by LottieFiles · Agent Tool · ★ 2.2k
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npx skills add LottieFiles/motion-design-skillTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 2,230 |
| Forks | 146 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 71/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-18 |
| Created | 2026-03-12 |
| Est. Tokens | ~3k |
Motion Design Skill Universal motion design principles for AI agents. Philosophy-first, implementation-agnostic. Teaches agents to think like motion directors — choosing the right timing, easing, choreography, and emotional intent before writing a single line of animation code. Works with any animation system (CSS, Framer Motion, GSAP, Lottie, Spring, etc.).
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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