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".
63
55%
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Optimize this skill with Tessl
npx tessl skill review --optimize ./.codex/skills/team-issue/SKILL.mdOrchestrate issue resolution pipeline: explore context -> plan solution -> review (optional) -> marshal queue -> implement. Supports Quick, Full, and Batch pipelines with review-fix cycle.
Skill(skill="team-issue", args="<issue-ids> [--mode=<mode>]")
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SKILL.md (this file) = Router
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+--------------+--------------+
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no --role flag --role <name>
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Coordinator Worker
roles/coordinator/role.md roles/<name>/role.md
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+-- clarify -> dispatch -> spawn workers -> STOP
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+-------+-------+-------+-------+
v v v v v
[explor] [plann] [review] [integ] [imple]| 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 |
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.
TISL.workflow/.team/TISL-<slug>-<date>/issueccw 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: <task-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.
Parallel spawn (Batch mode, N explorer or M implementer instances):
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>
agent_name: <role>-<N>
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 | 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_context: false,
model: "<model-override>",
reasoning_effort: "<effort-level>",
items: [...]
})| Command | Action |
|---|---|
check / status | View execution status graph, no advancement |
resume / continue | Check worker states, advance next step |
.workflow/.team/TISL-<slug>-<date>/
├── 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| Intent | API | Example |
|---|---|---|
| Send exploration context to running planner | send_message | Queue EXPLORE-* findings to SOLVE-* worker |
| Not used in this skill | assign_task | No resident agents -- all workers are one-shot |
| Check running agents | list_agents | Verify parallel explorer/implementer health |
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({ targets: explorerNames, timeout_ms: 900000 })
// 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({ targets: buildNames, timeout_ms: 900000 })Reviewer (AUDIT-*) may reject plans, triggering fix cycles (max 2). Dynamic SOLVE-fix and AUDIT re-review tasks are created in tasks.json.
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 pendingWorkers are spawned with task_name: "<task-id>" enabling direct addressing:
send_message({ target: "SOLVE-001", items: [...] }) -- queue exploration context to running plannerclose_agent({ target: "BUILD-001" }) -- cleanup by name after completion| 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 |
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