document-conversion

What this skill does

# document-conversion

Robust PDF and document conversion with intelligent tool selection. Chooses the best available conversion method based on document complexity and MCP availability.

## When to Use

Use this skill when:
- User needs to convert PDFs, especially with tables or figures
- User mentions "convert", "PDF", "document processing"
- User has complex academic papers to import
- User asks about document conversion options

## Conversion Options

| Feature | MinerU (Optional) | Manual Conversion |
|---------|-------------------|-------------------|
| API Key Required | Yes (MINERU_API_KEY) | No |
| PDF Accuracy | 90%+ (VLM mode) | Varies |
| Table Extraction | Excellent | Manual cleanup |
| Figure Handling | Extracts + describes | Manual description |
| Formula Recognition | Yes | Limited |
| Multi-column | Excellent | Manual formatting |
| Cost | Pay per page | Free |

## When to Use Which

### Use MinerU When:
- PDF has complex tables with merged cells
- Document has multi-column layouts
- Figures/charts need extraction
- Mathematical formulas present
- Academic paper with structured formatting
- Accuracy is critical

### Use Manual Conversion When:
- Simple text-based documents
- MinerU API key not available
- Cost is a concern
- Document is straightforward

## Tool Selection Logic

```
Is the document a PDF with tables/figures?
├── Yes, complex tables
│   └── MinerU available?
│       ├── Yes → Use MinerU (vlm mode)
│       └── No → Manual conversion + review
├── Yes, simple formatting
│   └── Manual conversion or external tool
└── No, other format
    └── Is it audio?
        ├── Yes → External transcription service
        └── No → Manual conversion
```

## Usage Examples

### MinerU (Complex PDF)
```
Use mineru_parse to convert this academic paper:
- URL: https://example.com/paper.pdf
- Model: vlm (for 90% accuracy)
- Enable: formula, table recognition
```

### Manual Conversion (Simple Document)
```
For simple PDFs without MinerU:
1. Use Adobe Acrobat to export to Word/text
2. Or open in Google Docs for auto-OCR
3. Review and clean up formatting
```

### Batch Processing
```
For multiple PDFs:
1. Check which have complex tables (use MinerU if available)
2. Process simple ones with manual conversion
3. Queue complex ones for MinerU batch if API key available
```

## MinerU Specific Features

### VLM vs Pipeline Mode
- **VLM Mode:** Uses vision-language model, 90%+ accuracy, slower
- **Pipeline Mode:** Traditional parsing, faster, lower accuracy

### Page Selection
```
Parse only specific pages:
mineru_parse({
  url: "https://...",
  pages: "1-10,15,20-25"
})
```

### Batch Processing
```
Process multiple documents:
mineru_batch({
  urls: ["url1", "url2", "url3"],
  model: "vlm"
})
```

## Output Quality Checklist

After conversion, verify:
- [ ] Text is accurately extracted
- [ ] Tables maintain structure
- [ ] Headers/sections are correct
- [ ] Figures have descriptions (if MinerU)
- [ ] Formulas are readable (if MinerU)
- [ ] No garbled text from OCR errors

## Integration with Research Workflow

### For Literature (Stream A)
1. Identify papers to convert
2. Complex papers → MinerU (if API key available)
3. Simple papers → Manual conversion
4. Store in stream-a-theoretical/papers/

### For Data Documents (Stream B)
1. Interview transcripts → External service (Otter.ai, Rev.com)
2. PDF field notes → MinerU or manual conversion
3. Store in appropriate stage folder

## Fallback Options

If MinerU unavailable:

1. **Adobe Acrobat** - Export to Word
2. **Google Docs** - Open PDF for auto-OCR
3. **Tesseract OCR** - Command-line tool
4. **Manual transcription** - Last resort

### Audio Transcription

For audio files, use external services:
- **Otter.ai** - Good transcription service
- **Rev.com** - Professional transcription
- **YouTube** - Upload as unlisted video for auto-captions

## Related

- **MCPs:** MinerU (optional)
- **Skills:** interview-ingest for audio, literature-sweep for papers
- **Configuration:** .mcp.json defines MCP availability