Video Content Watcher#

Extract audio → transcribe → analyze → generate structured Markdown report.

Quick Start#

bash

cd /home/ykl/.openclaw/workspace-code-dev/video-reader
export MINIMAX_API_KEY="your-key"
export WHISPER_MODE="local"   # or "api"
python3 << 'EOF'
import sys; sys.path.insert(0, 'src')
from video_reader_mcp import VideoReaderMCP
mcp = VideoReaderMCP()
result = mcp.process_url('VIDEO_URL')
print(result['report'])
EOF

Or use the CLI script:

bash

python3 /home/ykl/.openclaw/workspace/skills/video-content-watcher/scripts/video_reader.py "VIDEO_URL"

Workflow#

1. Audio extraction: Uses yt-dlp for online videos / ffmpeg for local files
2. Transcription: Whisper (local openai-whisper or API mode)
3. Analysis: MiniMax LLM analyzes transcript → structured report

Configuration (env vars)#

VariableRequiredDefaultDescriptionMINIMAX_API_KEYYes—MiniMax API keyWHISPER_MODENoapi``api or local``WHISPER_API_KEYIf mode=api—OpenAI API key for WhisperLLM_BASE_URLNohttps://api.minimaxi.com/v1MiniMax endpointLLM_MODELNoMiniMax-M2.7Model name

Supported Sources#

• YouTube: https://www.youtube.com/watch?v=xxx
• Bilibili: https://www.bilibili.com/video/BVxxx
• Local files: /path/to/video.mp4

Output#

Returns a Markdown report with:

• Basic info (source, transcript length)
• Core content summary
• Key takeaways
• Main viewpoints
• Pros / cons
• Target audience

Scripts#

• scripts/video_reader.py — CLI entry point
• scripts/analyze_text.py — Analyze raw text directly (skip video processing)