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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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@@ -1,7 +1,7 @@
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---
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name: team-ux-improve
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description: Unified team skill for UX improvement. Systematically discovers and fixes UI/UX interaction issues including unresponsive buttons, missing feedback, and state refresh problems. Uses team-worker agent architecture with roles/ for domain logic. Coordinator orchestrates pipeline, workers are team-worker agents. Triggers on "team ux improve".
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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(*), mcp__ccw-tools__read_file(*), mcp__ccw-tools__write_file(*), mcp__ccw-tools__edit_file(*), mcp__ccw-tools__team_msg(*)
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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(*), mcp__ccw-tools__read_file(*), mcp__ccw-tools__write_file(*), mcp__ccw-tools__edit_file(*), mcp__ccw-tools__team_msg(*)
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---
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# Team UX Improve
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@@ -63,7 +63,8 @@ Before calling ANY tool, apply this check:
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| Tool Call | Verdict | Reason |
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|-----------|---------|--------|
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| `spawn_agent`, `wait_agent`, `close_agent`, `send_input` | ALLOWED | Orchestration |
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| `spawn_agent`, `wait_agent`, `close_agent`, `send_message`, `assign_task` | ALLOWED | Orchestration |
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| `list_agents` | ALLOWED | Agent health check |
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| `request_user_input` | ALLOWED | User interaction |
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| `mcp__ccw-tools__team_msg` | ALLOWED | Message bus |
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| `Read/Write` on `.workflow/.team/` files | ALLOWED | Session state |
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@@ -94,6 +95,8 @@ Coordinator spawns workers using this template:
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```
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spawn_agent({
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agent_type: "team_worker",
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task_name: "<task-id>",
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fork_context: false,
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items: [
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{ type: "text", text: `## Role Assignment
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role: <role>
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@@ -117,7 +120,21 @@ pipeline_phase: <pipeline-phase>` },
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})
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```
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After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ id })` each worker.
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After spawning, use `wait_agent({ targets: [...], timeout_ms: 900000 })` to collect results, then `close_agent({ target })` each worker.
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### Model Selection Guide
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UX improvement has an explorer utility member and a scan-diagnose-design-implement-test pipeline.
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| Role | reasoning_effort | Rationale |
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|------|-------------------|-----------|
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| explorer | low | File reading and pattern summarization only (utility member) |
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| scanner | medium | Broad UI/UX issue scanning, pattern-based detection |
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| diagnoser | high | Root cause diagnosis of UX issues requires deep analysis |
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| designer | high | UX improvement design needs careful user experience reasoning |
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| implementer | high | UI code changes must preserve existing behavior |
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| tester | medium | Test execution follows defined UX verification criteria |
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## User Commands
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@@ -152,6 +169,50 @@ After spawning, use `wait_agent({ ids: [...], timeout_ms: 900000 })` to collect
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└── anti-patterns/
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```
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## v4 Agent Coordination
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### Message Semantics
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| Intent | API | Example |
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|--------|-----|---------|
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| Queue supplementary info (don't interrupt) | `send_message` | Send explorer findings to running scanner |
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| Assign implementation from design | `assign_task` | Assign IMPL task from designer output |
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| Check running agents | `list_agents` | Verify agent health during resume |
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### Agent Health Check
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Use `list_agents({})` in handleResume and handleComplete:
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```
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// Reconcile session state with actual running agents
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const running = list_agents({})
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// Compare with meta.json active tasks
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// Reset orphaned tasks (in_progress but agent gone) to pending
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```
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### Named Agent Targeting
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Workers are spawned with `task_name: "<task-id>"` enabling direct addressing:
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- `send_message({ target: "SCAN-001", items: [...] })` -- send explorer findings to scanner
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- `assign_task({ target: "IMPL-001", items: [...] })` -- assign UX fix from designer output
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- `close_agent({ target: "TEST-001" })` -- cleanup after UX testing
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### Explorer-Assisted Scanning
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Coordinator spawns explorer (utility member) early to gather codebase context, then sends findings to scanner via upstream context:
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```
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// Explorer results inform scanner's scope
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send_message({
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target: "SCAN-001",
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items: [
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{ type: "text", text: `## Explorer Findings
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component_patterns: <explorer's component inventory>
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framework: <detected framework>
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ui_library: <detected UI library>` }
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]
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})
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```
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## Error Handling
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| Scenario | Resolution |
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