Video Frames
- 66 installs
- 6 repo stars
- Updated March 13, 2026
- alphaonedev/openclaw-graph
video-frames is a Claude Code skill entry for extracting and analyzing video frames with ffmpeg, covering scene detection, frame selection, and batch processing.
About
This is a stub skill entry for video frame extraction and analysis using ffmpeg, including scene detection, frame selection, and batch processing. The entry is registered in the OpenClaw skill graph for discovery only and must be installed with clawhub install video-frames before use. It provides a description of when a task needs video frame capabilities but no implementation detail.
- Video frame extraction and analysis via ffmpeg
- Scene detection, frame selection, and batch processing
Video Frames by the numbers
- 66 all-time installs (skills.sh)
- Ranked #854 of 1,335 Generative Media skills by installs in the Skillselion catalog
- Data as of Jul 28, 2026 (Skillselion catalog sync)
video-frames capabilities & compatibility
- Use cases
- video generation
- Pricing
- Free
What video-frames says it does
Video frame extraction and analysis: ffmpeg integration, scene detection, frame selection, batch processing
This skill is registered in the Neo4j skill graph for discovery purposes only.
npx skills add https://github.com/alphaonedev/openclaw-graph --skill video-framesAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 66 |
|---|---|
| repo stars | ★ 6 |
| Last updated | March 13, 2026 |
| Repository | alphaonedev/openclaw-graph ↗ |
What it does
Extract and analyze video frames with ffmpeg, including scene detection and batch processing.
When should I use this skill?
A task requires extracting or analyzing video frames
Files
Video Frames
Purpose
Video frame extraction and analysis: ffmpeg integration, scene detection, frame selection, batch processing
Install When Needed
clawhub install video-framesNote
This skill is registered in the Neo4j skill graph for discovery purposes only. It is NOT installed via the traditional ClaWHub methodology. When a task matches this skill, the agent will inform you to install it if needed.
When to Use
- When the task requires video frames capabilities
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