ontology-mapper

ontology-mapper is a Chemistry & materials skill for AI agents, published by HeshamFS in the materials-simulation-skills repository on GitHub. Skillspace rates ontology-mapper F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.

Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.

Map materials science terms, crystal structures, and sample descriptions to standardized ontology classes and properties — resolve natural-language concepts to ontology entries with confidence scores, translate Bravais lattice types, space groups, and lattice constants into ontology-compliant annotations, and produce full sample metadata from structured descriptions. Supports any ontology in ontology_registry.json (CMSO, ASMO, etc.). Use when annotating simulation inputs with FAIR metadata, translating "BCC iron" or "FCC copper" into formal ontology terms, preparing machine- readable sample descriptions, or bridging between lab vocabulary and ontology vocabulary, even if the user only says "what CMSO terms describe my material" or "annotate this sample for me."

Grade

F

Quality

45 / 100

Safety

Risky

GitHub stars

59

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

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