pdf

To extract text and tables from PDF documents automatically, this Skill uses pdfplumber to parse binary streams and identify structured table data. It processes administrative and financial workflows like invoice data extraction, rendering content into usable formats without manual entry.

Automated form filling for non-fillable scanned PDFs is supported using coordinate-based annotation. The Skill uses pdf2image and pillow to render scanned pages, applies data mapping with built-in validation checks, and generates new PDFs for digitized records.

The best way to merge and split bulk PDFs for archival management is using pypdf to parse and restructure binary streams. The Skill handles end-to-end document manipulation, allowing you to combine multiple files or extract specific pages for operational workflows.

You need the Python libraries pdf2image, pillow, pdfplumber, and pypdf installed to process scanned documents with OCR. These dependencies enable the Skill to render scanned pages, parse existing content, and generate modified PDFs without manual intervention.

PDF processing handles encrypted files and watermarks by modifying existing content through pypdf. The Skill can encrypt or decrypt files and add watermarks to documents, applying these modifications directly to parsed binary streams for secure archival management.

A limitation of using pdfplumber for data extraction is that it works best for digitally generated PDFs rather than scanned paper documents. Scanned PDFs require OCR processing via pdf2image and pillow to render pages before extraction, adding processing overhead for archival workflows.