Locate exact text coordinates in PDFs and generate HTML proof pages.
npx skills add https://github.com/metedata/pdf-proof --skill pdf-proof
Please help me install this Agent Skill. Skill: pdf-proof Source: https://github.com/metedata/pdf-proof/tree/main Command: npx skills add https://github.com/metedata/pdf-proof --skill pdf-proof
This Skill helps users move beyond unverified AI claims by producing evidence that specific values actually appear in a source PDF document.
Verify values from your PDF by asking for screenshot proof of each specific field or number you need confirmed.
High-intent search queries and answers about installing and using this skill.
PDF text highlighting for visual proof works by locating exact text coordinates using OCR, cropping the surrounding area, and overlaying a highlight on the matched value. It generates an HTML proof page with a summary table and per-value proof cards for review.
Yes, you can generate screenshot proof from scanned documents. The process applies OCR to locate exact text coordinates, crops around the matched financial values, and outputs a standalone HTML page with highlighted screenshots as verification.
Yes, PDF visual verification works with Tesseract and PyMuPDF for contract review. These dependencies enable deterministic text search and coordinate-accurate cropping in scanned documents, allowing you to cross-reference clauses and highlight exact matches.
The best way to cross-reference financial forms without unverified claims is using deterministic text search that produces visual evidence. By locating exact coordinates and highlighting matched values, you generate a standalone HTML proof page with an audit trail.
To reduce wrong-highlight risk during an invoice audit, use a readback cross-check mechanism. This verifies the highlighted region by reading text back to confirm it matches the target value before generating the final visual proof.
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