Video-use: Edit videos with coding agents

Browser Use released video-use, an open-source tool that lets users edit videos by chatting with coding agents like Claude Code, dropping raw footage into a folder and receiving a final.mp4 without presets or menus. The tool cuts filler words, auto color grades, burns subtitles, generates animation overlays via HyperFrames or Remotion, and self-evaluates output at every cut boundary, persisting session memory in project.md.

Introducing video-use — edit videos with Claude Code. 100% open source. Drop raw footage in a folder, chat with Claude Code, get final.mp4 back. Works for any content — talking heads, montages, tutorials, travel, interviews — without presets or menus. Try video-use in Browser Use Cloud https://cloud.browser-use.com/v4?utm campaign=video-use-use-in-cloud&utm source=github . Cuts out filler words umm , uh , false starts and dead space between takes Auto color grades every segment warm cinematic, neutral punch, or any custom ffmpeg chain 30ms audio fades at every cut so you never hear a pop Burns subtitles in your style — 2-word UPPERCASE chunks by default, fully customizable Generates animation overlays via HyperFrames https://github.com/heygen-com/hyperframes , Remotion https://www.remotion.dev/ , Manim https://www.manim.community/ , or PIL — spawned in parallel sub-agents, one per animation Self-evaluates the rendered output at every cut boundary before showing you anything Persists session memory in project.md so next week's session picks up where you left off Paste into Claude Code, Codex, Hermes, Openclaw, or any agent with shell access: Set up https://github.com/browser-use/video-use for me. Read install.md first to install this repo, wire up ffmpeg, register the skill with whichever agent you're running under, and set up the ElevenLabs API key — ask me to paste it when you need it. Then read SKILL.md for daily usage, and always read helpers/ because that's where the editing scripts live. After install, don't transcribe anything on your own — just tell me it's ready and wait for me to drop footage into a folder. The agent handles the clone, dependencies, skill registration, and prompts you once for your ElevenLabs API key grab one at elevenlabs.io/app/settings/api-keys https://elevenlabs.io/app/settings/api-keys . Then point your agent at a folder of raw takes: cd /path/to/your/videos claude or codex, hermes, etc. For always-on editing from your own VPS or Telegram, run the agent through Browser Use Box https://browser-use.com/bux . Watch the 15-second demo https://www.tiktok.com/@browser use/video/7639824093721758989 . And in the session: edit these into a launch video It inventories the sources, proposes a strategy, waits for your OK, then produces edit/final.mp4 next to your sources. All outputs live in <videos dir /edit/ — the skill directory stays clean. If you'd rather do it by hand: 1. Clone and symlink into your agent's skills directory git clone https://github.com/browser-use/video-use ~/Developer/video-use ln -sfn ~/Developer/video-use ~/.claude/skills/video-use Claude Code ln -sfn ~/Developer/video-use ~/.codex/skills/video-use Codex 2. Install deps cd ~/Developer/video-use uv sync or: pip install -e . brew install ffmpeg required brew install yt-dlp optional, for downloading online sources 3. Add your ElevenLabs API key cp .env.example .env $EDITOR .env ELEVENLABS API KEY=... The LLM never watches the video. It reads it — through two layers that together give it everything it needs to cut with word-boundary precision. Layer 1 — Audio transcript always loaded . One ElevenLabs Scribe call per source gives word-level timestamps, speaker diarization, and audio events laughter , applause , sigh . All takes pack into a single ~12KB takes packed.md — the LLM's primary reading view. C0103 duration: 43.0s, 8 phrases 002.52-005.36 S0 Ninety percent of what a web agent does is completely wasted. 006.08-006.74 S0 We fixed this. Layer 2 — Visual composite on demand . timeline view produces a filmstrip + waveform + word labels PNG for any time range. Called only at decision points — ambiguous pauses, retake comparisons, cut-point sanity checks. Naive approach: 30,000 frames × 1,500 tokens = 45M tokens of noise. Video Use:12KB text + a handful of PNGs. Same idea as browser-use giving an LLM a structured DOM instead of a screenshot — but for video. Transcribe ── Pack ── LLM Reasons ── EDL ── Render ── Self-Eval │ └─ issue? fix + re-render max 3 The self-eval loop runs timeline view on the rendered output at every cut boundary — catches visual jumps, audio pops, hidden subtitles. You see the preview only after it passes. Text + on-demand visuals. No frame-dumping. The transcript is the surface. Audio is primary, visuals follow. Cuts come from speech boundaries and silence gaps. Ask → confirm → execute → self-eval → persist. Never touch the cut without strategy approval. Zero assumptions about content type. Look, ask, then edit. 12 hard rules, artistic freedom elsewhere. Production-correctness is non-negotiable. Taste isn't. See SKILL.md /browser-use/video-use/blob/main/SKILL.md for the full production rules and editing craft.