Agent skill · nvidia
medtech-model-evidence-export
Exports sanitized metadata, parameters, reproducibility details, quality metrics, and optional review artifacts from Medical AI inference runs or evidence packs to MLflow. Use after inference, including NV-Generate runs; not for live training tracking, model registration, or clinical use.
What it needs
About 3k tokens when loaded.
What this skill does
Medtech Model Evidence Export to MLflow Purpose Mirror an existing medical-inference result or evidence pack into MLflow after the run and emit the exportresult JSON contract. Keep the original evidence pack as the source of truth. Training skills should add MLflow inside their training loops instead. Instructions 1. Run scripts/exportevidencepack.py in the default dry-run mode. 2. Inspect params, metrics, artifactplan, and mlflow.note.content. 3. Choose --mode local or --mode databricks only after checking the target. 4. Keep --artifact-policy metadata unless the target is approved for images. 5. For preview or all in a live mode, also pass --confirm-medical-artifact-upload. 6. Keep --source-ref, --note, config filenames, and artifact filenames free of patient or secret identifiers; always review the dry-run output first. Hosts with a script helper can use runscript("scripts/exportevidencepack.py", args=["PACKORRESULT", "--mode", "dry-run"]). Available Scripts Script Purpose Arguments --- --- --- scripts/exportevidencepack.py Export post-hoc inference evidence through MLflow. PACKORRESULT --mode dry-run --artifact-policy metadata Prerequisites Python 3.10+. mlflow>=2.10,<4 for local or databricks mode. numpy>=1.24,<3 and nibabel>=4,<6 for NIfTI quality metrics and previews. MLFLOWTRACKINGURI may select a caller-managed tracking server. Databricks mode uses the caller's DATABRICKSHOST, DATABRICKSTOKEN, or configured Databricks profile. The declared network endpoint is https://<caller-provided-mlflow-or-databricks-workspace>; Docker and GPU are not required. Local mode may write the MLflow store under <current-working-directory>/mlruns. Examples Preview the export without contacting MLflow: Export a direct NV-Generate result with reproducibility metadata: Log downsampled slice previews, but not raw NIfTI files: --artifact-policy all additionally uploads discovered or explicitly supplied NIfTI images and masks, subject to --max-artifact-mb. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/medtech-model-evidence-export