An efficient tool for extracting YouTube transcripts and metadata to generate instant AI-powered video summaries.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install yt-summarize
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 yt-summarize 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 Video Summarizer?
The youtube-summarize skill is a specialized tool designed to bridge the gap between video content and text-based analysis. By leveraging the power of Openclaw Skills, developers and researchers can programmatically pull captions, metadata, and chapters from any YouTube URL. This skill is essential for anyone looking to bypass hours of video footage to find specific information or generate concise summaries using an AI agent.
This utility eliminates the need for manual transcription by interfacing directly with video data streams. Whether you are dealing with auto-generated captions or professional manual subtitles, this skill provides a clean, text-only output that is perfectly formatted for further processing by large language models.
YouTube Video Summarizer Use Cases
- Extracting lecture notes or tutorial steps from educational video content.
- Generating blog posts or social media snippets from long-form podcasts.
- Researching video trends by analyzing titles, descriptions, and view counts.
- Performing sentiment analysis or keyword extraction on video transcripts in bulk.
- Creating searchable text archives of video libraries for internal knowledge bases.
How YouTube Video Summarizer Works
- The skill identifies the target YouTube URL and checks for available manual or auto-generated subtitles.
- It uses the yt-dlp library to fetch the subtitle files in VTT or JSON formats without downloading the actual video file.
- A cleaning process removes VTT headers, timestamps, and formatting tags to produce a clean text file.
- Metadata like title, channel name, duration, and chapters are extracted to provide context for the transcript.
- The final clean text is passed to an LLM or saved as a text file for high-quality summarization within the Openclaw Skills framework.
YouTube Video Summarizer Setup
To get started with this skill, you need to install the yt-dlp dependency. Run the following command in your terminal:
pip install yt-dlp
Once installed, the Openclaw Skills environment will be able to invoke the extraction scripts to process any public YouTube URL.
YouTube Video Summarizer Data Schema & Taxonomy
The skill organizes extracted data into structured text and JSON formats for easy consumption. Below is the typical data output structure:
| File Type | Description | Content |
|---|---|---|
| transcript.txt | Plain text output | Cleaned video captions without timestamps or metadata tags. |
| metadata.json | Structured data | Comprehensive video info including Title, Channel, and View count. |
| chapters.txt | Timed segments | List of video chapters with their respective start times for segmented analysis. |
YouTube Video Summarizer Advanced Features
- Multi-language support allowing simultaneous extraction of subtitles in English, Russian, Spanish, and more.
- Advanced regex-based cleaning to remove VTT artifacts and duplicate lines from auto-generated captions.
- Extraction of detailed video chapters to create segmented, timestamped summaries.
- Capability to dump raw JSON metadata for deep data analysis and custom reporting.
- Support for listing all available subtitle tracks before initiating a download.
SKILL.md
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