ocr-and-documents

You can extract text from scanned PDFs and convert it to Markdown by applying OCR workflows that recognize text and preserve layout. This skill uses marker-pdf for complex layouts and tables, outputting clean Markdown from image-based files.

The best way to pull text from a remote research paper available by URL is using web-based extraction. This skill applies web_extract for public PDFs like arXiv papers, returning the document content as usable plain text or Markdown.

Yes, this OCR tool recovers tables and equations from complex document layouts. It applies marker-pdf specifically for handling complex layouts, tables, equations, and forms when processing scanned documents or image-based files into Markdown.

Yes, you can parse text-based PDFs without running heavy OCR processing. This skill applies pymupdf for lightweight PDF parsing when files already contain embedded text, reserving marker-pdf OCR for scanned documents and complex layouts.

To digitize and extract data from scanned invoices into editable text, apply a dedicated OCR workflow. This skill handles invoice digitization using marker-pdf to extract text from image-based documents and return it as clean, searchable Markdown.

No, you do not need a separate tool to extract text from DOCX office files. This skill parses DOCX documents structurally using python-docx, allowing you to process office files alongside PDFs and scanned documents in one workflow.