document-conversion
/document-conversion
This skill should be used when users need to convert PDFs (especially with tables or figures), mentions 'convert', 'PDF', 'document processing', has complex academic papers to import, or asks about document conversion options.
- Author
- linxule ↗
- Repository
- interpretive-orchestration ↗
- Licence
- MIT
- Last repository change
- 13.07.2026
Assessment and security
- Files in this package
- 1
- Scripts
- 0
- HTML comments
- 0
- URLs in SKILL.md
- 2
No signals detected. Repository changed on 13.07.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
What it does and when to use it
This skill should be used when users need to convert PDFs (especially with tables or figures), mentions 'convert', 'PDF', 'document processing', has complex academic papers to import, or asks about document conversion options.
Triggers from the description
Original author description
This skill should be used when users need to convert PDFs (especially with tables or figures), mentions 'convert', 'PDF', 'document processing', has complex academic papers to import, or asks about document conversion options.
How it works
- When to Use
- Conversion Options
- When to Use Which
- Tool Selection Logic
- Usage Examples
- MinerU Specific Features
- Output Quality Checklist
- Integration with Research Workflow
- Fallback Options
- Related
SKILL.md preview
---
name: document-conversion
description: "This skill should be used when users need to convert PDFs (especially with tables or figures), mentions 'convert', 'PDF', 'document processing', has complex academic papers to import, or asks about document conversion options."
---
# 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
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
Versions
| Repository | Score | Licence |
|---|---|---|
| This page · linxule/interpretive-orchestration | 100 | MIT |
| codealta/codealta | 100 | BSD-2-Clause |
| nimadorostkar/Claude-Skills-collection | 100 | MIT |
| athola/claude-night-market | 100 | MIT |
| linxule/interpretive-orchestration | 100 | MIT |
Database snapshot: 13.11.2026 · package version e867201a27c6 (SHA-256 digest of the entire package)
Downloads in the last 30 days: 0 · ranking
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