evaluating-machine-learning-models — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited evaluating-machine-learning-models (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Use this skill when the model exists and the question is whether it is good enough.
This skill focuses on choosing and interpreting the right evaluation metrics for the problem, then comparing candidate models or thresholds.
scikit-learn for classical modeling or ml-pipeline-workflow for end-to-end workflow ownershippreprocessing-data-with-automated-pipelinesml-data-leakage-guardscikit-learn for class-level error breakdowns and confusion matricesscientific-reporting when the evaluation must become a deliverable~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.