kermt-embed

kermt-embed is a Chemistry & materials skill for AI agents, published by NVIDIA-BioNeMo in the bionemo-agent-toolkit repository on GitHub. Skillspace rates kermt-embed D (67/100) and it passed the safety scan; the rating is based on static analysis only.

Extract per-molecule embeddings from any encoder-bearing KERMT checkpoint (grover_base / cmim / hybrid / finetuned). Writes one .npy per readout type (atom_from_atom, bond_from_atom, atom_from_bond, bond_from_bond) plus canonical_smiles.npy and validity.npy. Calls task/extract_embeddings.py (which featurizes SMILES on the fly — no pre-computed features needed).

Grade
D
Quality
67 / 100
Safety
Passed
GitHub stars
371

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 GitHubNVIDIA-BioNeMo/bionemo-agent-toolkit

Our review

Architecture
94 / 100
Maturity
Basic: a single SKILL.md
Security scan
Low-risk patterns
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 1 other repositories, in 0 collections
Scope
Vendor-specific: built around one product. Using public KERMT model checkpoints and container tooling

What the scanner flagged

  • mentions secrets in text

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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