Someone has developed a free video editing tool for Claude Code… it’s insane. Just drop your raw footage and assets into a folder. That’s it. It handles everything:

• Trimming clips
• Removing filler words
• Adding subtitles
• Applying color grading and filters
• Handling animations
• Rendering the final video

No timeline. No manual editing. No back-and-forth.

Honestly, this goes beyond tools like Remotion. It doesn’t just help you make videos… it does the editing for you.

The project is open source on GitHub. https://github.com/browser-use/video-use

browser-use/video-use

Source: https://github.com/browser-use/video-use

video-use

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.

What it does

• 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

Setup prompt

Paste into Claude Code, Codex, Hermes, Openclaw, or any agent with shell access:

text 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:

``bash
cd /path/to/your/videos
claude

or codex, hermes, etc.

``

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 /edit/ — the skill directory stays clean.

Manual install

If you’d rather do it by hand:

``bash

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=…

``

How it works

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.

Pipeline

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.

Design principles

1. Text + on-demand visuals. No frame-dumping. The transcript is the surface.
2. Audio is primary, visuals follow. Cuts come from speech boundaries and silence gaps.
3. Ask → confirm → execute → self-eval → persist. Never touch the cut without strategy approval.
4. Zero assumptions about content type. Look, ask, then edit.
5. 12 hard rules, artistic freedom elsewhere. Production-correctness is non-negotiable. Taste isn’t.

See SKILL.md for the full production rules and editing craft.