ocr-and-documents

To extract text from scanned PDF documents, this Skill applies OCR processing and layout-aware conversion to generate searchable markdown. It handles complex layouts and equations, converting scanned archives into structured text for research workflows.

Yes, you can convert text-based PDFs to markdown while preserving tables and metadata. This Skill uses lightweight parsing tools like pymupdf to extract text, images, and structured information into a searchable markdown format.

Yes, pymupdf4llm works with complex document layouts for markdown conversion. This Skill leverages it alongside pymupdf and marker-pdf to handle high-quality OCR, equation parsing, and layout-aware text extraction from difficult documents.

The best way to parse academic papers into searchable text is using OCR and layout analysis tools. This Skill converts reports and academic papers into structured markdown, supporting metadata retrieval and complex layout handling for knowledge workflows.

Text extraction fails on scanned documents without OCR because they contain images rather than embedded text layers. This Skill applies layout-aware OCR processing to interpret these images, extracting usable text and structured information from archival files.