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Contribute Catalog

Community
boraoztunc
contribute-catalog

Author a new HyperFrames registry block (caption style, VFX block, transition, lower third) or component (text effect, overlay, snippet) and ship it as an upstream PR to the hyperframes repo. Use ONLY when the user wants to CONTRIBUTE to the public catalog — for in-project caption/transition authoring use the `hyperframes` skill, for installing existing registry items use the `hyperframes-registry` skill.

Overview

Publisherboraoztunc
Repositoryskills
Skill namecontribute-catalog
Stars
422
Forks
63
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Contribute Catalog 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/boraoztunc/skills/tree/main/contribute-catalog
  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/boraoztunc/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/contribute-catalog .claude/skills/contribute-catalog
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Contribute Catalog 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 Contribute Catalog 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 Contribute Catalog 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.

Contribute to HyperFrames Registry

Guide the user from idea to merged PR for a new registry block or component.

Workflow

1. Clarify → 2. Scaffold → 3. Build → 4. Validate → 5. Preview → 6. Ship

Step 1: Clarify

Ask what they're building. The registry has two item types:

  • Block (registry/blocks/, type hyperframes:block) — a full standalone composition with fixed dimensions and duration. Caption styles, VFX effects, title cards, lower thirds.
  • Component (registry/components/, type hyperframes:component) — a reusable snippet with no fixed dimensions or duration. CSS effects, text treatments, overlays that adapt to any composition size.

Then ask:

  • One-sentence description of the effect
  • Visual reference (URL, screenshot, or description)
  • Who uses this and when?

Step 2: Scaffold

Create the registry structure:

For blocks:

registry/blocks/{block-name}/
  {block-name}.html
  registry-item.json

For components:

registry/components/{component-name}/
  {component-name}.html
  registry-item.json

Naming convention:

Item nameID prefixExample IDs
cap-hormozihzhz-cg-0, hz-cw-3
cap-typewritertwtw-cg-0, tw-ch-0-5
vfx-chromevcvc-canvas

Use a 2-3 letter prefix. ALL element IDs must use this prefix to avoid collisions in sub-compositions.

registry-item.json for blocks:

json
{
  "$schema": "https://hyperframes.heygen.com/schema/registry-item.json",
  "name": "{block-name}",
  "type": "hyperframes:block",
  "title": "{Human Title}",
  "description": "{one sentence}",
  "dimensions": { "width": 1920, "height": 1080 }, // adjust: 1080x1920 for portrait/social
  "duration": 10, // adjust for your composition
  "tags": ["{category}", "{subcategory}"],
  "files": [
    {
      "path": "{block-name}.html",
      "target": "compositions/{block-name}.html",
      "type": "hyperframes:composition"
    }
  ]
}

registry-item.json for components (no dimensions or duration):

json
{
  "$schema": "https://hyperframes.heygen.com/schema/registry-item.json",
  "name": "{component-name}",
  "type": "hyperframes:component",
  "title": "{Human Title}",
  "description": "{one sentence}",
  "tags": ["{category}"],
  "files": [
    {
      "path": "{component-name}.html",
      "target": "compositions/components/{component-name}.html",
      "type": "hyperframes:snippet"
    }
  ]
}

Step 3: Build

Apply the correct template based on type. See templates.md for copy-paste starters.

Caption blocks

Non-negotiable caption rules:

  • Font: 96px minimum for proportional fonts. 64-72px acceptable for monospace (wider characters need less size).
  • Readability: -webkit-text-stroke: 2-3px OR multi-layer text-shadow
  • Overflow: call window.__hyperframes.fitTextFontSize() on every group
  • Karaoke: highlight active word via tl.to(wordEl, { color/scale }, WORDS[wi].start)
  • Hard kill: tl.set(groupEl, { opacity: 0, visibility: "hidden" }, g.end) on EVERY group
  • Never use tl.from(el, { opacity: 0 }) at the same position as tl.set(el, { opacity: 1 }) — the from clobbers the set. Use tl.to instead.

Per-character animation (typewriter, scramble):

  • Wrap each character in <span> with ID {prefix}-ch-{group}-{char}
  • Stagger via tl.set at computed intervals from word timestamps
  • Cursors/decorative elements: use tl.set at intervals — NOT CSS animation (not seekable)

Positioning variants:

  • Centered: display: flex; align-items: center; justify-content: center;
  • Lower-third: position: absolute; bottom: 100px; left: 0; width: 100%; text-align: center;
  • Left-aligned: position: absolute; bottom: 100px; left: 120px; text-align: left;
VFX blocks (Three.js)
  • Use three@0.147.0 from CDN (global script)
  • tl.eventCallback("onUpdate", renderScene); renderScene(); — NO requestAnimationFrame
  • State proxy pattern: GSAP animates plain JS object, render function reads it
  • Seeded PRNG (mulberry32) for randomness
All types
  • data-composition-id MUST match window.__timelines["id"]
  • All element IDs prefixed with block abbreviation
  • gsap.timeline({ paused: true }) — always paused
  • No Math.random(), no Date.now()

Step 4: Validate

bash
hyperframes lint                    # 0 errors required
hyperframes validate --no-contrast  # 0 console errors required

Step 5: Preview

bash
# Render preview video
hyperframes render -o preview.mp4

# Snapshot for visual QA
hyperframes snapshot --at "1.0,3.0,5.0,7.0"

# Publish to hyperframes.dev for review
npx hyperframes publish

Catalog preview image — The catalog card uses a PNG at docs/images/catalog/{kind}/{name}.png (where {kind} is blocks or components). Generate it from a snapshot, then:

  • HeyGen internal contributors: run scripts/upload-docs-images.sh (requires AWS profile engineering-767398024897)
  • External contributors: attach the preview MP4 to your PR description. A maintainer will generate and upload the catalog image before merging.

Step 6: Ship

All steps are required. Missing any one produces a broken catalog entry.

{kind} is blocks or components depending on what you built in Step 1.

bash
# 1. Create branch
git checkout -b feat/registry-{name}

# 2. Format HTML
npx oxfmt registry/{kind}/{name}/*.html

# 3. Update registry/registry.json — add entry to the "items" array:
#    { "name": "{name}", "type": "hyperframes:block" }  (or "hyperframes:component")

# 4. Generate catalog docs page
npx tsx scripts/generate-catalog-pages.ts

# 5. Publish to hyperframes.dev so reviewers can preview
npx hyperframes publish

# 6. Stage everything
git add registry/{kind}/{name}/ registry/registry.json docs/catalog/

# 7. Commit
git commit -m "feat(registry): add {name} — {one sentence}"

# 8. Push and open PR with hyperframes.dev link
git push origin feat/registry-{name}
gh pr create --title "feat(registry): {name}" --body "preview: {hyperframes.dev-url}"

If you don't have a GitHub account: you need one to open a PR. Sign up at https://github.com/signup, then run gh auth login.

Quality Gate

  • hyperframes lint → 0 errors
  • hyperframes validate → 0 console errors
  • npx oxfmt --check passes
  • registry/registry.json updated with new entry
  • scripts/generate-catalog-pages.ts run (docs page generated)
  • npx hyperframes publish run (claim your project URL)
  • Preview MP4 attached to PR (external) or catalog PNG uploaded (internal)
  • All IDs unique and prefixed

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 Contribute Catalog AI skill do?

Author a new HyperFrames registry block (caption style, VFX block, transition, lower third) or component (text effect, overlay, snippet) and ship it as an upstream PR to the hyperframes repo. Use ONLY when the user wants to CONTRIBUTE to the public catalog — for in-project caption/transition authoring use the `hyperframes` skill, for installing existing registry items use the `hyperframes-registry` skill.

Why use Contribute Catalog on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/boraoztunc/skills/tree/main/contribute-catalog. 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 Contribute Catalog?

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 Contribute Catalog?

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

Is the Contribute Catalog AI skill free?

Yes. It is published on GitHub by boraoztunc under the Apache-2.0 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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