Does it download the entire video file?

No, it specifically uses the --skip-download flag to retrieve only the text-based transcript and metadata, making the process fast and bandwidth-efficient.

Do I need to install anything for this skill to work?

Yes, you must have yt-dlp installed on your system (via pip or Homebrew) to handle the transcript extraction and metadata retrieval.

Can it analyze videos that don't have manual captions?

Yes, the skill is configured to automatically fall back to auto-generated subtitles if manual captions are not available.

What kind of output can I expect?

You will receive a structured report containing a video overview, key technical insights with timestamps, a relevance assessment for your specific project, and actionable recommendations.

How does it handle very long videos?

For videos over 45 minutes, the skill uses intelligent chunking to split the transcript into logical segments, ensuring comprehensive analysis within AI token limits.

YouTube Transcript Analyzer

Name: YouTube Transcript Analyzer
Author: Light-Brands

byLight-Brands

学习与文档

Extracts and analyzes YouTube transcripts to provide actionable insights and technical comparisons for development projects.

关于

This Claude Code Skill enables seamless integration of YouTube's vast educational content into your development workflow by using yt-dlp to extract and process video transcripts. It intelligently handles long-form content through automated chunking, summarizes complex technical concepts, and directly relates video content to your current codebase or project goals. Whether you are researching new architectures from conference talks or learning from tutorials, this skill provides structured analysis including key insights with timestamps and specific implementation recommendations without requiring you to watch the entire video.

主要功能

Reliable transcript extraction using yt-dlp with auto-caption support
0 GitHub stars
Intelligent chunking for long-form content exceeding 45 minutes
Direct comparison between video concepts and your current project architecture
Automated metadata collection including titles, authors, and duration
Structured analysis reports with timestamped insights and actionable code patterns

使用场景

Extracting actionable code patterns from video tutorials without manual note-taking
Comparing external video-based solutions with an existing codebase for potential improvements
Researching technical concepts or architectural patterns from developer conference talks

关于

主要功能

Reliable transcript extraction using yt-dlp with auto-caption support
0 GitHub stars
Intelligent chunking for long-form content exceeding 45 minutes
Direct comparison between video concepts and your current project architecture
Automated metadata collection including titles, authors, and duration
Structured analysis reports with timestamped insights and actionable code patterns

使用场景

Extracting actionable code patterns from video tutorials without manual note-taking
Comparing external video-based solutions with an existing codebase for potential improvements
Researching technical concepts or architectural patterns from developer conference talks