video-clip-extractor
Processes videos to identify engaging moments, generate transcripts, and create highlight clips with artistic titles and custom cover images. Use when user needs to: extract highlights from long videos or livestreams, clip or cut best moments from videos, cut video highlights, process Bilibili/YouTube URLs or local video files, generate transcripts via Whisper, analyze content for engaging moments, create short-form clips with styled titles and covers, adjust cover text position and colors, find and export memorable scenes from recordings, burn subtitles into clips (with optional translation),
npx skills add linzzzzzz/openclip --skill video-clip-extractor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Video Clip Extractor Skill Run the video orchestrator to process videos and extract engaging highlights. ## When Triggered 1. **Get the source** — if the user didn't provide a video URL or file path, ask for it. 2. **Clarify intent** (optional) — if the user wants clips focused on a specific topic, capture it for `--user-intent`. If unclear, ask: "Any specific topic or moments to focus on? (e.g. 'funny moments', 'key arguments')" 3. **Check environment** — does `video_orchestrator.py` exist in the current directory? If yes, run directly. Otherwise use the global install at `~/.local/share/openclip`. 4. **Verify prerequisites** — check ffmpeg is installed and at least one API key is set. Warn if missing before running. 5. **Run the command** and stream output to user. 6. **Report results** — after completion, list the generated clips with timestamps and titles. ## Setup (first use only) Before running, determine the execution context: 1. **Inside openclip repo** — if `video_orchestrator.py` exists in the current directory, skip setup and run directly. 2. **Global install** — if `~/.local/share/openclip` does not exist, run these steps: **Prerequisites:** `git` and `uv` must be ins
- When Triggered
- Setup (first use only)
- Execution
- Preflight Checklist
- CLI Reference
- Required
- Optional
- Flags
- Custom Filename Template (-f)
- Environment Variables
- Workflow
- Output Example
- Output Structure
- Option Selection Guide
git clone https://github.com/linzzzzzz/openclip.git ~/.local/share/openclip cd ~/.local/share/openclip && uv sync git -C ~/.local/share/openclip pull && cd ~/.local/share/openclip && uv sync uv run python video_orchestrator.py [options] <source> cd ~/.local/share/openclip && uv run python video_orchestrator.py -o "$OLDPWD/processed_videos" [options] <source>
What does the video-clip-extractor skill do?
Processes videos to identify engaging moments, generate transcripts, and create highlight clips with artistic titles and custom cover images. Use when user needs to: extract highlights from long videos or livestreams, clip or cut best moments from videos, cut video highlights, process Bilibili/YouTube URLs or local video files, generate transcripts via Whisper, analyze content for engaging moments, create short-form clips with styled titles and covers, adjust cover text position and colors, find and export memorable scenes from recordings, burn subtitles into clips (with optional translation),
How do I install it?
Run `npx skills add linzzzzzz/openclip --skill video-clip-extractor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From linzzzzzz/openclip, a repository with 546 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.