中文文档 | English
🎬 One-stop video content extraction and copywriting analysis tool. Download videos, smart subtitle extraction (embedded/burned/audio), and analyze scripts using three AI frameworks.
| Stage | Function | Description |
|---|---|---|
| 1️⃣ | Video Download | Download from Bilibili/YouTube/Douyin (yt-dlp + custom downloader) |
| 2️⃣ | Smart Subtitle Extraction | Three-tier priority: Embedded → OCR (RapidOCR) → ASR (FunASR/Whisper) |
| 3️⃣ | Smart Correction | Context-based auto-correction of transcription errors |
| 4️⃣ | Three-Dimensional Analysis | TextContent + Viral + Brainstorming |
# 1. yt-dlp (video downloader)
pip install yt-dlp
# 2. FFmpeg (must be installed and in PATH)
ffmpeg -version
# 3. Python dependencies
pip install pysrt python-dotenv
# 4. FunASR (Recommended for Chinese, lightweight & accurate)
pip install funasr modelscope
# 5. RapidOCR (ONNX lightweight, for burned subtitle detection)
pip install rapidocr-onnxruntime
# 6. Whisper (Alternative for English/multilingual)
pip install openai-whisper
# 7. requests (for Douyin download)
pip install requestsThis is a Claude Skill designed for AI agents. Install it in your .agent/skills/ directory:
git clone https://github.com/ALBEDO-TABAI/video-copy-analyzer.git .agent/skills/video-copy-analyzerThen use it with Claude:
"Analyze this video: https://www.bilibili.com/video/BV1xxxxx"
The skill automatically selects the best extraction method:
Video Input
↓
[1️⃣ Embedded Subtitle] ──→ Detected ──→ Direct Extract (Highest Accuracy)
↓ Not detected
[2️⃣ Burned Subtitle OCR] ──→ RapidOCR Frame Sampling ──→ Detected ──→ Full Video OCR
↓ Not detected
[3️⃣ Audio Transcription] ──→ FunASR (Chinese optimized) / Whisper (Multilingual)
↓
Output SRT Subtitles
| Tier | Method | Use Case | Accuracy | Speed |
|---|---|---|---|---|
| L1 | Embedded Extract | Video has subtitle stream | ⭐⭐⭐⭐⭐ | ⚡ Fastest |
| L2 | RapidOCR | Subtitles burned into video | ⭐⭐⭐⭐ | 🚀 Fast |
| L3 | FunASR Nano | Chinese audio transcription | ⭐⭐⭐⭐ | � Medium |
| L3 | Whisper | English/multilingual audio | ⭐⭐⭐ | 🐢 Medium |
-
RapidOCR (ONNX): Lightweight OCR for burned subtitle detection
- 🚀 Lightweight: ONNX Runtime, no GPU required
- 🎯 Cross-platform: Windows/Linux/Mac
- 📦 Easy deploy: Single pip install
- ✨ High accuracy: Based on PaddleOCR
-
FunASR Nano: Alibaba open-source Chinese ASR model
- 🚀 Lightweight: ~100MB vs Whisper Large ~1.5GB
- 🎯 Chinese optimized: Better than Whisper for Chinese
- ⏱️ Timestamp: Word-level timestamps
- 💨 Fast: Runs well on CPU
- Narrative structure breakdown
- Rhetorical device identification
- Keyword extraction
- Viral-5D Diagnosis: Hook / Emotion / Peaks / CTA / Social Currency
- Style positioning
- Optimization suggestions
- Core value decomposition
- 2-3 creative direction exploration
- Incremental verification points
video-copy-analyzer/
├── SKILL.md # Core skill instructions
├── scripts/
│ ├── download_douyin.py # Douyin video downloader (watermark-free)
│ ├── extract_subtitle_funasr.py # Smart subtitle extraction (FunASR + RapidOCR)
│ ├── extract_subtitle.py # Whisper-based extraction
│ ├── transcribe_audio.py # Audio transcription script
│ └── check_environment.py # Environment verification
└── references/
└── analysis-frameworks.md # Analysis framework details
On first use, the skill will prompt you to set a default output directory:
- Option A: Use default
~/video-analysis/ - Option B: Specify each time
- Option C: Set a fixed custom directory
After analysis, you'll receive:
| File | Content |
|---|---|
{video_id}.mp4 |
Original video |
{video_id}.srt |
Raw subtitles |
{video_id}_transcript.md / {video_id}_文字稿.md |
Corrected transcript |
{video_id}_analysis.md / {video_id}_分析报告.md |
Three-dimensional analysis report |
This is a Claude Skill that works with AI coding assistants:
| Environment | Model | Status |
|---|---|---|
| Antigravity | Gemini 3 Pro | ✅ Supported |
| Cursor | Claude 4.5 Opus | ✅ Tested & Recommended |
| Claude Code | Claude 4.5 Opus | ✅ Supported |
| Windsurf | Any Claude model | ✅ Supported |
| Trae | Claude 3.5/4 | ✅ Supported |
💡 Best Performance: Tested with Claude 4.5 Opus, achieving optimal results in transcription correction and three-dimensional analysis.
MIT License