session state + cross-role state
├── wisdom/                         # Cross-task knowledge
│   ├── learnings.md
│   ├── decisions.md
│   ├── conventions.md
│   └── issues.md
├── explorations/                   # Explorer output
│   └── context-<issueId>.json
├── solutions/                      # Planner output
│   └── solution-<issueId>.json
├── audits/                         # Reviewer output
│   └── audit-report.json
├── queue/                          # Integrator output (also .workflow/issues/queue/)
└── builds/                         # Implementer output

Specs Reference

• specs/pipelines.md — Pipeline definitions and task registry

v4 Agent Coordination

Message Semantics

Intent	API	Example
Send exploration context to running planner	send_message	Queue EXPLORE-* findings to SOLVE-* worker
Not used in this skill	followup_task	No resident agents -- all workers are one-shot
Check running agents	list_agents	Verify parallel explorer/implementer health

Pipeline Pattern

Pipeline with context passing: explore -> plan -> review (optional) -> marshal -> implement. In Batch mode, N explorers and M implementers run in parallel:

// Batch mode: spawn N explorers in parallel (max 5)
const explorerNames = ["EXPLORE-001", "EXPLORE-002", ..., "EXPLORE-00N"]
for (const name of explorerNames) {
  spawn_agent({ agent_type: "team_worker", task_name: name, ... })
}
wait_agent({ timeout_ms: 1800000 })  // 30 min — apply timeout cascade if timed_out

// After MARSHAL completes: spawn M implementers in parallel (max 3)
const buildNames = ["BUILD-001", "BUILD-002", ..., "BUILD-00M"]
for (const name of buildNames) {
  spawn_agent({ agent_type: "team_worker", task_name: name, ... })
}
wait_agent({ timeout_ms: 1800000 })  // 30 min — apply timeout cascade if timed_out

Review-Fix Cycle

Reviewer (AUDIT-*) may reject plans, triggering fix cycles (max 2). Dynamic SOLVE-fix and AUDIT re-review tasks are created in tasks.json.

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

Named Agent Targeting

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

• send_message({ target: "SOLVE-001", message: "..." }) -- queue exploration context to running planner
• close_agent({ target: "BUILD-001" }) -- cleanup by name after completion

Error Handling

Scenario	Resolution
Unknown command	Error with available command list
Role not found	Error with role registry
CLI tool fails	Worker fallback to direct implementation
Fast-advance conflict	Coordinator reconciles on next callback
Completion action fails	Default to Keep Active
Review rejection exceeds 2 rounds	Force convergence to integrator
No issues found for given IDs	Coordinator reports error to user
Deferred BUILD count unknown	Defer to MARSHAL callback