Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Analyzes YouTube videos through both audio and visual channels by extracting timestamped transcripts and key frames from the video. Pairs spoken content with on-screen visuals, so UI actions, code, and diagrams shown but not described in speech are captured accurately.
Standard YouTube transcript tools miss anything shown on screen but not spoken; this skill matches frames to transcript timestamps to close that gap.
When to use it
- Building step-by-step guides from software tutorial videos
- Extracting code shown on screen during live coding demos
- Summarizing long explainer videos with visual anchors
- Following UI navigation in product walkthrough videos
- Capturing diagram details from architecture or design videos
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: 'Create a step-by-step guide from this YouTube tutorial: https://youtube.com/watch?v=...'
- 1Fetches video metadata (title, duration, ID) using yt-dlp
- 2Extracts timestamped transcript via yt-dlp JSON dump and curl
- 3Downloads video at 720p and extracts frames at adaptive intervals using ffmpeg
- 4Synchronizes each frame to its corresponding transcript segment by timestamp
- 5Reads each frame for on-screen text, UI elements, and code, then combines with audio to generate a structured guide
Timestamped step-by-step guide with descriptions combining spoken instructions and visible UI details, including button names, menu paths, and code shown on screen
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.