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Get Started Free →Unified team skill for motion design. Animation token systems, scroll choreography, GPU-accelerated transforms, reduced-motion fallback. Uses team-worker agent architecture. Triggers on "team motion design", "animation system".
.claude/skills/catlog22-team-motion-design/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-08 | ✗→✓ | ▲ Improved | 34% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 53% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 143% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 71% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 51% | 0% |
Systematic motion design pipeline: research -> choreography -> animation -> performance testing. Built on team-worker agent architecture -- all worker roles share a single agent definition with role-specific Phase 2-4 loaded from roles/<role>/role.md.
Skill(skill="team-motion-design", 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
[team-worker agents, each loads roles/<role>/role.md]
motion-researcher choreographer animator motion-tester| Role | Path | Prefix | Inner Loop | |------|------|--------|------------| | coordinator | roles/coordinator/role.md | -- | -- | | motion-researcher | roles/motion-researcher/role.md | MRESEARCH- | false | | choreographer | [roles/choreographer/role.md](roles/choreographer/role.md) | CHOREO- | false | | animator | roles/animator/role.md | ANIM- | true | | motion-tester | [roles/motion-tester/role.md](roles/motion-tester/role.md) | MTEST- | 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.
MD.workflow/.team/MD-<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.
Motion design is a performance-critical pipeline where research informs choreography decisions and animations must pass strict GPU performance gates. Researcher needs thorough profiling, animator needs creative implementation with inner loop capability.
| Role | reasoning_effort | Rationale | |------|-------------------|-----------| | motion-researcher | high | Deep performance profiling and animation audit across codebase | | choreographer | high | Creative token system design and scroll choreography sequencing | | animator | high | Complex CSS/JS animation implementation with compositor constraints | | motion-tester | medium | Performance validation follows defined test criteria and scoring |
Researcher findings must reach choreographer via coordinator's upstream context:
// After MRESEARCH-001 completes, coordinator sends findings to choreographer
spawn_agent({
agent_type: "team_worker",
task_name: "CHOREO-001",
fork_turns: "none",
message: `## Upstream Context
Research findings: <session>/research/animation-inventory.json
Performance baseline: <session>/research/performance-baseline.json
Easing catalog: <session>/research/easing-catalog.json`
})| Command | Action | |---------|--------| | check / status | View execution status graph | | resume / continue | Advance to next step |
.workflow/.team/MD-<date>-<slug>/
+-- .msg/
| +-- messages.jsonl # Team message bus
| +-- meta.json # Pipeline config + GC state
+-- research/ # Motion researcher output
| +-- perf-traces/ # Chrome DevTools performance traces
| +-- animation-inventory.json
| +-- performance-baseline.json
| +-- easing-catalog.json
+-- choreography/ # Choreographer output
| +-- motion-tokens.json
| +-- sequences/ # Scroll choreography sequences
+-- animations/ # Animator output
| +-- keyframes/ # CSS @keyframes files
| +-- orchestrators/ # JS animation orchestrators
+-- testing/ # Motion tester output
| +-- traces/ # Performance trace data
| +-- reports/ # Performance reports
+-- wisdom/ # Cross-task knowledge| Intent | API | Example | |--------|-----|---------| | Queue supplementary info (don't interrupt) | send_message | Send research findings to running choreographer | | Assign implementation from reviewed specs | followup_task | Assign ANIM task after choreography passes | | Check running agents | list_agents | Verify agent health during resume |
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: "CHOREO-001", message: "..." }) -- send additional research findings to choreographerfollowup_task({ target: "ANIM-001", message: "..." }) -- assign animation from reviewed choreography specsclose_agent({ target: "MTEST-001" }) -- cleanup after performance test| Scenario | Resolution | |----------|------------| | Unknown command | Error with available command list | | Role not found | Error with role registry | | Session corruption | Attempt recovery, fallback to manual | | Fast-advance conflict | Coordinator reconciles on next callback | | Completion action fails | Default to Keep Active | | GC loop stuck > 2 rounds | Escalate to user: accept / retry / terminate |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-08 | fail→pass | 22,043 | 8,833 | -60% | 1 | 1 | 0% | 2,754 | 3,682 | +34% | 0 | 0 | — |
case-09 | fail→pass | 15,048 | 8,776 | -42% | 1 | 1 | 0% | 2,398 | 3,665 | +53% | 0 | 0 | — |
case-02 | fail→fail | 3,109 | 6,311 | +103% | 1 | 1 | 0% | 519 | 2,554 | +392% | 0 | 0 | — |
case-01 | fail→fail | 32,023 | 5,559 | -83% | 1 | 1 | 0% | 6,205 | 2,461 | -60% | 0 | 0 | — |
case-03 | fail→fail | 6,778 | 6,862 | +1% | 1 | 1 | 0% | 1,024 | 2,673 | +161% | 0 | 0 | — |
case-04 | pass→pass | 15,161 | 18,308 | +21% | 1 | 1 | 0% | 2,729 | 4,937 | +81% | 0 | 0 | — |
case-05 | fail→fail | 28,848 | 5,244 | -82% | 1 | 1 | 0% | 6,180 | 2,500 | -60% | 0 | 0 | — |
case-06 | pass→fail | 12,273 | 7,474 | -39% | 1 | 1 | 0% | 2,179 | 2,700 | +24% | 0 | 0 | — |
case-07 | fail→pass | 7,764 | 4,074 | -48% | 1 | 1 | 0% | 1,179 | 2,860 | +143% | 0 | 0 | — |
case-10 | fail→pass | 9,077 | 3,804 | -58% | 1 | 1 | 0% | 1,719 | 2,933 | +71% | 0 | 0 | — |
case-11 | fail→pass | 9,982 | 3,269 | -67% | 1 | 1 | 0% | 1,776 | 2,683 | +51% | 0 | 0 | — |
case-12 | fail→pass | 12,647 | 4,639 | -63% | 1 | 1 | 0% | 2,189 | 3,097 | +41% | 0 | 0 | — |
case-13 | fail→pass | 12,082 | 2,618 | -78% | 1 | 1 | 0% | 1,851 | 2,548 | +38% | 0 | 0 | — |
case-14 | fail→pass | 7,509 | 3,098 | -59% | 1 | 1 | 0% | 1,250 | 2,409 | +93% | 0 | 0 | — |
case-15 | fail→pass | 10,870 | 5,849 | -46% | 1 | 1 | 0% | 1,992 | 3,027 | +52% | 0 | 0 | — |
case-16 | pass→pass | 9,951 | 2,642 | -73% | 1 | 1 | 0% | 1,663 | 2,654 | +60% | 0 | 0 | — |
case-17 | fail→fail | 12,808 | 2,175 | -83% | 1 | 1 | 0% | 2,022 | 2,393 | +18% | 0 | 0 | — |
case-18 | fail→pass | 11,612 | 2,519 | -78% | 1 | 1 | 0% | 1,477 | 2,659 | +80% | 0 | 0 | — |
case-19 | fail→pass | 17,238 | 3,041 | -82% | 1 | 1 | 0% | 1,971 | 2,729 | +38% | 0 | 0 | — |
case-20 | fail→pass | 11,819 | 2,528 | -79% | 1 | 1 | 0% | 1,746 | 2,511 | +44% | 0 | 0 | — |
case-21 | fail→pass | 8,188 | 2,439 | -70% | 1 | 1 | 0% | 1,333 | 2,588 | +94% | 0 | 0 | — |
case-22 | fail→pass | 5,501 | 3,343 | -39% | 1 | 1 | 0% | 946 | 2,698 | +185% | 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 17 counted toward the lift figure. The other 5 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 +59 percentage points is the difference between those two pass rates over the 17 comparable cases. 2 cases got worse with the skill loaded, and they are 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 | +45% |
Other measured skills in the registry, with their headline benchmark lift.