neqsim-pdf-ocr
neqsim-pdf-ocr is a Computer vision skill for AI agents, published by equinor in the neqsim repository on GitHub. Skillspace rates neqsim-pdf-ocr C (71/100) and it passed the safety scan; the rating is based on static analysis only.
OCR-based text extraction from PDFs (scanned documents, P&IDs, vendor datasheets, engineering drawings) using OCRmyPDF, Tesseract, and pytesseract. USE WHEN: a PDF has no embedded text layer (scanned), pymupdf returns empty/low text, or the user explicitly asks to extract text/tags from a P&ID, mechanical drawing, or paper-original datasheet. Pairs with neqsim-technical-document-reading (which handles text-based PDFs and visual analysis via view_image).
- Grade
- C
- Quality
- 71 / 100
- Safety
- Passed
- GitHub stars
- 132
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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