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.
Cloud-hosted video-use is coming. Join the waitlist at video-use.com.
## 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, Remotion, Manim, 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:
 [code] 
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).
Then point your agent at a folder of raw takes:
 [code] 
For always-on editing from your own VPS or Telegram, run the agent through Browser Use Box. Watch the 15-second demo.
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:
 [code] 
## 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.
 [code] 
**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
 [code] 
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