allbeingsfuture/skills@pdf

What problem does it solve?

PDF files are often locked in static layouts, scanned images, or complex form structures that make extracting text, tables, images, and form values manual, time-consuming, and error-prone. This guide centralizes reliable methods and scripts to programmatically read, extract, OCR, merge, split, rotate, watermark, encrypt/decrypt, and fill PDFs so you can automate document workflows and reduce manual effort.

Core Features & Use Cases

• Text and Table Extraction: Use pdfplumber, pypdf, and pypdfium2 workflows to extract plain text and structured tables for data pipelines and reporting.
• Form Handling: Detect and fill both fillable and non-fillable forms with validation helpers, bounding-box checks, and annotation-based fallbacks.
• Image and OCR Support: Convert pages to images, run OCR on scanned documents, and extract embedded images with poppler, pytesseract, or pypdfium2.
• Page and File Operations: Merge, split, rotate, watermark, password-protect, and optimize PDFs with qpdf, pdftk, or programmatic libraries.
• Use Case Example: Batch-extract invoice fields and tables from hundreds of PDFs, validate field coordinates, fill standardized forms, and produce a combined CSV and a merged searchable archive.

Quick Start

Ask the skill to extract all text and tables from the attached PDF, perform OCR on scanned pages, and return a combined CSV of tables plus a short plain-text summary.