What dependencies are required for this skill to work?

This skill primarily relies on yt-dlp for downloading and Python 3 for processing. For audio transcription, it requires OpenAI Whisper and ffmpeg.

Can I use this for non-English videos?

Yes, while the scripts default to English, the underlying yt-dlp commands can be configured to fetch subtitles in any language supported by the original video.

Does it remove the timestamps from the transcripts?

Yes, the included vtt-to-text.py script removes VTT headers, timestamps, and HTML tags to provide a clean, readable text file.

How does this skill handle videos without any subtitles?

If no manual or auto-generated subtitles are available, the skill offers a fallback script that downloads the video's audio and uses OpenAI's Whisper model to transcribe it locally.

YouTube Transcript Downloader

Name: YouTube Transcript Downloader
Author: bacchus-labs

bybacchus-labs

•

Web Scraping & Data Collection

Extracts, downloads, and cleans YouTube video transcripts and captions for easy reading and analysis.

About

The YouTube Transcript Downloader skill empowers Claude to retrieve text content from any YouTube video using a sophisticated multi-stage approach. It prioritizes high-quality manual subtitles, automatically falls back to auto-generated captions, and includes a last-resort Whisper transcription engine for videos with no existing subtitles. Beyond simple downloading, the skill features specialized processing to convert VTT files into clean, deduplicated plain text, making it an essential tool for summarizing videos, creating documentation, or analyzing video content directly within your terminal.

Key Features

Local audio-to-text transcription using OpenAI Whisper for videos without subs
Support for both manual and auto-generated YouTube captions
VTT to plain text conversion with automatic deduplication
3 GitHub stars
Automated subtitle downloading with intelligent fallback logic
Integrated dependency management for yt-dlp and Whisper installation

Use Cases

Analyzing video content for SEO and accessibility improvements
Extracting interview transcripts for research and content repurposed
Generating text summaries and documentation from educational video tutorials

About

Key Features

Local audio-to-text transcription using OpenAI Whisper for videos without subs
Support for both manual and auto-generated YouTube captions
VTT to plain text conversion with automatic deduplication
3 GitHub stars
Automated subtitle downloading with intelligent fallback logic
Integrated dependency management for yt-dlp and Whisper installation

Use Cases

Analyzing video content for SEO and accessibility improvements
Extracting interview transcripts for research and content repurposed
Generating text summaries and documentation from educational video tutorials