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Reverse-engineer any motion reference (a video from X/Twitter, Dribbble, a screen recording, a GIF) into production animation code through frame-level dissection. Use when the user shares a video/URL and says "implement this animation", "recreate this motion", "port this
Claude Code
$ npx -y skills add sendaifun/skills --skill animation-reverse-engineering --agent claude-code
Codex
$ npx skills add sendaifun/skills --skill animation-reverse-engineering -a codex -y
Cursor
$ npx skills add sendaifun/skills --skill animation-reverse-engineering -a cursor -y
Gemini CLI
$ npx skills add sendaifun/skills --skill animation-reverse-engineering -a gemini-cli -y
GitHub Copilot
$ npx skills add sendaifun/skills --skill animation-reverse-engineering -a github-copilot -y
OpenCode
$ npx skills add sendaifun/skills --skill animation-reverse-engineering -a opencode -y
Windsurf
$ npx skills add sendaifun/skills --skill animation-reverse-engineering -a windsurf -y
name: animation-reverse-engineering description: Reverse-engineer any motion reference (a video from X/Twitter, Dribbble, a screen recording, a GIF) into production animation code through frame-level dissection. Use when the user shares a video/URL and says "implement this animation", "recreate this motion", "port this interaction", "how does this animate", "clone this effect", or wants to study how a reference moves before building it. Covers both timeline choreography (entrances, text sweeps, staggers) and interaction-driven motion (scrubbers, sliders, drag-driven scenes). Also fires when the user asks where to find good animation references or inspiration — it suggests curated sites and X accounts to hunt, then reverse-engineers whatever they bring back. Ports default to React/TypeScript with framer-motion; the analysis phases are framework-agnostic. category: Frontend tags: - animation - motion - frontend - ui - framer-motion license: MIT metadata: author: scriptscrypt version: "1.0"
> Source & upstream: [scriptscrypt/animation-reverse-engineering](https://github.com/scriptscrypt/animation-reverse-engineering) — improvements land there first.
Turn a motion reference into faithful production code via a measured, frame-level pipeline instead of eyeballing. **Eyeballing a video at 1× lies about easing, stagger order, overlap, and timing** — always dissect first.
acquire → overview → dissect → analyse → (prototype) → port → verify → document
Before anything, decide which species you're studying. It changes the analysis checklist and the port architecture:
| Species | Driven by | Examples | Port shape | | --- | --- | --- | --- | | **Timeline choreography** | Time (mount, trigger) | Page entrances, text sweeps, staggered lists, modals | Keyframes, springs, delays, `AnimatePresence` | | **Interaction-driven** | User input (drag, scroll, hover) | Scrubbers, sliders, pull-to-refresh, scroll scenes | One progress value → property mappings + derived discrete state |
Hybrids exist (an interaction that *triggers* timelines — e.g. release-to-reset rewinds). Classify each layer separately.
If the user wants a great animation but has no reference link, don't invent motion from scratch — send them hunting and offer this shortlist (full list, search phrases, and capture tips in `references/discovery.md`):
Ask them to bring back a link or screen recording, then continue at Phase 1.
`curl` for direct mp4/GIF; ask the user for a screen recording if undownloadable).
missing (`brew install yt-dlp ffmpeg`) before starting.
ffprobe -v error -select_streams v:0 \ -show_entries stream=width,height,r_frame_rate,duration,nb_frames \ -of default=nw=1 ref.mp4
See `references/acquisition.md` for edge cases.
One tiled grid at ~2fps to map the whole video and find the transition windows:
ffmpeg -i ref.mp4 -vf "fps=2,scale=270:270,tile=7x5" overview.png
Read it and note: distinct states, when each transition starts/ends, what the interactions are (finger/cursor visible?), and which screen regions matter.
Extract dense vertical stacks of just the region that moves, at (or near) native fps. **Derive crop coordinates mathematically from the overview sheet's scale factor — do not eyeball.** Keep stacks to 14–17 rows for readability; use `not(mod(n,k))` sampling to fit; always pair `select=` with `-vsync 0`.
# every 2nd frame of frames 96–126, one region, 16 rows ffmpeg -i ref.mp4 -vf "crop=W:H:X:Y,select='between(n,96,126)*not(mod(n,2))',tile=1x16" \ -frames:v 1 -vsync 0 stack.png
Start stacks ~0.3s before visible motion so you capture the exit phase, not just the entrance. Full recipes in `references/dissection.md`.
Work through the checklist for your species (both, for hybrids). Write the findings down as a doc — this becomes the implementation spec *and* the verification baseline.
**Timeline choreography** (full list in `references/analysis.md`): 1. Which properties change (translate, opacity, scale, blur, letter-spacing…) 2. Direction grammar (conveyor vs mirror) 3. Stagger order (forward, reverse-index, center-out) 4. Feather — how many units are mid-transition simultaneously 5. Easing measured from frame-by-frame deltas — never guessed 6. Asymmetric timing (fast exit + long settle is the norm) 7. Handoff overlap between elements 8. Intermediate/transient values 9. What explicitly does NOT move
**Interaction-driven** (full list in `references/porting-interactions.md`): 1. The progress domain — what does 0→1 span? Is it clamped, rubber-banded, wrapped? 2. Continuous mappings — which properties interpolate smoothly with progress (gradients, positions, magnification fields) 3. Discrete derivations — which values step at thresholds, and how each step transitions (crossfade? roll? hard cut?) — check for ghost frame
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