pdf-reading

To extract text from scanned PDFs, this Skill inspects text-layer quality and applies rasterization with an OCR fallback to read image-based pages accurately. It diagnoses whether a document needs OCR or direct text extraction before processing.

The best way to read PDF tables and attachments is using a content inventory approach that checks for embedded files and form fields. This Skill retrieves attachments and extracts tabular data by selecting the appropriate extraction tool based on the document structure.

Yes, you can inspect PDFs to determine page count, fonts, text-layer quality, images, and embedded files. This Skill performs a content inventory to identify what is extractable and what requires visual inspection or attachment retrieval.

Handling encrypted or corrupted PDFs during document reading involves troubleshooting the file structure. This Skill diagnoses PDF content to identify encryption or corruption issues and applies the correct strategy to safely retrieve available information.

Yes, extracting text from data-heavy PDF reports requires poppler-utils, pypdf, pdfplumber, and pypdfium2. These dependencies enable the Skill to diagnose content and choose between extraction, rasterization, or OCR for accurate results.

You should use rasterization instead of direct text extraction for scanned pages, slide decks, and visually important figures. This Skill evaluates text-layer quality to determine when visual inspection is necessary over text extraction.