A specialized utility designed to extract, clean, and format readable text transcripts from any YouTube video URL while removing messy metadata.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install youtube-transcript-generator
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-transcript-generator 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 Transcript Generator?
The YouTube Transcript Generator is a high-performance utility within the Openclaw Skills ecosystem, designed to bridge the gap between video content and textual analysis. It leverages advanced extraction logic to fetch subtitles—prioritizing manual uploads over auto-generated captions—and processes them into a clean, paragraph-based format.
This tool is specifically engineered to handle the technical nuances of video subtitles, such as stripping away HTML tags, resolving duplicate lines from rolling captions, and providing optional timestamp markers. For developers and researchers, this skill transforms YouTube's vast video library into a structured text dataset ready for LLM consumption or archival research using Openclaw Skills.
YouTube Transcript Generator Use Cases
- Creating clean documentation or blog posts from video tutorials.
- Generating high-quality text input for AI agents to summarize long-form video content.
- Building searchable archives of podcast episodes or educational webinars.
- Extracting specific timestamps for video editing workflows or content repurposing.
- Translating international video content by extracting multi-language transcript files.
How YouTube Transcript Generator Works
- The user provides a YouTube URL to the script, which initiates a metadata check via yt-dlp.
- The skill attempts to locate English manual subtitles first, falling back to auto-generated English or other available languages.
- Raw subtitle data in VTT or SRT format is downloaded into a temporary buffer.
- A cleaning algorithm parses the raw data to remove HTML tags, formatting markers, and redundant lines.
- Depending on the flags provided, the text is either merged into flowing paragraphs or formatted with [HH:MM:SS] markers.
- The final transcript is saved to a local .txt file and printed to the standard output for immediate verification.
YouTube Transcript Generator Setup
To utilize this skill, ensure you have the necessary dependencies installed on your system. This skill relies on yt-dlp for the heavy lifting of media interaction.
# Install the dependency using Homebrew (macOS)
brew install yt-dlp
# Or install via Python PIP
pip install yt-dlp
Once installed, you can trigger the transcript generation through the Openclaw Skills interface:
bash scripts/get_transcript.sh "https://www.youtube.com/watch?v=VIDEO_ID"
YouTube Transcript Generator Data Schema & Taxonomy
The skill manages data by generating clean text files associated with the unique video identifier.
| File/Element | Description | Data Type |
|---|---|---|
| transcript_[VIDEO_ID].txt | The final processed transcript file. | Text File |
| Subtitle Track | Manual or Auto-generated captions fetched from YouTube. | VTT/SRT |
| Timestamp Markers | Optional [HH:MM:SS] headers for each dialogue line. | String |
YouTube Transcript Generator Advanced Features
- Intelligent language fallback: Automatically detects and cycles through available languages to ensure data capture.
- Format flexibility: Choose between clean paragraph mode or timestamped reference mode for deep-linking.
- Automated cleaning: Sophisticated stripping of rolling caption duplicates that often plague raw YouTube subtitle files.
- Command-line extensibility: Easily integrated into larger automation pipelines within the Openclaw Skills framework for batch processing.
SKILL.md
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