Weighs the risk profile of every model weight file in the repo. SafeTensors are safe by design; pickle-derived formats can execute arbitrary code on load.

Documentation completeness mapped to the EU AI Act Article 13 transparency requirements: intended use, limitations, training-data summary, evaluation tables, contact info, and risk notes.

Whether the model card declares a standard SPDX licence; whether the YAML metadata licence tag matches the prose; whether the licence permits the use case you're scoring it for.

Account age, verified org status, prior-model history, and hijacking-pattern flags (typosquatting + burst-creation + mass-mirroring).

Whether the card discloses safety, bias, or fairness evaluations against recognised benchmarks. Partial credit awarded for each disclosed evaluation.

Coverage of regulator-required disclosures: EU AI Act Article 13 signals, NIST AI RMF references, training-data provenance, energy + emissions disclosure.

Community signal (Discussions, PRs, commit activity), external provenance (GitHub repo + arXiv paper + Papers With Code), and cross-platform attestation lookups.