neqsim-technical-document-reading

neqsim-technical-document-reading is a Physics, mathematics & simulation skill for AI agents, published by equinor in the neqsim repository on GitHub. Skillspace rates neqsim-technical-document-reading F (50/100) and it passed the safety scan; the rating is based on static analysis only.

Reads and extracts structured engineering data from technical documents (PDFs, Word, Excel, CSV) and engineering images/drawings (P&IDs, vendor datasheets, mechanical arrangements, performance maps). USE WHEN: a user provides engineering documents or images — equipment data sheets, technical requirements, design basis, well test reports, P&ID descriptions, inspection reports, standards, vendor drawings, compressor maps, phase envelopes, material certificates, trapped-liquid fire rupture evidence packs, or water-hammer route/event evidence — and needs structured data for process simulation. Covers document classification, extraction patterns by document type, image/figure analysis with view_image, unit normalization, data quality scoring, and output formats.

Grade
F
Quality
50 / 100
Safety
Passed
GitHub stars
132

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubequinor/neqsim

Our review

Architecture
68 / 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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