FrameJam plugin
FrameJam lets an agent build videos in a chosen style and take edits from a click on a frame with a timestamp
- 69 ★ on the repository
- Last commit
- MIT
Extended access
Why this level
- A local process runs next to the agent, reads renders and opens the review page
- The app downloads playbooks from framejam.ai, and link sharing publishes a version of the video
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add plugins/framejamDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- A local process runs next to the agent, reads renders and opens the review page
- The app downloads playbooks from framejam.ai, and link sharing publishes a version of the video
This is third-party code. Review the repository files before installing.
What it does
FrameJam is a plugin for Claude Code, ChatGPT and Cursor plus a small local app next to the agent. Instead of describing a style in words you name one of 30 example videos or run `/framejam:style` and choose on a page. The agent receives the palette, textures, fonts, easing, transitions, text animation and pacing, then builds the video in that style. Feedback works as with a person: pause and comment, click the spot that is off, or drag a range on the timeline. The Finish review button sends the agent every comment with its timestamp and a frame from the render carrying your pin. Any tool that renders an mp4 will do: Hyperframes, Remotion, Motion Canvas, ffmpeg. Each new version is a fresh round and old ones keep their comments. It runs as a single Node process on your machine.
Who it is for. People who make videos with a coding agent and are tired of giving edits like "the thing at three seconds should be bigger".
Good fit when
- You need to pick a visual style from ready examples and get a working build at once
- An edit concerns one frame and is easier to show with a click than to describe
- The video is built in Remotion or Hyperframes and review runs on the finished mp4
- You need a link for a client with the final version and a single download
- Captions require transcription on a local whisper.cpp model
Not a fit when
- You need text instructions only with no preview: the app opens a review page
- You have no Node 22 or ffmpeg and cannot install them
- You want finished editing with no agent involved
Example request
Make a 20-second product launch video in the clean-cut style and let me review it and leave frame commentsLimitations
Node 22 and ffmpeg are required. `npx -y framejam install` installs the plugin into every detected app and starts the local app. The app downloads playbook updates from framejam.ai and the Feedback button sends the note you write. The 574 MB whisper.cpp model downloads from Hugging Face on first transcription. A project link can go to a client and can be disabled from the project header or with `allowDownload: false`. A video on a link is capped at 500 MB.
How to disable. Remove the plugin through the plugin list in Claude Code, ChatGPT or Cursor. The local app process stops together with the session.
FAQ
How do I install FrameJam?
Run `npx -y framejam install`. Without an app name the command sets up every app it finds: Claude Code, ChatGPT and Cursor.
What does it need?
Node 22 or newer and ffmpeg, installed on macOS with `brew install ffmpeg`. The installer checks both.
Which tools can build the video?
Any that output an mp4: Hyperframes, Remotion, Motion Canvas, ffmpeg. Review runs on the finished render.
How many ready styles are there?
The README names 30 example videos. You choose by name in the prompt or on the `/framejam:style` page.
Do I need an account?
The app runs locally, and an account is needed only for link sharing if you turn it on.
Discussion
No questions or reviews yet.
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README in short
The README explains why style picking and click feedback matter and shows the review page. Install for three apps, working in rounds, link sharing, agent tools and local transcription follow, with a reference of commands and settings below.