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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>
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@@ -99,6 +99,16 @@ Output status -- do NOT advance pipeline.
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## handleResume
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**Agent Health Check** (v4):
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```
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// Verify actual running agents match session state
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const runningAgents = list_agents({})
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// For each active_agent in tasks.json:
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// - If agent NOT in runningAgents -> agent crashed
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// - Reset that task to pending, remove from active_agents
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// This prevents stale agent references from blocking the pipeline
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```
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1. Audit tasks.json for inconsistencies:
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- Tasks stuck in "in_progress" -> reset to "pending"
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- Tasks with completed deps but still "pending" -> include in spawn list
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@@ -124,6 +134,7 @@ state.tasks[taskId].status = 'in_progress'
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// 2) Spawn worker
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const agentId = spawn_agent({
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agent_type: "team_worker",
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task_name: taskId, // e.g., "DESIGN-001" — enables named targeting
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items: [
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{ type: "text", text: `## Role Assignment
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role: ${role}
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@@ -141,12 +152,18 @@ Execute built-in Phase 1 (task discovery) -> role Phase 2-4 -> built-in Phase 5
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// 3) Track agent
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state.active_agents[taskId] = { agentId, role, started_at: now }
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// 4) Wait for completion
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wait_agent({ ids: [agentId] })
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// 5) Collect results and update tasks.json
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state.tasks[taskId].status = 'completed'
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delete state.active_agents[taskId]
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// 4) Wait for completion — use task_name for stable targeting (v4)
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const waitResult = wait_agent({ targets: [taskId], timeout_ms: 900000 })
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if (waitResult.timed_out) {
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state.tasks[taskId].status = 'timed_out'
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close_agent({ target: taskId })
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delete state.active_agents[taskId]
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} else {
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// 5) Collect results and update tasks.json
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state.tasks[taskId].status = 'completed'
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close_agent({ target: taskId }) // Use task_name, not agentId
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delete state.active_agents[taskId]
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}
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```
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**Parallel spawn rules by mode**:
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@@ -159,10 +176,33 @@ delete state.active_agents[taskId]
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| full-system | After Sync Point 1 | Spawn DESIGN-002 + BUILD-001 in parallel, wait_agent for both |
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| full-system | After BUILD-002 | Spawn AUDIT-003 |
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**Cross-Agent Supplementary Context** (v4):
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When spawning workers in a later pipeline phase, send upstream results as supplementary context to already-running workers:
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```
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// Example: Send design results to running implementer
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send_message({
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target: "<running-agent-task-name>",
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items: [{ type: "text", text: `## Supplementary Context\n${upstreamFindings}` }]
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})
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// Note: send_message queues info without interrupting the agent's current work
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```
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Use `send_message` (not `assign_task`) for supplementary info that enriches but doesn't redirect the agent's current task.
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5. Update tasks.json, output summary, STOP
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## handleComplete
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**Cleanup Verification** (v4):
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```
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// Verify all agents are properly closed
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const remaining = list_agents({})
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// If any team agents still running -> close_agent each
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// Ensures clean session shutdown
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```
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Pipeline done. Generate report and completion action.
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**Completion check by mode**:
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@@ -6,7 +6,7 @@ UI Design Team coordinator. Orchestrate pipeline: analyze -> dispatch -> spawn -
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**You are a dispatcher, not a doer.** Your ONLY outputs are:
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- Session state files (`.workflow/.team/` directory)
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- `spawn_agent` / `wait_agent` / `close_agent` / `send_input` calls
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- `spawn_agent` / `wait_agent` / `close_agent` / `send_message` / `assign_task` calls
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- Status reports to the user / `request_user_input` prompts
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**FORBIDDEN** (even if the task seems trivial):
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@@ -34,6 +34,8 @@ WRONG: Edit/Write on project source files — worker work
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- Handle Generator-Critic loops with max 2 iterations
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- Maintain session state persistence (tasks.json)
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- **Always proceed through full Phase 1-5 workflow, never skip to direct execution**
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- Use `send_message` for supplementary context (non-interrupting) and `assign_task` for triggering new work
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- Use `list_agents` for session resume health checks and cleanup verification
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### MUST NOT
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- Implement domain logic (researching, designing, auditing, building) -- workers handle this
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@@ -187,6 +189,16 @@ Delegate to `@commands/monitor.md#handleSpawnNext`:
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})
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```
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## v4 Coordination Patterns
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### Message Semantics
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- **send_message**: Queue supplementary info to a running agent. Does NOT interrupt current processing. Use for: sharing upstream results, context enrichment, FYI notifications.
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- **assign_task**: Assign new work and trigger processing. Use for: waking idle agents, redirecting work, requesting new output.
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### Agent Lifecycle Management
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- **list_agents({})**: Returns all running agents. Use in handleResume to reconcile session state with actual running agents. Use in handleComplete to verify clean shutdown.
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- **Named targeting**: Workers spawned with `task_name: "<task-id>"` can be addressed by name in send_message, assign_task, and close_agent calls.
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## Error Handling
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| Error | Resolution |
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