Can I analyze videos in languages other than English?

Yes, while it prefers English, it can list available subtitle languages and download specific translations using the --sub-lang flag.

Does this skill require watching the video?

No, it extracts the transcript and metadata using yt-dlp, allowing Claude to perform text-based analysis without you needing to watch the video.

What happens if a video has no transcript available?

The skill will notify you if transcripts are missing and can offer alternative approaches such as analyzing the video description and metadata.

Can it handle very long videos or live stream recordings?

Yes, for transcripts exceeding 8,000 tokens (roughly 45+ minutes), the skill uses an intelligent chunking process to summarize segments and synthesize overall themes.

Do I need to install any external software?

Yes, you must have yt-dlp installed via pip or Homebrew on your system for the skill to download transcripts and metadata.

YouTube Transcript Analyzer

Name: YouTube Transcript Analyzer
Author: Krosebrook

byKrosebrook

•

Aprendizaje y Documentación

Analyzes YouTube transcripts to extract technical insights and relate video content to your software projects.

Acerca de

The YouTube Transcript Analyzer streamlines the process of extracting knowledge from video content by downloading and processing transcripts using yt-dlp. It intelligently chunks long-form content to fit within AI context windows, provides timestamp-referenced summaries, and offers context-aware analysis to show exactly how a video's concepts apply to your current codebase or project requirements.

Características Principales

Context-aware comparison between video content and local codebases
Automated transcript extraction using yt-dlp integration
Intelligent chunking for long-form video content processing
Timestamp-referenced insights and actionable recommendations
Metadata extraction for full video context including title and duration
1 GitHub stars

Casos de Uso

Extracting technical implementation details from conference talks or tutorials
Comparing external architectural patterns with your current project structure
Rapidly researching technical concepts in video format without manual watching

Acerca de

Características Principales

Context-aware comparison between video content and local codebases
Automated transcript extraction using yt-dlp integration
Intelligent chunking for long-form video content processing
Timestamp-referenced insights and actionable recommendations
Metadata extraction for full video context including title and duration
1 GitHub stars

Casos de Uso

Extracting technical implementation details from conference talks or tutorials
Comparing external architectural patterns with your current project structure
Rapidly researching technical concepts in video format without manual watching