noteking

name

noteking

description

Convert any video or blog into structured learning notes. Supports Bilibili, YouTube, Douyin, Xiaohongshu, TikTok, and 1800+ platforms via yt-dlp. Offers 13 output templates including detailed notes, mind maps, flashcards, quizzes, exam notes, timeline, LaTeX PDF, and more. Use when the user provides a video URL and wants summarized content, study notes, or any form of structured output from video/audio content.

NoteKing - Video/Blog to Learning Notes

Use this skill when the user wants to convert a video, podcast, or blog into structured notes.

Supported Platforms

• Bilibili (B站): single videos, multi-part (分P), series, collections, favorites
• YouTube: single videos, playlists, channels (proxy support for China)
• Douyin (抖音), Xiaohongshu (小红书), Kuaishou (快手)
• TikTok, Twitter/X, Instagram, Twitch, Vimeo, Facebook
• 1800+ additional sites via yt-dlp
• Local files: MP4, MP3, WAV, FLAC

Available Templates

Template	Name	Best For
brief	简要总结	Quick 3-5 sentence overview
detailed	详细学习笔记	Systematic study with chapters & key points
mindmap	思维导图	Visual knowledge structure (Markmap)
flashcard	闪卡 (Anki)	Spaced repetition study
quiz	测验题	Self-testing with MCQ + short answer
timeline	时间线笔记	Timestamped notes with video links
exam	考试复习笔记	Exam preparation with formulas & key concepts
tutorial	教程步骤	Step-by-step how-to extraction
news	新闻速览	News-style quick summary
podcast	播客/访谈摘要	Interview & discussion summary
xhs_note	小红书笔记	Xiaohongshu-style social media note
latex_pdf	LaTeX PDF 讲义	Professional academic lecture notes
custom	自定义	User-defined prompt template

Dependencies

The following tools must be available in the environment:

• yt-dlp - Video downloading (install: pip install yt-dlp)
• ffmpeg - Audio/video processing (install: brew install ffmpeg or apt install ffmpeg)

Python packages (auto-installed):

• openai - LLM API client
• youtube-transcript-api - YouTube subtitle extraction
• httpx - HTTP client
• pysrt - SRT subtitle parsing

Optional:

• faster-whisper - Local speech recognition (install: pip install faster-whisper)

Environment Variables

Variable	Required	Description
NOTEKING_LLM_API_KEY	Yes	API key for LLM (OpenAI/DeepSeek/etc.)
NOTEKING_LLM_BASE_URL	No	Custom API base URL
NOTEKING_LLM_MODEL	No	Model name (default: gpt-4o-mini)
NOTEKING_PROXY	No	Proxy URL for YouTube access from China
BILIBILI_SESSDATA	No	Bilibili login cookie for HD & member content

Usage

Basic Usage

When the user provides a video URL, run the NoteKing core:

cd /path/to/noteking
python -m cli run "<VIDEO_URL>" -t <TEMPLATE>

Examples

# Detailed notes from a Bilibili video
python -m cli run "https://www.bilibili.com/video/BV1xx411c79H" -t detailed

# Mind map from a YouTube video
python -m cli run "https://youtu.be/dQw4w9WgXcQ" -t mindmap

# Flashcards from a local lecture
python -m cli run "./lecture.mp4" -t flashcard

# Exam notes with custom API
python -m cli run "https://www.bilibili.com/video/BV1xx" -t exam --api-key sk-xxx --model deepseek-chat --base-url https://api.deepseek.com

Batch Processing

For playlists or video collections (e.g., a 50-lecture math course):

python -m cli run "https://www.bilibili.com/video/BV1xx?p=1" -t detailed
python -m cli run "https://youtube.com/playlist?list=PLxxx" -t exam

Available CLI Commands

python -m cli run <URL> -t <TEMPLATE>    # Process video
python -m cli transcript <URL>            # Extract transcript only
python -m cli templates                   # List all templates
python -m cli setup                       # Interactive setup
python -m cli cache-clear                 # Clear cache

Workflow

1. Parse URL → Detect platform, check if playlist/collection
2. Extract subtitles → Three-level fallback: CC subtitles → ASR → Visual mode
3. Get metadata → Title, chapters, duration, thumbnail
4. Generate notes → Apply selected template via LLM
5. Save output → Markdown file + SRT subtitles + transcript

Configuration

Config file location: ~/.noteking/config.json

Run python -m cli setup for interactive configuration, or edit the JSON directly.

Notes for AI Agents

• When the user says "summarize this video" or "help me take notes on this video", use this skill
• Default to detailed template unless the user specifies otherwise
• For exam preparation, recommend exam + flashcard templates
• For quick browsing, recommend brief template
• For courses with multiple videos, use batch processing
• Always check if yt-dlp and ffmpeg are installed first