# video-use

Edit video by chatting with a coding agent — drop raw takes in a folder, get a cut, graded, subtitled final.mp4 back. The model never watches the footage; it reads a word-level transcript and a rendered timeline.

**Type:** repo
**Added:** 2026-08-09
**Link:** https://github.com/browser-use/video-use
**Topics:** AI Coding, Open Source
**Tags:** agents, cli, speech-to-text

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The LLM never watches the video. One ElevenLabs Scribe call per source gives word-level timestamps, speaker diarization, and audio events; every take packs into a single ~12KB markdown file that is the agent's primary reading view. A `timeline_view` composite — filmstrip, waveform, word labels, silence gaps — is rendered only at decision points, like an ambiguous pause or a retake comparison. Because the surface is the transcript, cuts land on word boundaries. It's the same swap [Browser Use](/directory/browser-use) makes by handing an agent a structured DOM instead of a screenshot, applied to video.

From there the pipeline is opinionated: filler words and dead space go, every segment is color graded, cuts get 30ms audio fades so there's no pop, subtitles burn in as two-word uppercase chunks, and animation overlays are generated by parallel sub-agents through HyperFrames, Remotion, Manim, or PIL. The agent then runs `timeline_view` over its own render at every cut boundary and fixes what it finds before showing a preview. Session memory persists in `project.md`.

Two things to budget for. It needs an ElevenLabs API key and a local ffmpeg, so a run costs transcription minutes rather than nothing. And it installs by cloning the repo and symlinking it into the agent's skills directory — `~/.claude/skills`, `~/.codex/skills` — not through a package manager, so updates are a `git pull`.

MIT, ~20k stars.

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## Links

- Directory entry: https://andrey-markin.com/directory/video-use
- All directory entries: https://andrey-markin.com/directory
- Contact: https://andrey-markin.com/#contact