by LottieFiles · Agent Tool · ★ 111
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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.). Install Supports 40+ agents including Claude Code, Cursor, Codex, GitHub Copilot, and more. What's included Core () — Quick reference with the 8-step checklist, motion personality archetypes, duration/easing tables, property selection guide, common patterns, and quality rules. Philosophy () — Deep dives into the three pillars, Disney's 12 principles adapted for UI, emotion-to-motion mapping, choreography, narrative structure, and context adaptation. Patterns () — Ready-to-use recipes for entrance/exit animations, state feedback (success, error, loading, hover), ambient/continuous motion, and multi-element choreography. Reference () — Lookup tables for timing and easing, property selection guide, quality checklist, and troubleshooting common animation problems. When it activates The skill activat
| Stars | 111 |
| Forks | 15 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 71.2726928266424/100 |
| Last Updated | 2026-05-18 |
| Created | 2026-03-12 |
| Est. Tokens | ~3k |
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motion-design-skill is Universal motion design principles for AI agents — timing, easing, choreography, and Disney animation principles adapted for UI. It is categorized as a Agent Tool with 111 GitHub stars.
You can find installation instructions and usage details in the motion-design-skill GitHub repository at github.com/LottieFiles/motion-design-skill. The project has 111 stars and 15 forks, indicating an active community.
motion-design-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to motion-design-skill on Agent Skills Hub include typeui.sh, copilot-mcp, clsh. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.