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Hyperframes Cli

OrganizationPopular
heygen-com
hyperframes-cli

The HyperFrames CLI by job - scaffold, check, look at frames, edit the timeline, preview, render locally or in the cloud, publish, project history - plus reading its JSON and recovering from build or render failures.

Overview

Publisherheygen-com
Repositoryhyperframes
Skill namehyperframes-cli
Stars
73.3K
Forks
6.6K
Bundled files
12
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.

  • 12 bundled files

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

  • Open source

    Published by heygen-com 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/heygen-com/hyperframes/tree/main/skills/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/heygen-com/hyperframes.git /tmp/hyperframes
mkdir -p .claude/skills
cp -r /tmp/hyperframes/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.

Plugin installs: Before setup or freshness commands, follow plugin execution rules when this skill is inside a HyperFrames plugin.

HyperFrames CLI

Run npx hyperframes <command> unless the project gives a wrapper; then use the wrapper. It needs Node.js 22+ and FFmpeg. Every command has --help; most take --json, and a failure prints ✗ …, a Fix: line and exits non-zero.

Commands by job

JobCommands
Startinit <dir> (blank; --example <name> only when asked), capture <url>
Read a projectinfo, compositions, timeline --json, docs <topic>
Check itlint while writing; check --json as the gate (lint, runtime, layout, contrast)
Look at itsnapshot (--at <t,…>, --range START,END, --composition <id>, --zoom, --angle, --against <video>), keyframes, compare, audio
Edit the timelinetimeline with move, trim, split, set, duplicate, delete, apply, undo, ids
Reusecatalog, add (/hyperframes-registry)
Media and soundmedia-treatment, grade-compare, remove-background, tts, transcribe, beats, normalize-audio (/media-use)
Show and shippreview, present (/slideshow), render, publish, cloud, lambda, cloudrun
Desktop appopen, catch-up
Upkeepdoctor, browser, upgrade, skills, usage, clean, feedback

validate, inspect and layout are deprecated aliases of check; events is telemetry for skills' own scripts. Don't run them.

The loop

  1. Write, then npx hyperframes lint after the first pass and after structural changes.
  2. npx hyperframes check --json and fix every error. While a lint error remains the layout and contrast audits don't run; "0 samples" means nothing was checked. Contrast failures carry a suggestedColor. A finding at a single sample (an entrance in flight) is info; a 3 s+ video with no visible change fails sweep_static.
  3. npx hyperframes snapshot and read the PNGs (under .hyperframes/artifacts/snapshots/): that is how you see the video. With sub-compositions, snapshot a midpoint of every scene; tiny unstyled content or a missing hero is a mount defect (../hyperframes/references/format.md).
  4. npx hyperframes preview --background, check the URL answers 200, give the person the project URL and wait, unless they asked for the file or for no stops. Passing checks alone is not a reason to render.
  5. When it is time to render (step 4): npx hyperframes render --quality looks --output out.mp4 (draft while iterating, delivery for the final). Confirm the file is non-empty and its ffprobe duration matches the root data-duration, then look at decoded frames.

"This element" or the current selection: npx hyperframes preview --context --json --context-fields selection; no-selection means ask them to click it.

Edit the timeline

These are the edits Studio itself makes, so the result stays in Studio's shape.

  • timeline --json lists clips with absolute absStart/absEnd, owning file and the #id ref the edit commands take (timeline ids stamps missing ids).
  • timeline move|trim|split|set|duplicate|delete <ref> … --plan --json previews one edit; run it again without --plan. --start, --end, --duration set one edge or the length.
  • An edit is refused when the clip would overlap a neighbour (--overwrite, or move the neighbour first) or end past its composition: raise the root's data-duration first. No command changes data-duration.
  • Several edits at once: a JSON file such as [{"verb": "move", "ref": "#outro", "time": "9"}], then timeline apply plan.json --json. Each run prints a receipt; save it and timeline undo receipt.json reverts it.

Project history

Every write is kept and can be undone. At the start of a turn, npx hyperframes history begin --who <you> --label "<plan>", then history --since mine --who <you> to see what the person changed; build on their edits. A check failed or they say it got worse: history undo --who <you>, never hand-edit back. End the turn with history end.

Render where

NeedCommand
Localrender --quality looks --output out.mp4 (draft, delivery)
Reproducible containerrender --docker --strict --output out.mp4
Batch from variablesrender --batch rows.json --output "renders/{name}.mp4"
Hosted, no local Chrome or FFmpegcloud render (references/cloud.md)
Your own AWS or GCPlambda render, cloudrun render (references/lambda.md, references/cloudrun.md)

A 30 s film renders in a minute or two: run it in the foreground. Detach only a render longer than your tool's timeout (HYPERFRAMES_RENDER_DETACHED=1, its own group, output to a log) and wait with until grep -qE 'Render (complete|failed)' render.log; do sleep 5; done, never pgrep -f, which matches its own loop and waits until the tool times out.

After a verified render, send one feedback --rating, plus a report for anything the person asked for that HyperFrames can't do, unless telemetry is off: references/feedback.md.

When a command fails

SymptomFix
Chrome missing or won't startnpx hyperframes browser ensure; doctor --json always exits 0, gate on .ok
A heavy page isn't ready in timeRaise --timeout on check or snapshot
Unusual codec looks blankKeep --proxy on (the default)
Render slow on LinuxThe summary's second line says screenshot + software gpu: the slow path
capture fails or writes BLOCKED.mdTake nothing from its partial files; retry into a new -o folder
Disk tightclean --dry-run, then clean; never delete .hyperframes (it holds history)

References

Read the row before running its command.

CommandsRead
init, capture, skillsreferences/init-and-scaffold.md
lint, check, motion sidecars, snapshotreferences/lint-validate-inspect.md
compare, grade-compare, render --batchreferences/compare-and-batch.md
beatsreferences/beats.md
preview, play, render, publish, Studio contextreferences/preview-render.md
doctor, browserreferences/doctor-browser.md
auth, cloud, template variablesreferences/cloud.md
lambda, cloudrunreferences/lambda.md, references/cloudrun.md
info, upgrade, compositions, timeline, docs, usage, telemetryreferences/upgrade-info-misc.md
--strict flags, run ids, clean, shader lint, JSON pathsreferences/conventions.md
keyframes../hyperframes/references/motion.md (Seeing motion)

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 Hyperframes Cli AI skill do?

The HyperFrames CLI by job - scaffold, check, look at frames, edit the timeline, preview, render locally or in the cloud, publish, project history - plus reading its JSON and recovering from build or render failures.

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/heygen-com/hyperframes/tree/main/skills/hyperframes-cli. 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 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 heygen-com 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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