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>

Author: catlog22

.codex/skills/team-arch-opt/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: team-arch-opt
 description: Unified team skill for architecture optimization. Uses team-worker agent architecture with role directories for domain logic. Coordinator orchestrates pipeline, workers are team-worker agents. Triggers on "team arch-opt".
-allowed-tools: spawn_agent(*), wait_agent(*), send_input(*), close_agent(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), mcp__ace-tool__search_context(*)
+allowed-tools: spawn_agent(*), wait_agent(*), send_message(*), assign_task(*), close_agent(*), list_agents(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*), mcp__ace-tool__search_context(*)
 ---
 
 # Team Architecture Optimization
@@ -54,7 +54,8 @@ Before calling ANY tool, apply this check:
 
 | Tool Call | Verdict | Reason |
 |-----------|---------|--------|
-| `spawn_agent`, `wait_agent`, `close_agent`, `send_input` | ALLOWED | Orchestration |
+| `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 |
@@ -84,6 +85,8 @@ 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>
@@ -107,11 +110,34 @@ pipeline_phase: <pipeline-phase>` },
 })
 ```
 
-After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ id })` each worker.
+After spawning, use `wait_agent({ targets: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ target: <name> })` each worker.
 
 **Inner Loop roles** (refactorer): Set `inner_loop: true`.
 **Single-task roles** (analyzer, designer, validator, reviewer): Set `inner_loop: false`.
 
+### Model Selection Guide
+
+Architecture optimization is reasoning-intensive. All analysis and design roles need high reasoning effort.
+
+| Role | reasoning_effort | Rationale |
+|------|-------------------|-----------|
+| analyzer | high | Deep structural analysis of codebase architecture |
+| designer | high | Architecture redesign requires careful reasoning about tradeoffs |
+| refactorer | high | Code transformations must preserve correctness |
+| validator | high | Validation must thoroughly check refactoring correctness |
+| reviewer | high | Code quality review demands deep understanding |
+
+Override in spawn_agent when needed:
+```
+spawn_agent({
+  agent_type: "team_worker",
+  task_name: "<task-id>",
+  fork_context: false,
+  reasoning_effort: "high",
+  items: [...]
+})
+```
+
 ## User Commands
 
 | Command | Action |
@@ -161,6 +187,47 @@ After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect
 
 - [specs/pipelines.md](specs/pipelines.md) — Pipeline definitions, task registry, parallel modes
 
+## v4 Agent Coordination
+
+### Message Semantics
+
+| Intent | API | Example |
+|--------|-----|---------|
+| Queue supplementary info (don't interrupt) | `send_message` | Send codebase patterns to running analyzer |
+| Assign new work / trigger processing | `assign_task` | Assign fix task to refactorer after review feedback |
+| Check running agents | `list_agents` | Verify agent health during resume |
+
+### Agent Health Check
+
+Use `list_agents({})` in handleResume and handleComplete:
+
+```
+// Reconcile session state with actual running agents
+const running = list_agents({})
+// Compare with session.json active tasks
+// 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: "ANALYZE-001", items: [...] })` -- queue analysis context without interrupting
+- `assign_task({ target: "REFACTOR-001", items: [...] })` -- assign fix task after review feedback
+- `close_agent({ target: "VALIDATE-001" })` -- cleanup by name
+
+### Merged Exploration Pattern
+
+For architecture analysis, analyzer may need broad codebase exploration. Consider spawning analyzer with `fork_context: true` when deep structural analysis of interconnected modules is needed:
+```
+spawn_agent({
+  agent_type: "team_worker",
+  task_name: "ANALYZE-001",
+  fork_context: true,   // Share coordinator's codebase context
+  reasoning_effort: "high",
+  items: [...]
+})
+```
+
 ## Error Handling
 
 | Scenario | Resolution |

.codex/skills/team-arch-opt/roles/coordinator/commands/monitor.md

@@ -41,6 +41,16 @@ Fan-out mode adds per-branch grouping. Independent mode adds per-pipeline groupi
 
 ## handleResume
 
+**Agent Health Check** (v4):
+```
+// Verify actual running agents match session state
+const runningAgents = list_agents({})
+// For each active_agent in tasks.json:
+//   - If agent NOT in runningAgents -> agent crashed
+//   - Reset that task to pending, remove from active_agents
+// This prevents stale agent references from blocking the pipeline
+```
+
 1. Read tasks.json, check active_agents
 2. No active agents -> handleSpawnNext
 3. Has active agents -> check each status
@@ -74,6 +84,7 @@ state.tasks[taskId].status = 'in_progress'
 // 2) Spawn worker
 const agentId = spawn_agent({
   agent_type: "team_worker",
+  task_name: taskId,  // e.g., "DESIGN-001" — enables named targeting
   items: [
     { type: "text", text: `## Role Assignment
 role: ${task.role}
@@ -109,20 +120,43 @@ state.active_agents[taskId] = { agentId, role: task.role, started_at: now }
 | Fan-out (REFACTOR-B{NN} done) | VALIDATE + REVIEW ready | Spawn both for that branch in parallel |
 | Independent | Any unblocked task | Spawn all ready tasks across all pipelines in parallel |
 
+**Cross-Agent Supplementary Context** (v4):
+
+When spawning workers in a later pipeline phase, send upstream results as supplementary context to already-running workers:
+
+```
+// Example: Send design analysis results to running refactorers
+send_message({
+  target: "<running-agent-task-name>",
+  items: [{ type: "text", text: `## Supplementary Context\n${upstreamFindings}` }]
+})
+// Note: send_message queues info without interrupting the agent's current work
+```
+
+Use `send_message` (not `assign_task`) for supplementary info that enriches but doesn't redirect the agent's current task.
+
 ### Wait and Process Results
 
 After spawning all ready tasks:
 
 ```javascript
-// 4) Batch wait for all spawned workers
-const agentIds = Object.values(state.active_agents).map(a => a.agentId)
-wait_agent({ ids: agentIds, timeout_ms: 900000 })
-
-// 5) Collect results
-for (const [taskId, agent] of Object.entries(state.active_agents)) {
-  state.tasks[taskId].status = 'completed'
-  close_agent({ id: agent.agentId })
-  delete state.active_agents[taskId]
+// 4) Batch wait — use task_name for stable targeting (v4)
+const taskNames = Object.keys(state.active_agents)
+const waitResult = wait_agent({ targets: taskNames, timeout_ms: 900000 })
+if (waitResult.timed_out) {
+  // Mark timed-out agents, close them, report to user
+  for (const taskId of taskNames) {
+    state.tasks[taskId].status = 'timed_out'
+    close_agent({ target: taskId })
+    delete state.active_agents[taskId]
+  }
+} else {
+  // 5) Collect results
+  for (const [taskId, agent] of Object.entries(state.active_agents)) {
+    state.tasks[taskId].status = 'completed'
+    close_agent({ target: taskId })  // Use task_name, not agentId
+    delete state.active_agents[taskId]
+  }
 }
 ```
 
@@ -159,6 +193,14 @@ Fix cycle tracking per branch in tasks.json `fix_cycles`:
 
 ## handleComplete
 
+**Cleanup Verification** (v4):
+```
+// Verify all agents are properly closed
+const remaining = list_agents({})
+// If any team agents still running -> close_agent each
+// Ensures clean session shutdown
+```
+
 Pipeline done. Generate report and completion action.
 
 Completion check by mode:

.codex/skills/team-arch-opt/roles/coordinator/role.md

@@ -6,7 +6,7 @@ Orchestrate team-arch-opt: analyze -> dispatch -> spawn -> monitor -> report.
 
 **You are a dispatcher, not a doer.** Your ONLY outputs are:
 - Session state files (`.workflow/.team/` directory)
-- `spawn_agent` / `wait_agent` / `close_agent` / `send_input` calls
+- `spawn_agent` / `wait_agent` / `close_agent` / `send_message` / `assign_task` calls
 - Status reports to the user / `request_user_input` prompts
 
 **FORBIDDEN** (even if the task seems trivial):
@@ -34,6 +34,8 @@ WRONG: Bash running build/test/lint commands          — worker work
 - Handle review-fix cycles with max 3 iterations
 - Execute completion action in Phase 5
 - **Always proceed through full Phase 1-5 workflow, never skip to direct execution**
+- Use `send_message` for supplementary context (non-interrupting) and `assign_task` for triggering new work
+- Use `list_agents` for session resume health checks and cleanup verification
 
 ### MUST NOT
 - Implement domain logic (analyzing, refactoring, reviewing) -- workers handle this
@@ -173,6 +175,16 @@ Delegate to @commands/monitor.md#handleSpawnNext:
    - auto_archive -> Archive & Clean (rm -rf session folder)
    - auto_keep -> Keep Active (status=paused)
 
+## v4 Coordination Patterns
+
+### Message Semantics
+- **send_message**: Queue supplementary info to a running agent. Does NOT interrupt current processing. Use for: sharing upstream results, context enrichment, FYI notifications.
+- **assign_task**: Assign new work and trigger processing. Use for: waking idle agents, redirecting work, requesting new output.
+
+### Agent Lifecycle Management
+- **list_agents({})**: Returns all running agents. Use in handleResume to reconcile session state with actual running agents. Use in handleComplete to verify clean shutdown.
+- **Named targeting**: Workers spawned with `task_name: "<task-id>"` can be addressed by name in send_message, assign_task, and close_agent calls.
+
 ## Error Handling
 
 | Error | Resolution |

.codex/skills/team-brainstorm/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: team-brainstorm
 description: Unified team skill for brainstorming team. Uses team-worker agent architecture with role directories for domain logic. Coordinator orchestrates pipeline, workers are team-worker agents. Triggers on "team brainstorm".
-allowed-tools: spawn_agent(*), wait_agent(*), send_input(*), close_agent(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*)
+allowed-tools: spawn_agent(*), wait_agent(*), send_message(*), assign_task(*), close_agent(*), list_agents(*), report_agent_job_result(*), request_user_input(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*)
 ---
 
 # Team Brainstorm
@@ -53,7 +53,8 @@ Before calling ANY tool, apply this check:
 
 | Tool Call | Verdict | Reason |
 |-----------|---------|--------|
-| `spawn_agent`, `wait_agent`, `close_agent`, `send_input` | ALLOWED | Orchestration |
+| `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 |
@@ -83,6 +84,8 @@ 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>
@@ -106,7 +109,7 @@ pipeline_phase: <pipeline-phase>` },
 })
 ```
 
-After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ id })` each worker.
+After spawning, use `wait_agent({ targets: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ target: <name> })` each worker.
 
 **Parallel ideator spawn** (Full pipeline with N angles):
 
@@ -115,6 +118,8 @@ When Full pipeline has N parallel IDEA tasks, spawn N distinct team-worker agent
 ```
 spawn_agent({
   agent_type: "team_worker",
+  task_name: "ideator-<N>",
+  fork_context: false,
   items: [
     { type: "text", text: `## Role Assignment
 role: ideator
@@ -139,7 +144,29 @@ pipeline_phase: <pipeline-phase>` },
 })
 ```
 
-After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ id })` each worker.
+After spawning, use `wait_agent({ targets: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ target: <name> })` each worker.
+
+
+### Model Selection Guide
+
+| Role | model | reasoning_effort | Rationale |
+|------|-------|-------------------|-----------|
+| Ideator (IDEA-*) | (default) | high | Creative divergent thinking requires full reasoning |
+| Challenger (CHALLENGE-*) | (default) | high | Critical analysis of ideas needs deep reasoning |
+| Synthesizer (SYNTH-*) | (default) | medium | Aggregation and convergence over generation |
+| Evaluator (EVAL-*) | (default) | medium | Scoring and ranking against criteria |
+
+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: [...]
+})
+```
 
 ## User Commands
 
@@ -178,6 +205,47 @@ After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect
 
 - [specs/pipelines.md](specs/pipelines.md) — Pipeline definitions and task registry
 
+## v4 Agent Coordination
+
+### Message Semantics
+
+| Intent | API | Example |
+|--------|-----|---------|
+| Share idea context across ideators | `send_message` | Send seed ideas to running ideator for cross-pollination |
+| Not used in this skill | `assign_task` | No resident agents -- all workers are one-shot |
+| Check running agents | `list_agents` | Verify parallel ideator health during Full pipeline |
+
+### Parallel Ideator Coordination (Full Pipeline)
+
+Full pipeline spawns N parallel ideators for different brainstorming angles. Use batch spawn + wait:
+
+```
+// Spawn N ideators in parallel, each with a different angle
+const ideatorNames = ["IDEA-001", "IDEA-002", "IDEA-003"]
+for (const name of ideatorNames) {
+  spawn_agent({ agent_type: "team_worker", task_name: name, fork_context: false, ... })
+}
+wait_agent({ targets: ideatorNames, timeout_ms: 900000 })
+// Collect all idea outputs, feed to challenger as upstream context
+```
+
+### 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: "IDEA-002", items: [...] })` -- share context from another ideator
+- `close_agent({ target: "IDEA-001" })` -- cleanup by name after wait_agent returns
+
 ## Error Handling
 
 | Scenario | Resolution |