noteking-pro

name	noteking-pro
description	全网最强视频/录音处理工具。将视频、录音、会议转化为精美图文 PDF 讲义、结构化会议纪要、思维导图、学习闪卡等多种格式。支持说话人分离、降噪增强、中英混合、30+ 平台视频链接。涵盖会议/课堂/访谈/灵感/娱乐全场景，23 种输出模板，本地优先+云端可选。
version	2.0.0
metadata	{"openclaw":{"requires":{"env":"[Truncated]","bins":"[Truncated]"},"primaryEnv":"NOTEKING_LLM_API_KEY","emoji":"👑","homepage":"https://github.com/bcefghj/noteking","os":["macos","linux","windows"],"install":["[Truncated]"]}}

NoteKing Pro - 全网最强视频/录音处理工具

Use this skill when the user wants to:

• Convert a video or audio recording into structured notes
• Generate meeting minutes from a recording
• Transcribe audio/video with speaker identification
• Create study materials from lectures
• Process interviews, brainstorm sessions, or podcasts

Core Capabilities

1. Online Video Processing (30+ platforms)

Convert any online video URL into structured notes.

2. Local Recording Processing (NEW)

Process local audio/video files with advanced features:

• Speaker diarization: Identify who said what in multi-speaker recordings
• Noise reduction: Clean up noisy recordings (3 levels)
• Multi-file merge: Combine multiple recording segments
• Language detection: Auto-detect language including Chinese-English mix

3. 23 Output Templates

Template	Name	Best For
brief	简要总结	Quick overview
detailed	详细学习笔记	Systematic study
mindmap	思维导图	Visual knowledge structure
flashcard	闪卡	Spaced repetition
quiz	测验题	Self-testing
timeline	时间线笔记	Timestamped notes
exam	考试复习	Exam preparation
tutorial	教程步骤	Step-by-step extraction
news	新闻速览	News summary
podcast	播客摘要	Discussion summary
xhs_note	小红书笔记	Social media note
latex_pdf	LaTeX PDF	Professional lecture notes
custom	自定义	User-defined prompt
meeting_minutes	会议纪要	Meeting notes with action items
lecture_notes	课堂笔记	Knowledge hierarchy
interview	访谈记录	Q&A with insights
brainstorm	灵感记录	Idea capture
news_digest	新闻摘要	5W1H structured digest
exam_prep	考试复习	Flashcards + mock questions
cornell_notes	康奈尔笔记	Cornell note method
podcast_shownotes	播客笔记	Show notes with chapters
entertainment

Supported Platforms

• Bilibili (B站), YouTube, Douyin (抖音), Xiaohongshu (小红书)
• TikTok, Twitter/X, Instagram, Twitch, Vimeo
• 1800+ additional sites via yt-dlp
• Local files: MP4, MKV, AVI, MOV, MP3, WAV, FLAC, M4A, OGG, AAC

Dependencies

Required:

• ffmpeg - Audio/video processing
• python3 >= 3.11

Python packages (auto-installed):

• openai - LLM API client
• yt-dlp - Video downloading
• rich - Terminal UI

Optional (for best experience):

• funasr - Best Chinese ASR (WER 8.4%)
• faster-whisper - Local multilingual ASR
• pyannote.audio - Speaker diarization
• noisereduce - Noise reduction

Environment Variables

Variable	Required	Description
NOTEKING_LLM_API_KEY	Yes	API key for LLM (MiniMax/OpenAI/DeepSeek)
NOTEKING_LLM_BASE_URL	No	Custom API base URL
NOTEKING_LLM_MODEL	No	Model name (default: gpt-4o-mini)
HF_TOKEN	No	HuggingFace token for pyannote speaker diarization
NOTEKING_PROXY	No	Proxy URL for YouTube access from China
BILIBILI_SESSDATA	No	Bilibili login cookie

Usage

Process Online Video

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

Process Local Recording (NEW)

# Meeting recording with speaker diarization
python -m cli process meeting.mp4 -t meeting_minutes -c "产品周会" --speakers 4

# Lecture with noise reduction
python -m cli process lecture.mp3 -t lecture_notes --denoise 2

# Multiple files merged
python -m cli process part1.mp4 part2.mp4 -t meeting_minutes

# Interview with multiple output formats
python -m cli process interview.wav -t interview --format markdown,srt,json

Transcribe Only

python -m cli transcribe recording.mp4

Denoise Audio

python -m cli denoise noisy.wav --level 2

Merge Files

python -m cli merge segment1.mp4 segment2.mp4 -o merged.mp4

Scene Types

Scene	Template	Description
meeting	meeting_minutes	会议纪要: 参会人/议题/决议/行动项
lecture	lecture_notes	课堂笔记: 知识点/公式/习题
interview	interview	访谈: Q&A/观点/立场
brainstorm	brainstorm	灵感: 想法/思维导图/行动
news	news_digest	新闻: 5W1H/引用/背景
exam	exam_prep	考试: 闪卡/模拟题/要点
entertainment	entertainment	娱乐: 高光/金句/推荐

Workflow

For Online Videos:

1. Parse URL → Detect platform
2. Extract subtitles → CC → ASR → Visual fallback
3. Generate notes → Apply template via LLM
4. Save output → Markdown + SRT

For Local Recordings:

1. Preprocess → Validate, merge files, extract audio, denoise
2. Transcribe → Auto-detect language, FunASR(Chinese)/Whisper(multilingual)
3. Diarize → Identify speakers with pyannote-audio
4. Generate → LLM with scene context and speaker labels
5. Output → Multi-format (Markdown/PDF/SRT/VTT/JSON)

Notes for AI Agents

• For meetings: use process command with meeting_minutes template and specify --speakers
• For lectures: use lecture_notes template, optionally with --denoise
• For noisy recordings: increase --denoise level (1=light, 2=medium, 3=heavy)
• For long recordings split into parts: pass all files to process command
• Default to meeting_minutes for recordings unless user specifies otherwise
• For quick overview, use smart_summary template
• Check ffmpeg and python3 are installed before processing