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5e8ff36675
Move per-command examples from the centralized `help.ts` record into each command file as `export const examples: Example[]`. help.ts now dynamically imports them at --help time. This means adding a new command and its examples happens in one file instead of two, reducing the chance of forgetting examples. Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
188 lines
9.7 KiB
Markdown
188 lines
9.7 KiB
Markdown
# Hyperframes
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## Skills — USE THESE FIRST
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This repo ships skills that are installed globally via `npx hyperframes skills` (runs automatically during `hyperframes init`). **Always use the appropriate skill instead of writing code from scratch or fetching external docs.**
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### HyperFrames Skills (from this repo)
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| Skill | Invoke with | When to use |
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| ------------------------ | ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| **hyperframes-compose** | `/hyperframes-compose` | Creating ANY HTML composition — videos, animations, title cards, overlays. Contains required HTML structure, `class="clip"` rules, GSAP timeline patterns, and rendering constraints. |
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| **hyperframes-captions** | `/hyperframes-captions` | Any task involving text synced to audio: captions, subtitles, lyrics, lyric videos, karaoke. Also covers transcription strategy (whisper model selection, transcript format). |
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| **hyperframes-tts** | `/hyperframes-tts` | Generating speech from text: narration, voiceovers, text-to-speech. Voice selection, speed control, and combining TTS output with compositions. |
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| **marker-highlight** | `/marker-highlight` | Animated text highlighting — marker sweeps, hand-drawn circles, burst lines, scribble, sketchout. Use with captions for dynamic emphasis. |
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### GSAP Skills (from [greensock/gsap-skills](https://github.com/greensock/gsap-skills))
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| Skill | Invoke with | When to use |
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| ---------------------- | --------------------- | -------------------------------------------------------------------------------- |
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| **gsap-core** | `/gsap-core` | `gsap.to()`, `from()`, `fromTo()`, easing, duration, stagger, defaults |
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| **gsap-timeline** | `/gsap-timeline` | Timeline sequencing, position parameter, labels, nesting, playback |
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| **gsap-performance** | `/gsap-performance` | Performance best practices — transforms over layout props, will-change, batching |
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| **gsap-plugins** | `/gsap-plugins` | ScrollTrigger, Flip, Draggable, SplitText, and other GSAP plugins |
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| **gsap-scrolltrigger** | `/gsap-scrolltrigger` | Scroll-linked animations, pinning, scrub, triggers |
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| **gsap-utils** | `/gsap-utils` | `gsap.utils` helpers — clamp, mapRange, snap, toArray, wrap, pipe |
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### Why this matters
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The skills encode HyperFrames-specific patterns (e.g., required `class="clip"` on all timed elements, GSAP timeline registration via `window.__GSAP_TIMELINE`, `data-*` attribute semantics) that are NOT in generic web docs. Skipping the skills and writing from scratch will produce broken compositions.
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### Rules
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- When creating or modifying HTML compositions → invoke `/hyperframes-compose` BEFORE writing any code
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- When adding captions, subtitles, lyrics, or any text synced to audio → invoke `/hyperframes-captions` BEFORE writing any code
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- When transcribing audio or choosing a whisper model → invoke `/hyperframes-captions` BEFORE running any transcription tool
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- When generating speech from text (narration, voiceover, TTS) → invoke `/hyperframes-tts` BEFORE running any TTS command
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- When creating a video from audio (music video, lyric video, audio visualizer with text) → invoke BOTH `/hyperframes-compose` AND `/hyperframes-captions`
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- When writing GSAP animations → invoke `/gsap-core` and `/gsap-timeline` BEFORE writing any code
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- When optimizing animation performance → invoke `/gsap-performance` BEFORE making changes
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- When adding animated text emphasis (highlight sweeps, circles, bursts, scribbles) → invoke `/marker-highlight` BEFORE writing any code
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- After creating or editing any `.html` composition → run `npx hyperframes lint` and `npx hyperframes validate` in parallel, fix all errors before opening the studio or considering the task complete. `lint` checks the HTML structure statically; `validate` loads the composition in headless Chrome and catches runtime JS errors, missing assets, and failed network requests. Always validate before `npx hyperframes preview`.
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### Installing skills
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```bash
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npx skills add heygen-com/hyperframes # HyperFrames skills
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npx skills add greensock/gsap-skills # GSAP skills
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```
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Uses [vercel-labs/skills](https://github.com/vercel-labs/skills). Installs to Claude Code, Gemini CLI, and Codex CLI by default. Pass `-a <agent>` for other targets.
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## Project Overview
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Open-source video rendering framework: write HTML, render video.
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```
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packages/
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cli/ → hyperframes CLI (create, preview, lint, render)
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core/ → Types, parsers, generators, linter, runtime, frame adapters
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engine/ → Seekable page-to-video capture engine (Puppeteer + FFmpeg)
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producer/ → Full rendering pipeline (capture + encode + audio mix)
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studio/ → Browser-based composition editor UI
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```
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## Development
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```bash
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pnpm install # Install dependencies
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pnpm build # Build all packages
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pnpm test # Run tests
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```
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### Linting & Formatting
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This project uses **oxlint** and **oxfmt** (not biome, not eslint, not prettier).
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```bash
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bunx oxlint <files> # Lint
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bunx oxfmt <files> # Format (write)
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bunx oxfmt --check <files> # Format (check only, used by pre-commit hook)
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```
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Always run both on changed files before committing. The lefthook pre-commit hook runs `bunx oxlint` and `bunx oxfmt --check` automatically.
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### Adding CLI Commands
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When adding a new CLI command:
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1. Define the command in `packages/cli/src/commands/<name>.ts` using `defineCommand` from citty
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2. **Export `examples`** in the same file — `export const examples: Example[] = [...]` (import `Example` from `./_examples.js`). These are displayed by `--help`.
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3. Register it in `packages/cli/src/cli.ts` under `subCommands` (lazy-loaded)
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4. Validate by running `npx tsx packages/cli/src/cli.ts <name> --help` and verifying the examples section appears
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## Key Concepts
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- **Compositions** are HTML files with `data-*` attributes defining timeline, tracks, and media
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- **Frame Adapters** bridge animation runtimes (GSAP, Lottie, CSS) to the capture engine
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- **Producer** orchestrates capture → encode → audio mix into final MP4
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- **BeginFrame rendering** uses `HeadlessExperimental.beginFrame` for deterministic frame capture
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## Transcription
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HyperFrames uses word-level timestamps for captions. The `hyperframes transcribe` command handles both transcription and format conversion.
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### Quick reference
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```bash
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# Transcribe audio/video (local whisper.cpp, no API key)
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npx hyperframes transcribe audio.mp3
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npx hyperframes transcribe video.mp4 --model medium.en --language en
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# Import existing transcript from another tool
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npx hyperframes transcribe subtitles.srt
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npx hyperframes transcribe subtitles.vtt
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npx hyperframes transcribe openai-response.json
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```
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### Whisper models
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Default is `small.en`. Upgrade for better accuracy:
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| Model | Size | Use case |
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| ---------- | ------ | ------------------------------ |
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| `tiny` | 75 MB | Quick testing |
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| `base` | 142 MB | Short clips, clear audio |
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| `small` | 466 MB | **Default** — most content |
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| `medium` | 1.5 GB | Important content, noisy audio |
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| `large-v3` | 3.1 GB | Production quality |
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**Only use `.en` suffix when you know the audio is English.** `.en` models translate non-English audio into English instead of transcribing it.
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### Supported transcript formats
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The CLI auto-detects and normalizes: whisper.cpp JSON, OpenAI Whisper API JSON, SRT, VTT, and pre-normalized `[{text, start, end}]` arrays.
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### Improving transcription quality
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If captions are inaccurate (wrong words, bad timing):
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1. **Upgrade the model**: `--model medium.en` or `--model large-v3`
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2. **Set language**: `--language en` to filter non-target speech
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3. **Use an external API**: Transcribe via OpenAI or Groq Whisper API, then import the JSON with `hyperframes transcribe response.json`
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See the `/hyperframes-captions` skill for full details on model selection and API usage.
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## Text-to-Speech
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Generate speech audio locally using Kokoro-82M (no API key, runs on CPU). Useful for adding voiceovers to compositions.
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### Quick reference
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```bash
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# Generate speech from text
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npx hyperframes tts "Welcome to HyperFrames"
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# Choose a voice and output path
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npx hyperframes tts "Hello world" --voice am_adam --output narration.wav
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# Read text from a file
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npx hyperframes tts script.txt --voice bf_emma
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# Adjust speech speed
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npx hyperframes tts "Fast narration" --speed 1.2
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# List available voices
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npx hyperframes tts --list
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```
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### Voices
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Default voice is `af_heart`. The model ships with 54 voices across 8 languages:
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| Voice ID | Name | Language | Gender |
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| ------------ | ------- | -------- | ------ |
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| `af_heart` | Heart | en-US | Female |
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| `af_nova` | Nova | en-US | Female |
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| `am_adam` | Adam | en-US | Male |
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| `am_michael` | Michael | en-US | Male |
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| `bf_emma` | Emma | en-GB | Female |
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| `bm_george` | George | en-GB | Male |
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Use `npx hyperframes tts --list` for the full set, or pass any valid Kokoro voice ID.
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### Requirements
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- Python 3.8+ (auto-installs `kokoro-onnx` package on first run)
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- Model downloads automatically on first use (~311 MB model + ~27 MB voices, cached in `~/.cache/hyperframes/tts/`)
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