Files
skill-seekers-reference/configs/example_pdf.json
yusyus 6936057820 Add PDF documentation support (Tasks B1.1-B1.8)
Complete PDF extraction and skill conversion functionality:
- pdf_extractor_poc.py (1,004 lines): Extract text, code, images from PDFs
- pdf_scraper.py (353 lines): Convert PDFs to Claude skills
- MCP tool scrape_pdf: PDF scraping via Claude Code
- 7 comprehensive documentation guides (4,705 lines)
- Example PDF config format (configs/example_pdf.json)

Features:
- 3 code detection methods (font, indent, pattern)
- 19+ programming languages detected with confidence scoring
- Syntax validation and quality scoring (0-10 scale)
- Image extraction with size filtering (--extract-images)
- Chapter/section detection and page chunking
- Quality-filtered code examples (--min-quality)
- Three usage modes: config file, direct PDF, from extracted JSON

Technical:
- PyMuPDF (fitz) as primary library (60x faster than alternatives)
- Language detection with confidence scoring
- Code block merging across pages
- Comprehensive metadata and statistics
- Compatible with existing Skill Seeker workflow

MCP Integration:
- New scrape_pdf tool (10th MCP tool total)
- Supports all three usage modes
- 10-minute timeout for large PDFs
- Real-time streaming output

Documentation (4,705 lines):
- B1_COMPLETE_SUMMARY.md: Overview of all 8 tasks
- PDF_PARSING_RESEARCH.md: Library comparison and benchmarks
- PDF_EXTRACTOR_POC.md: POC documentation
- PDF_CHUNKING.md: Page chunking guide
- PDF_SYNTAX_DETECTION.md: Syntax detection guide
- PDF_IMAGE_EXTRACTION.md: Image extraction guide
- PDF_SCRAPER.md: PDF scraper usage guide
- PDF_MCP_TOOL.md: MCP integration guide

Tasks completed: B1.1-B1.8
Addresses Issue #27
See docs/B1_COMPLETE_SUMMARY.md for complete details

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-23 00:23:16 +03:00

18 lines
558 B
JSON

{
"name": "example_manual",
"description": "Example PDF documentation skill",
"pdf_path": "docs/manual.pdf",
"extract_options": {
"chunk_size": 10,
"min_quality": 5.0,
"extract_images": true,
"min_image_size": 100
},
"categories": {
"getting_started": ["introduction", "getting started", "quick start", "setup"],
"tutorial": ["tutorial", "guide", "walkthrough", "example"],
"api": ["api", "reference", "function", "class", "method"],
"advanced": ["advanced", "optimization", "performance", "best practices"]
}
}