ffmpeg-analyse-video-skill

AI agent skill that analyses video content by extracting frames with ffmpeg and using vision to generate timestamped step-by-step summaries.

Works with screen recordings, tutorials, presentations, footage, and animations.

Install

npx skills add fabriqaai/ffmpeg-analyse-video-skill

Requirements

• ffmpeg and ffprobe installed on your system
  • macOS: brew install ffmpeg
  • Ubuntu/Debian: sudo apt install ffmpeg
  • Windows: choco install ffmpeg or winget install ffmpeg

Usage

Provide a video file path and ask your agent to analyse it:

Analyse this video: /path/to/recording.mp4

What happens in this video? ~/Desktop/demo.mov

Summarise this recording: ./tutorial.mp4

Advanced

Analyse 2:00 to 5:00 of meeting.mp4

Analyse this video in high detail: demo.mp4

Focus on the code shown in this video: screencast.mp4

How It Works

Main Agent                          Sub-Agents (disposable context)
──────────                          ──────────────────────────────
1. ffprobe metadata        ───►
2. ffmpeg frame extraction ───►
3. Split frames into batches ──►   4. Read images (vision)
                                      Write text descriptions
                                      to batch_N_analysis.md
5. Read text files only    ◄───    (context discarded)
6. Synthesise final output

Frame images are only ever read inside disposable sub-agent contexts. The main agent receives lightweight text-only analysis files — no images enter the main conversation. This cuts context usage by ~90% compared to reading frames directly.

Frame Extraction Strategies

Video Duration	Strategy	Expected Frames
0-60s	Interval (1 frame/2s)	1-30
1-10min	Scene detection	15-60
10-30min	Keyframe extraction	30-80
30min+	Thumbnail filter	Capped at 60

Output Format

The skill produces a structured markdown report:

• Metadata — duration, resolution, fps, content type, frames analysed
• Timeline — chronological segments with descriptions
• Key Moments — 3-7 most significant timestamps
• Summary — 2-5 sentence narrative

License

MIT