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Get Started Free →Unified team skill for frontend development. Pure router — all roles read this file. Beat model is coordinator-only in monitor.md. Built-in ui-ux-pro-max design intelligence. Triggers on "team frontend".
.claude/skills/catlog22-team-frontend/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 71% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 186% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 57% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 21% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 60% | 0% |
Unified team skill: frontend development with built-in ui-ux-pro-max design intelligence. Covers requirement analysis, design system generation, frontend implementation, and quality assurance. Built on team-worker agent architecture — all worker roles share a single agent definition with role-specific Phase 2-4 loaded from role.md specs.
Skill(skill="team-frontend", args="task description")
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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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+-- analyze -> dispatch -> spawn workers -> STOP
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+-------+-------+-------+
v v v v
[analyst] [architect] [developer] [qa]
(team-worker agents, each loads roles/<role>/role.md)| Role | Path | Prefix | Inner Loop | |------|------|--------|------------| | coordinator | roles/coordinator/role.md | — | — | | analyst | roles/analyst/role.md | ANALYZE- | false | | architect | [roles/architect/role.md](roles/architect/role.md) | ARCH- | false | | developer | roles/developer/role.md | DEV- | true | | qa | [roles/qa/role.md](roles/qa/role.md) | QA- | 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, 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.
FE.workflow/.team/FE-<date>-<slug>/ccw 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_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: <true|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.
| Role | model | reasoning_effort | Rationale | |------|-------|-------------------|-----------| | Analyst (ANALYZE-) | (default) | high | Design intelligence requires deep UI/UX reasoning | | Architect (ARCH-) | (default) | high | Component spec and design token generation needs precision | | Developer (DEV-) | (default) | high | Frontend code generation needs full reasoning | | QA (QA-) | (default) | high | 5-dimension audit requires thorough analysis |
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: "..."
})| Command | Action | |---------|--------| | check / status | View execution status graph | | resume / continue | Advance to next step |
.workflow/.team/FE-<slug>-<YYYY-MM-DD>/
├── .msg/
│ ├── messages.jsonl # Message bus log
│ └── meta.json # Session state + cross-role state
├── task-analysis.json # Coordinator analyze output
├── wisdom/ # Cross-task knowledge
├── analysis/ # Analyst output
│ ├── design-intelligence.json
│ └── requirements.md
├── architecture/ # Architect output
│ ├── design-tokens.json
│ ├── component-specs/
│ └── project-structure.md
├── qa/ # QA output
│ └── audit-<NNN>.md
└── build/ # Developer output| Intent | API | Example | |--------|-----|---------| | Send architecture specs to running developer | send_message | Queue design tokens and component specs to DEV- | | Not used in this skill | followup_task | No resident agents -- all workers are one-shot | | Check running agents | list_agents | Verify agent health during resume |
Sequential pipeline with GC loops: analyst -> architect -> developer -> QA. In system mode, architect revision (ARCH-002) and developer (DEV-001) may run in parallel after QA-001 arch review.
Developer workers (DEV-) benefit from fork_turns: "all" when the coordinator has accumulated significant design context (analysis results, architecture specs, design tokens). This avoids the developer needing to re-read all upstream artifacts:
// Consider fork_turns: "all" for developer in feature/system modes
spawn_agent({
agent_type: "team_worker",
task_name: "DEV-001",
fork_turns: "all", // Developer gets full coordinator context including design decisions
message: "..."
})QA may flag FIX_REQUIRED, creating DEV-fix + QA-recheck tasks (max 2 rounds). If QA score remains < 6 after 2 rounds, escalate to user.
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: "DEV-001", message: "..." }) -- queue architecture specs to running developerclose_agent({ target: "ARCH-001" }) -- cleanup by name after completion| Scenario | Resolution | |----------|------------| | Unknown command | Error with available command list | | Role not found | Error with role registry | | QA score < 6 over 2 GC rounds | Escalate to user | | ui-ux-pro-max unavailable | Degrade to LLM general design knowledge | | Worker no response | Report waiting task, suggest user resume | | Pipeline deadlock | Check blockedBy chain, report blocking point |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-21 | pass→pass | 12,316 | 12,153 | -1% | 1 | 1 | 0% | 2,350 | 4,470 | +90% | 0 | 0 | — |
case-22 | pass→pass | 12,971 | 11,482 | -11% | 1 | 1 | 0% | 2,431 | 4,189 | +72% | 0 | 0 | — |
case-01 | fail→fail | 28,548 | 6,003 | -79% | 1 | 1 | 0% | 6,211 | 2,619 | -58% | 0 | 0 | — |
case-02 | fail→fail | 28,777 | 7,649 | -73% | 1 | 1 | 0% | 6,190 | 2,631 | -57% | 0 | 0 | — |
case-03 | fail→fail | 10,889 | 6,582 | -40% | 1 | 1 | 0% | 1,919 | 2,624 | +37% | 0 | 0 | — |
case-04 | fail→pass | 11,390 | 6,420 | -44% | 1 | 1 | 0% | 1,854 | 3,176 | +71% | 0 | 0 | — |
case-05 | pass→fail | 10,043 | 2,795 | -72% | 1 | 1 | 0% | 1,541 | 2,630 | +71% | 0 | 0 | — |
case-06 | fail→pass | 6,264 | 10,361 | +65% | 1 | 1 | 0% | 1,182 | 3,375 | +186% | 0 | 0 | — |
case-07 | fail→pass | 11,063 | 2,814 | -75% | 1 | 1 | 0% | 1,721 | 2,704 | +57% | 0 | 0 | — |
case-08 | fail→pass | 12,436 | 4,338 | -65% | 1 | 1 | 0% | 2,490 | 3,014 | +21% | 0 | 0 | — |
case-09 | fail→pass | 10,693 | 5,505 | -49% | 1 | 1 | 0% | 1,858 | 2,968 | +60% | 0 | 0 | — |
case-20 | pass→pass | 13,411 | 11,895 | -11% | 1 | 1 | 0% | 2,575 | 4,550 | +77% | 0 | 0 | — |
case-10 | pass→pass | 12,815 | 7,297 | -43% | 1 | 1 | 0% | 1,885 | 3,490 | +85% | 0 | 0 | — |
case-11 | fail→pass | 10,827 | 2,625 | -76% | 1 | 1 | 0% | 1,726 | 2,621 | +52% | 0 | 0 | — |
case-12 | fail→pass | 15,097 | 4,521 | -70% | 1 | 1 | 0% | 1,849 | 3,104 | +68% | 0 | 0 | — |
case-13 | pass→pass | 7,252 | 2,455 | -66% | 1 | 1 | 0% | 1,291 | 2,559 | +98% | 0 | 0 | — |
case-14 | fail→pass | 11,994 | 5,556 | -54% | 1 | 1 | 0% | 1,912 | 3,131 | +64% | 0 | 0 | — |
case-15 | fail→pass | 10,397 | 2,476 | -76% | 1 | 1 | 0% | 1,794 | 2,580 | +44% | 0 | 0 | — |
case-16 | pass→pass | 9,386 | 5,933 | -37% | 1 | 1 | 0% | 1,577 | 3,175 | +101% | 0 | 0 | — |
case-17 | pass→pass | 6,459 | 3,269 | -49% | 1 | 1 | 0% | 1,052 | 2,515 | +139% | 0 | 0 | — |
case-18 | fail→fail | 10,329 | 3,296 | -68% | 1 | 1 | 0% | 1,427 | 2,708 | +90% | 0 | 0 | — |
case-19 | fail→pass | 8,142 | 3,176 | -61% | 1 | 1 | 0% | 1,342 | 2,677 | +99% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 19 counted toward the lift figure. The other 3 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +41 percentage points is the difference between those two pass rates over the 19 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/3/2026 | +50% |
Other measured skills in the registry, with their headline benchmark lift.