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Hyperframes

OrganizationPopular
spinabot
hyperframes

Author HTML compositions that the `render_video` tool turns into deterministic MP4 video — animated charts and dashboards, data explainers, text/quote cards, kinetic typography, product teasers, and branded short-form social clips. Use when the user asks Brigade to make, render, animate, or produce a video from data, text, or a layout (NOT photoreal/AI footage — that's `generate_video`).

Overview

Publisherspinabot
Repositorybrigade
Skill namehyperframes
Stars
4.4K
Forks
50
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Hyperframes 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.
  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/spinabot/brigade.git /tmp/brigade
mkdir -p .claude/skills
cp -r /tmp/brigade/skills/hyperframes .claude/skills/hyperframes
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hyperframes 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 Hyperframes 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 Hyperframes 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.

hyperframes — HTML → deterministic MP4

The render_video tool renders an HTML composition you write into a pixel-exact MP4. A headless Chrome steps a GSAP master timeline frame by frame, captures one image per frame, and FFmpeg encodes them — so the same HTML always produces the same video. This is the right tool for anything programmatic and data-driven; reach for generate_video only when you need photoreal/AI-generated footage.

Great fits: animated bar/line/donut charts, KPI dashboards, "N facts about X" explainers, quote/announcement cards, kinetic typography, countdowns, before/after reveals, branded intros/outros, vertical social clips.

The composition contract (this is what makes or breaks a render)

Write ONE self-contained HTML document. Two things are mandatory and non-obvious:

  1. A paused GSAP timeline registered to window.__timelines[<composition-id>]. HyperFrames seeks this timeline to render each frame. Total video duration = tl.duration() — you do NOT set duration with an attribute.
  2. data-* attributes on the root and on every timed element.

Root composition element — required: data-composition-id (must match the window.__timelines key), data-width, data-height, data-start; plus data-track-index.

Timed childrendata-start + data-track-index on every one; visible elements (<img>, text/graphic <div>s) also need class="clip"; <img> also takes data-duration. Do not put data-duration on the root/composition — its duration comes from the timeline.

html
<!doctype html>
<html>
  <head>
    <meta charset="utf-8" />
    <!-- Load GSAP (see "GSAP + assets" below). -->
    <script src="https://cdn.jsdelivr.net/npm/gsap@3/dist/gsap.min.js"></script>
    <style>
      body { margin: 0; }
      .stage { width: 1080px; height: 1920px; position: relative; overflow: hidden;
               background: #0b0b12; color: #fff; font-family: system-ui, sans-serif; }
      .title { position: absolute; top: 220px; left: 80px; font-size: 96px;
               font-weight: 800; opacity: 0; transform: translateY(24px); }
    </style>
  </head>
  <body>
    <div class="stage"
         data-composition-id="promo"
         data-width="1080" data-height="1920"
         data-start="0" data-track-index="0">
      <div class="title clip" data-start="0" data-duration="4" data-track-index="0">
        Ship faster.
      </div>
    </div>
    <script>
      // A PAUSED timeline — HyperFrames drives playback by seeking it per frame.
      const tl = gsap.timeline({ paused: true });
      tl.to(".title", { opacity: 1, y: 0, duration: 0.7, ease: "power2.out" }, 0.4)
        .to(".title", { opacity: 0, duration: 0.5, ease: "power2.in" }, 3.5);
      // Register under the SAME id as data-composition-id. This is mandatory.
      window.__timelines = window.__timelines || {};
      window.__timelines["promo"] = tl;
    </script>
  </body>
</html>
  • Vertical 1080×1920 for TikTok/Reels/Shorts, 1920×1080 for landscape, 1080×1080 for square feed posts.
  • Frame rate is an engine default (the tool doesn't expose an fps flag) — author for smooth motion at 30fps.

GSAP + assets

The tool renders a single standalone index.html (no project scaffold), so the composition must bring its own GSAP and assets:

  • GSAP: load it via a <script src="…gsap.min.js"> (CDN as above) or paste the minified source inline. It must be defined before your timeline script runs.
  • Assets: embed images/fonts as data: URIs so nothing depends on external files.
  • Determinism: never drive motion from Date.now(), Math.random(), setTimeout, or a hand-rolled requestAnimationFrame loop — put all motion on the GSAP timeline. Off-timeline animation desyncs from the frame stepper.

Workflow

  1. Write the composition to the contract above with real data/text (never lorem).
  2. Call render_video with { html, output_name?, lint? }. It lints, renders in an isolated subprocess (a real render legitimately takes a minute or more), and returns a saved MP4 as a MEDIA:<path> line.
  3. Deliver it with send_media({ path }).
  4. Handle failures by errorType:
    • composition_invalid — read the lint message, fix the HTML, retry.
    • render_failed — read the stderr excerpt (bad timeline id, missing GSAP, etc.).
    • render_timeout — the composition is too heavy; simplify or shorten it.
    • render_unavailable — the engine/FFmpeg isn't installed (see below).

Design quality (make it look intentional, not templated)

  • Pick a palette that fits the subject; commit to one accent and keep the rest quiet. Set a real type scale; give headings weight and letter-spacing.
  • Stagger reveals (offset each element's timeline position by 0.15–0.3s) so motion reads as choreographed, not simultaneous.
  • Keep text ≥64px from every edge on vertical video so platform UI never clips it.
  • Ease everything (power2.out in, power2.in out). Linear motion reads robotic.
  • For charts, animate the value (bar height, arc sweep, a counting number) on the timeline rather than swapping static frames.

Requirements & install

Needs Node 22+, the @hyperframes/producer engine (an optional dependency — install it to enable video), and FFmpeg on PATH. A headless Chromium is auto-downloaded by the engine on first render (needs network once).

bash
npm i @hyperframes/producer   # the render engine (optional; enables render_video)
# FFmpeg: brew install ffmpeg | winget install ffmpeg | apt install ffmpeg

Overrides: BRIGADE_HYPERFRAMES_PATH (explicit producer entry file), FFMPEG_PATH, BRIGADE_BROWSER_EXECUTABLE / PUPPETEER_EXECUTABLE_PATH.

Frequently asked questions

What does the Hyperframes AI skill do?

Author HTML compositions that the `render_video` tool turns into deterministic MP4 video — animated charts and dashboards, data explainers, text/quote cards, kinetic typography, product teasers, and branded short-form social clips. Use when the user asks Brigade to make, render, animate, or produce a video from data, text, or a layout (NOT photoreal/AI footage — that's `generate_video`).

Why use Hyperframes on TypingMind?

Because you install it once and use it with any model. Hyperframes 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 Hyperframes in TypingMind?

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

Which AI models can use Hyperframes?

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 Hyperframes?

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

Is the Hyperframes AI skill free?

Yes. It is published on GitHub by spinabot 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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