Extract and process text from local PDF files with OCR fallback.
npx skills add https://github.com/takimoto-sketch/medica-agent --skill pdf-takimoto-sketch
Please help me install this Agent Skill. Skill: pdf Source: https://github.com/takimoto-sketch/medica-agent/tree/main/.claude/skills/pdf Command: npx skills add https://github.com/takimoto-sketch/medica-agent --skill pdf-takimoto-sketch
Automates the manual, error-prone work of reading, extracting, converting, splitting, merging, and filling PDF documents so teams can process documents quickly and safely.
Please extract and summarize text from reports/minutes/input/proposal.pdf and return page-level text plus a short summary.
High-intent search queries and answers about installing and using this skill.
To extract text from a scanned PDF, the system applies an OCR fallback mechanism during page-level text extraction. It renders pages as images and processes them to output searchable text for your local documents.
Yes, you can convert PDF content to Markdown. The system performs markdown conversion and applies token-aware chunking for long documents, allowing structured text extraction that breaks down large files for analysis.
You can mask PII during PDF text extraction by utilizing the built-in PII masking feature. It processes local PDF files to redact sensitive information, enabling safe document analysis and reporting without exposing personal data.
The best way to fill form fields in a PDF is through automated form field inspection and filling. The system processes local PDFs to handle form fields directly and exports the completed documents to a designated output directory.
Yes, PDF text extraction supports splitting and merging pages. The system handles page-selected extraction, allowing you to split specific pages from a local PDF or merge multiple documents into a single output file.
After processing a local PDF file, you can export results to JSON, Markdown, PNG, or PDF formats. The system saves these outputs to a specific directory, providing structured data, text, images, or modified documents.
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