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Design motion audit

Skill BjornMelin/dev-skills/plugins/design-motion/skills/design-motion-audit

AgentSkills library: reusable skills for AI coding agents (AI SDK, Codex, LangGraph, Supabase, Docker, Vitest, pytest, Streamlit, Zod).

Install
npx -y skills add BjornMelin/dev-skills --skill design-motion-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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What its author says it does

Copied from the file, not written here

Audits a repo, route, screen, or 3D scene for motion quality, covering design-token consistency, frame-rate and draw-call risk, reduced-motion coverage, and accessibility. Use to audit, critique, or find motion gaps. Returns a prioritized punch list rather than implementing fixes.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.8 KB, as published. Nobody here has run it

Design Motion Audit

Audit the target surface (a repo, route, screen, component, or 3D scene) for motion quality and implementation safety, and return a prioritized punch list with exact files, severity, reasoning, and concrete fixes. This skill diagnoses; it routes implementation to the owning skill (expo-motion, web-three-r3f for R3F setup and correctness, r3f-scene-polish for look-dev, or gsap). Token and motion-system work is handled here via references/design-system-tokens.md and scripts/scaffold_motion_tokens.py.

How to run

  1. Optionally run the static analyzers to gather leads (treat findings as leads, verify each against the real code before reporting):

    python3 scripts/detect_motion_stack.py <project-root> --pretty   # what stacks/files exist
python3 scripts/audit_motion_system.py <project-root> --pretty    # heuristic motion-quality scan

  2. Read the flagged files and judge against the dimensions below.

  3. Return the punch list, most-severe first.

Audit dimensions

  1. Design tokens & consistency — hardcoded durations/easings/springs vs tokenized values; naming by intent. (references/motion-vocabulary.md)
  2. R3F / three.js / WebGL — setState in useFrame, missing delta-time, per-frame allocations, disposal, DPR, shadows, postprocessing budget.
  3. Reanimated / Expo / gestures — JS-thread per-frame work, deprecated runOnJS/runOnUI, worklet misuse, interruptibility, layout-vs-transform.
  4. Interaction physicality — velocity-aware release, cancellation-safety.
  5. Performance risk — frame budget, draw calls, texture/asset weight, blur. (references/performance-accessibility.md)
  6. Reduced-motion coverage — every camera move, parallax, loop, and bounce has a reduced-motion branch that preserves functional feedback.
  7. Accessibility & readability — text legibility during motion.
  8. Missing hallmark opportunities — where a signature motion would add value.

Score against references/quality-gates.md, and shape the output with references/report-template.md. For any change with a visible motion surface, add runtime proof (references/runtime-verification.md) — static findings alone do not prove a scene renders or holds its frame budget; the motion-runtime-verifier subagent (design-motion plugin) drives that when the browser tools are available. For deep implementation fixes, hand each finding to the skill that owns its stack.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.