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Reanimate

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NiazMorshed2007
reanimate

Clone a section, widget, page or animation from any reference (a live website URL, a screen recording, an mp4/mov/webm, a gif, a Lottie file, a prototype export) frame by frame into the user's own codebase, then record the clone and verify it against the reference frame by frame, iterating until timing, easing, sequence and layout match. Use whenever the user wants to clone, copy, replicate, recreate, reverse-engineer, port or "steal" a hero, section, widget, marquee, carousel, hover effect, page transition, loader, scroll animation or interaction from a site or video, says "make it look/feel/move like this", "same animation as", "match this exactly", or hands over a gif/video and asks to build it, including when they also want to add their own content, colours or extra features on top, or only want part of the reference (one section, one widget, a few seconds). Covers canvas, WebGL, WebGPU and three.js / 3D scenes (shaders, particles, globes, glTF models) as well as CSS and JS motion. Pixel-level matching of fonts, colours and spacing is done only when they ask for it.

Overview

PublisherNiazMorshed2007
Repositoryreanimate
Skill namereanimate
Stars
162
Forks
13
Bundled files
17
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 17 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NiazMorshed2007 on GitHub. Read the source before you install it.

Installation

Install the Reanimate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NiazMorshed2007/reanimate/tree/main/skills/reanimate
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NiazMorshed2007/reanimate.git /tmp/reanimate
mkdir -p .claude/skills
cp -r /tmp/reanimate/skills/reanimate .claude/skills/reanimate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Reanimate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Reanimate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Reanimate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

reanimate

Rebuild what the user points at so that it moves the way the reference moves, prove it with a frame-by-frame comparison, and keep going until the comparison passes. The deliverable is code in the user's project plus evidence (numbers and side-by-side sheets), never "it looks about right".

What "done" means

Pick the fidelity level from the user's words and state it in the first message; it decides what you verify.

LevelWhenMust matchMay differ
motion-faithful (default)"clone this animation", "make ours feel like theirs", "same hero as X but our copy"trigger, sequence and order, stagger, timing of every step (±80 ms), easing family, direction and distance of movement relative to the element size, layout proportionscopy, colours, fonts, images, brand details
pixel-faithful"match it exactly", "pixel-perfect", "details should match", "1:1"everything above plus fonts, sizes, colours, spacing, radii, shadows, assets; mean frame mismatch ≤ 2 %nothing the user did not ask to change
mixed"clone X and add Y", "like theirs but with our pricing tiers"the cloned parts at one of the levels abovethe additions, which you describe and show but verify only for not breaking the cloned motion

The user can narrow the target to one section, one widget, one page, or a time range of a video ("the first 3 seconds", "0:12 to 0:15"). Clone exactly that; do not pull in the rest of the page.

Workflow

Everything below lives in .reanimate/<name>/ inside the user's project (add it to .gitignore unless they want the evidence committed). Keep each round's artefacts; they are the proof.

0. Scope

Write three lines at the top of .reanimate/<name>/spec.md before any capture:

  • Target: what to clone, as precisely as the user said it (URL + selector / time range / "the toggle in the gif").
  • Destination: where the code goes and in what stack (read package.json, existing components and the animation library already in use; match it rather than introducing a new one).
  • Fidelity: motion-faithful, pixel-faithful or mixed, plus the list of additions for mixed.

Infer what you can from the request and the repo. Ask only when two readings lead to different work (for instance "the hero" on a page with two candidate sections). When a reference is a login-walled page or a YouTube/Loom link you cannot download here, ask the user for a screen recording and continue with everything else meanwhile.

1. Setup

<skill> below is the directory this SKILL.md lives in. Scripts need Bun; the first run downloads Playwright's Chromium and a static ffmpeg (about 250 MB).

bash
bash <skill>/scripts/setup.sh      # installs playwright, ffmpeg, pixelmatch once; prints "ready"

All scripts are run with bun <skill>/scripts/<name>.ts --help. They are deterministic and share one rule: capture the reference and the clone with the same viewport, selector crop, trigger, duration and fps, otherwise the comparison measures your setup instead of your work.

2. Capture the reference

Read references/capture.md for the recipe for your source type. In short:

  • Website: capture.ts --url … --out ref --selector <section> --trigger load|scroll|hover|click|none --duration … --track "<moving elements>". You get video.webm, frames/, inspect.json (declared animations, keyframes, computed styles, fonts, detected libraries) and track.json (per animation frame position, size, opacity, transform of each tracked element). For CSS/WAAPI motion inspect.json often contains the exact durations, delays and easings: use them, it beats estimating.
  • Video or gif: frames.ts --in file --out ref/frames --fps 10..30 --start … --end … --crop …. Probe first with --probe, then view a few frames to find the crop of the widget you are cloning.
  • Canvas, WebGL, WebGPU, 3D (inspect.json › canvases shows one, or the page uses three.js, Pixi, Babylon, Spline…): add --clock virtual --gl --assets to the capture and read gl/summary.md (gl.ts summary <out>). You get the shader sources, every constant uniform, the scene graph, the render passes, the textures and models, and each animated uniform or object property as a channel in gl-track.json. The virtual clock makes every frame exact and every capture identical, random particles included. Read references/webgl.md.
  • Lottie / Rive / prototype export: the file is the spec; read it, do not re-derive it from pixels.

Then build labelled sheets and look at them: sheet.ts filmstrip --frames ref/frames --out ref/sheets. Read every sheet with the image viewer. This is the frame-by-frame inspection the user asked for; do not skip it or sample only the first sheet.

3. Write the motion spec

Fill spec.md using the template in references/analysis.md. One row per element per property: trigger, start time, duration, delay or stagger, from → to, easing, notes. Get the numbers from, in order of preference: inspect.json animations and keyframes → easing.ts on track.json, or on gl-track.json --channel for canvas → reading frames (first frame where it changes, last frame where it changes, overshoot or not). Also note the static facts the motion depends on: element sizes and positions, z-order, overflow clipping, transform origins, and for pixel-faithful work fonts, colours, spacing and assets.

The spec is the contract between the reference and the clone. Every row becomes a check in step 5. If a row has a "?" you have not finished reading the frames.

4. Build

Implement in the user's stack following references/implementation.md (easing tables, stagger math, scroll and hover triggers, reduced motion). Keep the DOM structure close to the reference's role structure so the tracked selectors have equivalents. For mixed work, put additions in clearly separate components or blocks and mention them in spec.md under "Additions".

Give the clone a way to be captured the same way as the reference: a route or a static page that renders the component at the reference viewport with the same trigger. A dev server is fine (capture.ts --url http://localhost:5173/…); a standalone HTML file also works.

5. Verify, fix, repeat

Capture the clone with the exact command used for the reference, changing only --url and --out clone-N, then:

bash
bun <skill>/scripts/compare.ts --ref ref/frames --clone clone-N/frames --out compare-N
bun <skill>/scripts/sheet.ts compare --ref ref/frames --clone clone-N/frames --diff compare-N/diff --out compare-N/sheets --every 2
bun <skill>/scripts/easing.ts --track clone-N/track.json --selector "<el>" --prop <translateY|opacity|…> --compare-track ref/track.json

For canvas work, also run gl.ts compare --ref ref --clone clone-N, which checks canvas settings, draw structure and every animated channel.

Read references/verify.md for how to read the report, the pass criteria for each fidelity level and the fixes that each kind of failure usually needs. Look at the compare sheets yourself, every round; the numbers tell you that something is off, the sheets tell you what.

Loop until every spec row passes. Each round: change the smallest thing the evidence points at, re-capture, re-compare. Expect 2 to 5 rounds. If after 5 rounds a row still fails, stop and report it with its numbers and the reason (missing font, a shader or model the user may not copy, a physics spring you approximated), do not quietly lower the threshold or drop the row.

6. Report

The final message must stand alone:

  • Fidelity level and what was cloned, what was added.
  • Where the code is (files) and how to trigger the motion.
  • A short table of the last compare round: timing error, mean mismatch, easing match per key element, pass/fail.
  • Paths to the final compare sheets, embedded as images when the environment shows them.
  • Residual deviations, each with a number and a reason.

Pitfalls that waste rounds

  • Different viewport or crop between reference and clone: fix the capture before touching code.
  • Judging from the first frame and the last frame only: the easing lives in the middle frames; read the sheets.
  • Fonts: a different fallback font changes every frame's pixels. For pixel-faithful work load the same font (from inspect.json fonts) before judging mismatch; for motion-faithful work ignore text pixels and read the timing columns.
  • Reference recorded on a loaded page vs clone captured cold: use --wait-before, or --trigger none with a --pre-js that restarts the animation, so both start from rest.
  • Scroll-driven motion: it is a function of scroll position, not time. Capture both with the same --scroll-steps and --scroll-ms, and compare per scroll position (the track's scrollY), not per second.
  • JS libraries (GSAP, Framer Motion springs): --playback-rate does not slow them. Use track.json and easing.ts (it reports overshoot and "spring-like") and tune spring parameters by the overshoot and settle time.
  • Videos of someone else's screen have a cursor, a browser chrome and compression noise: crop them out and raise --pixel-threshold a little (0.15) rather than chasing noise.
  • Canvas and WebGL captured on the real clock: frames drop in software GL and random content differs on every load, so the comparison measures the machine. Capture both sides with --clock virtual and the same --seed.
  • Rebuilding a shader from screenshots: the trace already has its source and every constant. Read gl/shaders/ and the fixed uniforms before writing GLSL.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Reanimate AI skill do?

Clone a section, widget, page or animation from any reference (a live website URL, a screen recording, an mp4/mov/webm, a gif, a Lottie file, a prototype export) frame by frame into the user's own codebase, then record the clone and verify it against the reference frame by frame, iterating until timing, easing, sequence and layout match. Use whenever the user wants to clone, copy, replicate, recreate, reverse-engineer, port or "steal" a hero, section, widget, marquee, carousel, hover effect, page transition, loader, scroll animation or interaction from a site or video, says "make it look/fe...

Why use Reanimate on TypingMind?

Because you install it once and use it with any model. Reanimate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Reanimate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NiazMorshed2007/reanimate/tree/main/skills/reanimate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Reanimate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Reanimate?

As many as you like. As long as a model supports skills, you can use Reanimate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Reanimate AI skill free?

Yes. It is published on GitHub by NiazMorshed2007 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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