document-processor

Text and table extraction from PDFs works by parsing document structure using pdfplumber and pypdf to isolate content blocks and tabular data, then outputting structured results in JSON, CSV, or Markdown format for further analysis or integration.

PDF to Word conversion is supported through bidirectional format transformation—read PDF content as text, tables, and metadata, then write to DOCX format using python-pptx and related libraries, preserving structure in the output document.

Excel to CSV export processes XLSX files using openpyxl to read sheets and cell data, then transforms and writes output as CSV, JSON, or Markdown, enabling data portability and downstream processing in any application.

Supported formats include PDF, DOCX, XLSX, and PPTX for reading and writing. The Skill analyzes all formats to extract text, tables, and images, then converts between formats or exports to CSV, JSON, and Markdown as needed.

AI-generated summaries are produced alongside extracted content—text, tables, and metadata are parsed from documents, then summarized automatically and output in JSON or Markdown, reducing manual review time for large batches.

Automated conversion preserves formatting, tables, and metadata while eliminating manual labor for bulk processing; use it when you need repeatable, consistent output across multiple files or when preserving complex structure matters more than speed.