A local, cost-free tool to extract and export transcripts from entire YouTube channels or playlists into structured data formats.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install youtube-full-channel-transcripts
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-full-channel-transcripts 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 Full Channel Transcripts?
The YouTube Full Channel Transcripts skill is a robust Openclaw Skills extension designed for developers and researchers who need to build datasets from video content. Unlike expensive cloud-based scrapers, this skill operates entirely on your local machine using reliable open-source utilities. It automates the discovery of every video on a channel and systematically retrieves the text-based subtitles, providing a high-fidelity textual representation of video content without the need for manual transcription.
By leveraging this skill within the Openclaw Skills ecosystem, users can bypass the complexities of the YouTube Data API and avoid subscription fees associated with third-party actors. It is the ideal solution for training local LLMs, performing sentiment analysis on specific creators, or archiving educational content for offline search and retrieval.
YouTube Full Channel Transcripts Use Cases
- Compiling massive datasets of creator content for LLM fine-tuning or RAG applications.
- Exporting full channel subtitles to perform keyword research and content gap analysis.
- Generating structured archives of video transcripts for legal or compliance documentation.
- Building searchable local databases of educational or technical tutorials from specific playlists.
How YouTube Full Channel Transcripts Works
- Discovery Phase: The skill uses yt-dlp with flat-playlist flags to scrape the metadata and URLs of all videos within the provided channel or playlist link.
- Transcript Retrieval: It iterates through the discovered video list, specifically targeting subtitle files (SRT/VTT) while skipping the heavy video binary downloads to save bandwidth.
- Text Parsing: The tool processes the raw subtitle formats, stripping timestamps and formatting codes to produce clean, readable plain text.
- Data Aggregation: All individual video transcripts are combined with their respective metadata (ID, title, date, duration) into a single unified file.
- Export: The final dataset is saved to your specified workspace in either JSON or CSV format for immediate use in other applications.
YouTube Full Channel Transcripts Setup
To use this Openclaw Skills contribution, ensure you have the necessary system dependencies installed.
# Install system dependencies
brew install yt-dlp jq
# Basic usage command
youtube_full_channel_transcripts channel_url="https://www.youtube.com/@ChannelHandle" output_format="json"
YouTube Full Channel Transcripts Data Schema & Taxonomy
The skill generates a structured output containing the following fields for every video processed:
| Field | Type | Description |
|---|---|---|
video_id |
String | The unique YouTube identifier for the video |
title |
String | The full title of the video |
url |
String | Direct link to the source video |
upload_date |
String | Date of publication in YYYYMMDD format |
duration |
Integer | Length of the video in seconds |
transcript |
String | The full extracted text of the subtitles |
is_auto_generated |
Boolean | Indicates if the transcript was AI-generated by YouTube |
YouTube Full Channel Transcripts Advanced Features
- Auto-Generated Support: Option to toggle the inclusion of YouTube's automatic captions when manual transcripts are unavailable.
- Multi-Language Filtering: Target specific language codes (e.g., en, es, fr) to ensure dataset consistency.
- Rate Limit Protection: Built-in retry logic with backoff and configurable sleep intervals to prevent IP flagging.
- Partial Processing: Use the
max_videosparameter to sample large channels or test workflows without processing thousands of videos.
SKILL.md
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