video-clipper
Repurposes long-form video (podcasts, interviews, talks) into short-form vertical clips for Instagram Reels, TikTok, and YouTube Shorts. Handles transcription, moment selection, clip extraction, speaker-tracked reframing (16:9 to 9:16), and animated captions.
npx skills add gooseworks-ai/goose-skills --skill video-clipper --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 Clipper Takes a long-form video and produces ready-to-post short-form vertical clips with speaker-tracked framing and professional animated captions. Works with podcasts, interviews, talks, and any talking-head content. --- ## Requirements - **FFmpeg** installed and available in PATH (`brew install ffmpeg` on macOS, `apt install ffmpeg` on Linux) - **Python 3** with `openai-whisper` and `requests` packages (`pip install openai-whisper requests`). **Note:** `openai-whisper` installs PyTorch (~2GB download). This skill uses `openai-whisper` instead of the lighter `whisper-cpp` because it provides word-level timestamps needed for accurate viral moment scoring. - **yt-dlp** installed (for YouTube/URL downloads) — `brew install yt-dlp` on macOS, `pip install yt-dlp` on Linux - **API Keys** in `.env` file (project root or any parent directory): - `KLAP_API_KEY` — from [klap.app](https://klap.app) (reframing with speaker tracking) - `CAPTIONS_AI_API_KEY` — from [captions.ai](https://captions.ai) / [platform.mirage.app](https://platform.mirage.app) (animated captions) **Before starting:** Verify that FFmpeg, yt-dlp, and the Python packages are installed. If any are missing, instruc
- Requirements
- Cost Per Clip
- Input
- Pipeline
- Step 1: Get the Video
- Step 2: Transcribe with Whisper
- Step 3: Identify Best Moments (Viral Scoring)
- Step 4: Extract Raw Clips
- Step 5: Reframe with Klap
- Step 6: Add Animated Captions with Captions.ai
- Step 7: Generate Platform Captions
- Step 8: Output
- Workflow Summary
- Known Limitations
Verify it exists and get duration ffprobe -v quiet -print_format json -show_format "video.mp4" yt-dlp -f "bestvideo[height<=720]+bestaudio/best[height<=720]" --merge-output-format mp4 -o "<workdir>/source.mp4" "<URL>" curl -L -o "<workdir>/source.mp4" "<URL>" ffmpeg -y -ss <start> -to <end> -i source.mp4 -c copy clip<N>-raw.mp4
What does the video-clipper skill do?
Repurposes long-form video (podcasts, interviews, talks) into short-form vertical clips for Instagram Reels, TikTok, and YouTube Shorts. Handles transcription, moment selection, clip extraction, speaker-tracked reframing (16:9 to 9:16), and animated captions.
How do I install it?
Run `npx skills add gooseworks-ai/goose-skills --skill video-clipper --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 gooseworks-ai/goose-skills, a repository with 1,091 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.