PDF Utilsv1.0.1

Researchers processing downloaded arXiv papers need to extract all cited arXiv IDs from text-based PDFs and optionally batch-download referenced papers into a local folder. The skill's extract_refs.py automates what would otherwise be hours of manual reference hunting.

Libraries and archives converting image-based scanned documents into searchable text using Tesseract OCR via ocr_pdf.py. Combined with --extract-refs, staff can mine citations from century-old scanned academic journals.

Law firms processing scanned discovery PDFs need OCR plus repeatable merge/split operations across thousands of filings. pdf_ops.py handles batching while ocr_pdf.py makes image-only exhibits text-searchable.

A newsroom or newsletter operator ingests arXiv PDFs, extracts referenced paper IDs, downloads them, and assembles curated weekly digests for subscribers. The pipeline runs entirely scriptable via extract_refs.py with --download.

R&D teams build internal knowledge bases from scanned patent filings and technical papers, OCR'ing them and mining cross-references. Page-range OCR keeps memory usage sane on multi-hundred-page filings.

Offer a subscription platform that ingests user-uploaded PDFs and returns OCR text, extracted arXiv IDs, and auto-downloaded references. Wraps the skill's scripts behind a web API with queueing for large batch jobs.

Agency service that OCRs and structures scanned document collections for law firms, libraries, and archives. Uses pdf_ops.py and ocr_pdf.py as the production pipeline, charging per page or per project.

Sell a desktop or VSCode/Jupyter plugin to researchers that integrates arXiv mining, reference downloading, and PDF merging directly into their workflow. Monetized through one-time licenses or institutional site licenses.