pdf-reader

To extract tables and text from PDF documents while preserving layout, this skill uses layout-aware processing to maintain headings, sections, and multi-column reading order. It pulls structured data into usable formats like JSON, CSV, and Markdown.

Yes, you can parse scanned PDFs with non-selectable text using OCR. The skill supports OCR libraries like pdf2image to interpret content from scanned images, ensuring accurate data extraction from archived or image-based documents.

The best way to extract invoice lines and metadata from a batch of PDFs is using structured data extraction. This skill identifies and pulls form fields, tables, and text, outputting the compiled results in CSV and JSON formats for reporting.

Yes, this PDF parsing approach supports multi-column layouts and complex form fields. It applies layout-aware processing to maintain the correct reading order and accurately extract form data for contract review and archival data extraction.

To convert an academic paper PDF into structured Markdown or JSON, the skill identifies text, tables, and form data while preserving document structure. It outputs the parsed academic content directly into your chosen structured format.

The required libraries for PDF parsing and OCR in this workflow include pypdf, pdfplumber, and pdf2image. These dependencies enable the skill to handle multi-column layouts, non-selectable content, and structured data output.