Extracts high-fidelity text from scanned PDFs and images using Apple Silicon-optimized Vision OCR.
This skill provides a robust pipeline for converting PDF documents—including scanned files and image-based PDFs—into machine-readable formats like Markdown, plain text, or JSONL. By leveraging Apple's native Vision framework and PyMuPDF, it offers high-performance, parallelized OCR processing specifically optimized for Apple Silicon (M-series) Macs. It is an essential tool for developers and researchers who need to digitize legacy documents, invoices, or research papers where standard text extraction fails or produces garbled results.
Key Features
01Support for Markdown, JSONL, and plain text output formats
020 GitHub stars
03Multi-language support for international document processing
04Native Apple Vision OCR integration for superior accuracy on macOS
05Parallel multi-threaded processing for rapid multi-page PDF conversion
06Adjustable DPI settings to optimize between recognition quality and speed
Use Cases
01Digitizing scanned paper archives into searchable Markdown documentation
02Extracting text from image-based PDFs where copy-pasting is restricted or broken
03Preprocessing bulk document sets for LLM context or data analysis pipelines
