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 transcript extraction and frame-by-frame visual analysis. Synchronizes spoken content with extracted video frames by timestamp, enabling step-by-step guides where on-screen UI elements, code, and diagrams are captured alongside what is said.
Unlike transcript-only YouTube tools, it captures visual content, so information shown on screen but not spoken, such as specific button names, menu paths, or code, is not lost.
When to use it
- Building step-by-step guides from software tutorial videos
- Extracting code shown on screen but not read aloud
- Documenting exact UI click paths from product demo videos
- Summarizing long explainer videos with timestamped visual anchors
- Capturing tool usage and hand positions from physical howto 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=abc123
- 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 keyframes at adaptive intervals using ffmpeg
- 4Synchronizes each frame with the corresponding transcript segment by timestamp
- 5Reads each frame image alongside transcript text to generate a structured step-by-step guide
A markdown step-by-step guide with each action timestamped and annotated with visual descriptions of what appears on screen at that moment
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.