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Hyperframes Cli

Community
boraoztunc
hyperframes-cli

HyperFrames CLI dev loop — `npx hyperframes` for scaffolding (init), validation (lint, inspect), preview, render, and environment troubleshooting (doctor, browser, info, upgrade). Use when running any of these commands or troubleshooting the HyperFrames build/render environment. For asset preprocessing commands (`tts`, `transcribe`, `remove-background`), invoke the `hyperframes-media` skill instead.

Overview

Publisherboraoztunc
Repositoryskills
Skill namehyperframes-cli
Stars
422
Forks
63
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

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

Installation

Install the Hyperframes Cli 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/hyperframes-cli
  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/hyperframes-cli .claude/skills/hyperframes-cli
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hyperframes Cli 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 Cli 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 Cli 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 CLI

Everything runs through npx hyperframes. Requires Node.js >= 22 and FFmpeg.

Workflow

  1. Scaffold — npx hyperframes init my-video
  2. Write — author HTML composition (see the hyperframes skill)
  3. Lint — npx hyperframes lint
  4. Visual inspect — npx hyperframes inspect
  5. Preview — npx hyperframes preview
  6. Render — npx hyperframes render

Lint and inspect before preview. lint catches missing data-composition-id, overlapping tracks, and unregistered timelines. inspect opens the rendered composition in headless Chrome, seeks through the timeline, and reports text spilling out of bubbles/containers or off the canvas.

Scaffolding

bash
npx hyperframes init my-video                        # interactive wizard
npx hyperframes init my-video --example warm-grain   # pick an example
npx hyperframes init my-video --video clip.mp4        # with video file
npx hyperframes init my-video --audio track.mp3       # with audio file
npx hyperframes init my-video --example blank --tailwind # with Tailwind v4 browser runtime
npx hyperframes init my-video --non-interactive       # skip prompts (CI/agents)

Templates: blank, warm-grain, play-mode, swiss-grid, vignelli, decision-tree, kinetic-type, product-promo, nyt-graph.

init creates the right file structure, copies media, transcribes audio with Whisper, and installs AI coding skills. Use it instead of creating files by hand.

When using --tailwind, invoke the tailwind skill before editing classes or theme tokens. The scaffold uses Tailwind v4.2 via the browser runtime, not Studio's Tailwind v3 setup.

Linting

bash
npx hyperframes lint                  # current directory
npx hyperframes lint ./my-project     # specific project
npx hyperframes lint --verbose        # info-level findings
npx hyperframes lint --json           # machine-readable

Lints index.html and all files in compositions/. Reports errors (must fix), warnings (should fix), and info (with --verbose).

Visual Inspect

bash
npx hyperframes inspect                 # inspect rendered layout over the timeline
npx hyperframes inspect ./my-project    # specific project
npx hyperframes inspect --json          # agent-readable findings
npx hyperframes inspect --samples 15    # denser timeline sweep
npx hyperframes inspect --at 1.5,4,7.25 # explicit hero-frame timestamps

Use this after lint and validate, especially for compositions with speech bubbles, cards, captions, or tight typography. It reports:

  • Text extending outside the nearest visual container or bubble
  • Text clipped by its own fixed-width/fixed-height box
  • Text extending outside the composition canvas
  • Children escaping clipping containers

Errors should be fixed before rendering. Warnings are surfaced for agent review; add --strict to fail on warnings too. Repeated static issues are collapsed by default so JSON output stays compact for LLM context windows. If overflow is intentional for an entrance/exit animation, mark the element or ancestor with data-layout-allow-overflow. If a decorative element should never be audited, mark it with data-layout-ignore.

npx hyperframes layout remains available as a compatibility alias for the same visual inspection pass.

Previewing

bash
npx hyperframes preview                   # serve current directory
npx hyperframes preview --port 4567       # custom port (default 3002)

Hot-reloads on file changes. Opens the studio in your browser automatically.

When handing a project back to the user, use the Studio project URL, not the source index.html path:

text
http://localhost:<port>/#project/<project-name>

Use the actual port from the preview output and the project directory name. For example, after npx hyperframes preview --port 3017 in codex-openai-video, report http://localhost:3017/#project/codex-openai-video.

Treat index.html as source-code context only. It is fine to link it as an implementation file, but do not label it as the project or preview surface.

Rendering

bash
npx hyperframes render                                # standard MP4
npx hyperframes render --output final.mp4             # named output
npx hyperframes render --quality draft                # fast iteration
npx hyperframes render --fps 60 --quality high        # final delivery
npx hyperframes render --format webm                  # transparent WebM
npx hyperframes render --docker                       # byte-identical
FlagOptionsDefaultNotes
--outputpathrenders/name_timestamp.mp4Output path
--fps24, 30, 603060fps doubles render time
--qualitydraft, standard, highstandarddraft for iterating
--formatmp4, webmmp4WebM supports transparency
--workers1-8 or autoautoEach spawns Chrome
--dockerflagoffReproducible output
--gpuflagoffGPU-accelerated encoding
--strictflagoffFail on lint errors
--strict-allflagoffFail on errors AND warnings
--variablesJSON object—Override variable values declared in data-composition-variables
--variables-filepath—JSON file with variable values (alternative to --variables)
--strict-variablesflagoffFail render on undeclared keys or type mismatches in --variables

Quality guidance: draft while iterating, standard for review, high for final delivery.

Parametrized renders: the composition declares its variables on the <html> root with data-composition-variables — a JSON array of declarations ({id, type, label, default} per entry) that defines the schema. Scripts inside read the resolved values via window.__hyperframes.getVariables(). The CLI --variables '{"title":"Q4 Report"}' is a JSON object keyed by id that overrides those declared defaults for one render; missing keys fall through, so the same composition runs unchanged in dev preview and in production. (Sub-comp hosts can also override per-instance with data-variable-values — same object shape, scoped to one mount of the sub-composition. See the hyperframes skill for the full pattern.)

Asset Preprocessing

npx hyperframes tts, transcribe, and remove-background produce assets (narration audio, word-level transcripts, transparent video) that get dropped into a composition. Each downloads its own model on first run. For voice selection, whisper model rules (the .en-translates-non-English gotcha), output format choice (VP9 alpha WebM vs ProRes), and the TTS → transcribe → captions chain, invoke the hyperframes-media skill.

Troubleshooting

bash
npx hyperframes doctor       # check environment (Chrome, FFmpeg, Node, memory)
npx hyperframes browser      # manage bundled Chrome
npx hyperframes info         # version and environment details
npx hyperframes upgrade      # check for updates

Run doctor first if rendering fails. Common issues: missing FFmpeg, missing Chrome, low memory.

Other

bash
npx hyperframes compositions   # list compositions in project
npx hyperframes docs           # open documentation
npx hyperframes benchmark .    # benchmark render performance

Frequently asked questions

What does the Hyperframes Cli AI skill do?

HyperFrames CLI dev loop — `npx hyperframes` for scaffolding (init), validation (lint, inspect), preview, render, and environment troubleshooting (doctor, browser, info, upgrade). Use when running any of these commands or troubleshooting the HyperFrames build/render environment. For asset preprocessing commands (`tts`, `transcribe`, `remove-background`), invoke the `hyperframes-media` skill instead.

Why use Hyperframes Cli on TypingMind?

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

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

Which AI models can use Hyperframes Cli?

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 Cli?

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

Is the Hyperframes Cli 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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