# Youtube Summarizer

> Summarize YouTube videos by extracting and analyzing auto-generated subtitles. Use when the user provides a YouTube URL and asks to summarize, explain, or analyze a video's content. Triggers on patterns like "this video summarize", "summarize this YouTube", "what does this video say", or any request involving a youtube.com or youtu.be URL combined with summarization/analysis intent. Supports both Japanese and English videos.

- Skill: `tumf/youtube-summarizer` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add tumf/youtube-summarizer`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tumf/youtube-summarizer/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: tumf (https://skillmd.com/u/tumf)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tumf/youtube-summarizer

---


# YouTube Summarizer

## Prerequisites

- `yt-dlp` must be installed (`pip install yt-dlp`)

## Workflow

### 1. Extract transcript

Run the bundled script to fetch and clean the transcript:

```bash
python scripts/fetch_transcript.py "<YOUTUBE_URL>" --lang <LANG> 2>/tmp/yt_meta.json > /tmp/yt_transcript.txt
```

- `--lang ja` (default) for Japanese videos, `--lang en` for English.
- The script auto-detects original-language captions first, then falls back.
- **stdout**: cleaned plain-text transcript.
- **stderr**: JSON metadata `{"video_id", "title", "language"}`.
- If no subtitles exist, the script exits with code 1.

### 2. Read transcript and metadata

Read `/tmp/yt_meta.json` for the title and language, then read `/tmp/yt_transcript.txt` for the full text.

### 3. Summarize

Produce a structured summary in the user's language. Use the following structure as a guide (adapt headings to fit the content):

- **Title / topic** (one line)
- **Core concept** (1-2 paragraphs explaining the main idea)
- **Key sections** (3-5 sections with subheadings, covering the major points)
- **Conclusion / takeaway**

Keep the summary concise but comprehensive. Preserve technical terms and proper nouns from the original.

### 4. Clean up

Remove temporary files after summarization:

```bash
rm -f /tmp/yt_transcript.txt /tmp/yt_meta.json
```