dicom-series-to-volume
Pass
Audited by Gen Agent Trust Hub on Jun 12, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill performs local file transformations on DICOM datasets. It uses standard, well-known Python libraries (pydicom, nibabel, numpy) for medical imaging tasks.
- [SAFE]: Extensive documentation is provided in the SKILL.md and BENCHMARK.md files, clearly outlining the tool's limitations (no multi-frame support, single-series only) and safety warnings regarding clinical use.
- [SAFE]: The skill includes a 'fixtures' directory and a generation script (
generate_fixtures.py) to create synthetic datasets for testing, which is an excellent security and reliability practice to avoid using real Patient Health Information (PHI) during development. - [SAFE]: The YAML manifest (
skill_manifest.yaml) includes detailed runtime constraints, validation gates (sanity_checks), and reproducibility metrics, which helps ensure the agent operates within a restricted and predictable environment. - [SAFE]: The metadata extraction in
scripts/series_to_volume.pyis limited to standard DICOM header fields (Modality, StudyInstanceUID, etc.) necessary for imaging provenance and does not access sensitive system files or environment variables.
Audit Metadata