Can I use this for videos in languages other than Korean or English?

Yes, it follows a subtitle priority (Manual Korean > Manual English > Auto Korean > Auto English) but can process any transcript available via yt-dlp.

How does YouTube Digest handle technical terms?

It uses web search to cross-reference video titles and speaker names, ensuring automatic transcripts are corrected for accurate technical terminology and proper nouns.

Where are the summaries and quiz results stored?

All outputs are saved as Markdown files in the research/readings/youtube/ directory with standardized naming conventions for easy retrieval.

What kind of quizzes does it generate?

It generates 9 questions across three difficulty levels (Basic, Intermediate, Advanced) to test both core concepts and specific applied details.

YouTube Digest

Name: YouTube Digest
Author: team-attention

byteam-attention

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313

Aprendizaje y Documentación

Summarizes YouTube videos, translates transcripts into Korean, and generates interactive quizzes for deep learning.

Acerca de

YouTube Digest is a specialized Claude Code skill designed to transform video content into structured knowledge. It automates the extraction of metadata and transcripts, utilizes web searches to correct technical terminology and proper nouns, and generates comprehensive Markdown documentation featuring summaries, insights, and full Korean translations. To ensure knowledge retention, it includes a multi-level 9-question quiz system and offers optional deep research capabilities for extended topical investigation, making it ideal for researchers and students.

Características Principales

Automated metadata and transcript extraction using yt-dlp
Seamless integration with Deep Research for follow-up investigations
Interactive 9-question assessment across three difficulty levels
Context-aware transcript correction via web search for technical terms
Comprehensive Markdown generation with summaries and Korean translations
313 GitHub stars

Casos de Uso

Creating bilingual documentation for foreign language educational content
Summarizing long technical tutorials or conference talks for quick review
Self-testing knowledge retention after watching complex video lectures

Acerca de

Características Principales

Automated metadata and transcript extraction using yt-dlp
Seamless integration with Deep Research for follow-up investigations
Interactive 9-question assessment across three difficulty levels
Context-aware transcript correction via web search for technical terms
Comprehensive Markdown generation with summaries and Korean translations
313 GitHub stars

Casos de Uso

Creating bilingual documentation for foreign language educational content
Summarizing long technical tutorials or conference talks for quick review
Self-testing knowledge retention after watching complex video lectures