youtube-clipper-skill

Automatically generate semantic chapters and output high-quality clips with bilingual subtitles and social media summaries.

An AI-powered tool for Claude Code to clip YouTube videos, generate semantic chapters, translate bilingual subtitles, and burn them into video files.

归藏

Product designer focused on AI, LLMs, and AI image and video design

VideoAutomationVerifiedOpen-source license: MIT

GitHub Stars2.1K

Suggested prompts

Clip this YouTube video: https://youtube.com/watch?v=VIDEO_ID

Analyze this video and create short clips with bilingual subtitles: https://youtube.com/watch?v=VIDEO_ID

Segment this video into semantic chapters and generate social media summaries: https://youtube.com/watch?v=VIDEO_ID

About this skill

YouTube Clipper Skill

YouTube Clipper is an AI-powered YouTube video clipper for Claude Code. It downloads videos, generates semantic chapters, clips segments, translates subtitles to bilingual format, and burns subtitles into videos.

Use Cases

Extract highlights from YouTube videos (e.g., tech interviews, courses, talks)
Generate bilingual subtitles (Chinese/English) for multi-language distribution
Create short clips ready for social media platforms (Xiaohongshu, Douyin, WeChat)
Automatically segment long videos by semantic content for quick navigation

Core Capabilities

AI Semantic Analysis — Generate fine-grained chapters (2–5 minutes each) by understanding video content, not just mechanical time splitting
Precise Clipping — Use FFmpeg to extract video segments with frame-accurate timing
Bilingual Subtitles — Batch translate subtitles to Chinese/English with 95% API call reduction and 10x faster translation
Subtitle Burning — Hardcode bilingual subtitles into videos with customizable styling
Content Summarization — Auto-generate social media content (Xiaohongshu, Douyin, WeChat)

How It Works

Environment Check — Verifies yt-dlp, FFmpeg, and Python dependencies
Video Download — Downloads video (up to 1080p) and English subtitles
AI Chapter Analysis — Claude analyzes subtitles to generate semantic chapters (2–5 min each)
User Selection — Choose which chapters to clip and processing options (translate subtitles, burn subtitles, generate summary)
Processing — Clips video, translates subtitles, burns subtitles (if requested)
Output — Organized files in ./youtube-clips/<timestamp>/

What You Need to Provide

A YouTube video URL
A command in Claude Code, e.g.: Clip this YouTube video: https://youtube.com/watch?v=VIDEO_ID
Optionally, select which chapters to clip and whether to generate bilingual subtitles, burn subtitles, or create a summary

What You Will Get

For each clipped chapter, the output directory contains:

./youtube-clips/20260122_143022/
└── Chapter_Title/
    ├── Chapter_Title_clip.mp4              # Original clip (no subtitles)
    ├── Chapter_Title_with_subtitles.mp4    # With burned-in subtitles
    ├── Chapter_Title_bilingual.srt         # Bilingual subtitle file
    └── Chapter_Title_summary.md            # Social media content

Configuration

Edit ~/.claude/skills/youtube-clipper/.env to customize:

# FFmpeg path (auto-detected if empty)
FFMPEG_PATH=

# Output directory (default: current working directory)
OUTPUT_DIR=./youtube-clips

# Video quality limit (720, 1080, 1440, 2160)
MAX_VIDEO_HEIGHT=1080

# Translation batch size (20-25 recommended)
TRANSLATION_BATCH_SIZE=20

# Target language for translation
TARGET_LANGUAGE=中文

# Target chapter duration in seconds (180-300 recommended)
TARGET_CHAPTER_DURATION=180

Selection Guide

Unlike mechanical time-based splitting, this skill uses AI semantic analysis to:

Understand content semantics and identify natural topic transitions
Generate meaningful chapter titles and summaries
Ensure complete coverage with no gaps

Usage Examples

Example: Extract highlights from a tech interview

Input:

Clip this video: https://youtube.com/watch?v=Ckt1cj0xjRM

AI-generated chapters:

1. [00:00 - 03:15] AGI as an exponential curve, not a point in time
2. [03:15 - 06:30] China's gap in AI development
3. [06:30 - 09:45] The impact of chip bans

Select chapters → get clipped videos with bilingual subtitles and social media content.

Requirements & Notes

System Dependencies

Dependency	Version	Purpose	Installation
Python	3.8+	Script execution	python.org
yt-dlp	Latest	YouTube download	`brew install yt-dlp` (macOS) / `sudo apt install yt-dlp` (Ubuntu) / `pip install yt-dlp`
FFmpeg with libass	Latest	Video processing & subtitle burning	`brew install ffmpeg-full` (macOS) / `sudo apt install ffmpeg libass-dev` (Ubuntu)

FFmpeg libass Support

macOS users: The standard ffmpeg package from Homebrew does NOT include libass support (required for subtitle burning). Install ffmpeg-full:
```
brew uninstall ffmpeg
brew install ffmpeg-full
```
Verify libass support: ffmpeg -filters 2>&1 | grep subtitles — should output subtitles V->V (...)

Troubleshooting

Slow video download: Set a proxy in .env: YT_DLP_PROXY=http://proxy-server:port or socks5://proxy-server:port
Subtitle translation fails: The skill auto-retries up to 3 times. If persistent, check network connectivity, Claude API status, or reduce TRANSLATION_BATCH_SIZE
Special characters in filenames: Automatically sanitized by removing \ / : * ? " < > |, replacing spaces with underscores, and limiting length to 100 characters