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SKILL verified Apache-2.0 Self-run

Dicom Volume Quality V1

skill-nvidia-medtech-medical-ai-skills-dicom-volume-quality-v1 · by NVIDIA-Medtech

Used to verify dicom-series-to-volume evidence packs by comparing JSON geometry evidence with the emitted NIfTI artifact. Not for clinical validation.

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Install

$ agentstack add skill-nvidia-medtech-medical-ai-skills-dicom-volume-quality-v1

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

DICOM Volume Quality Verifier

Purpose

  • Used for deterministic second-pass review of a dicom-series-to-volume evidence pack.
  • Checks that the source pack passed and that the declared NIfTI artifact matches reported shape, spacing, affine orientation, and voxel range evidence.
  • Manifest I/O: inputs are dicom_series_to_volume_evidence_pack; outputs are dicom_volume_quality_report.

Instructions

  • Use this verifier only on an evidence pack directory produced by skills/dicom-series-to-volume.
  • Run it through eval_engine/run.py when producing verifier evidence.
  • The verifier entrypoint is scripts/grade.py; do not reimplement its checks in an agent prompt.
  • Do not treat a pass as clinical validation of conversion quality.

Available Scripts

| Script | Purpose | Arguments | |---|---|---| | scripts/grade.py | Primary verifier entrypoint declared by skill_manifest.yaml. | EVIDENCE_PACK_DIR |

Prerequisites

  • Runtime requirements: Python packages listed in runtime.side_effects.pip_packages.
  • The input directory must contain manifest.json, validation_summary.json, output.json, and the NIfTI file declared by output.path.

Limitations

  • Audits the emitted NIfTI and JSON evidence; it does not re-read DICOM inputs.
  • Does not prove clinical correctness of orientation or HU scaling.
  • Does not repair non-canonical orientation, spacing, or voxel metadata.

Troubleshooting

| Error | Cause | Fix | |---|---|---| | target_skill_matches fails | The fixture is not a dicom-series-to-volume evidence pack. | Re-run the verifier against the source skill pack directory. | | output_artifact_exists fails | The source pack declares a missing or moved NIfTI path. | Keep the NIfTI inside the pack or use a repo-relative path that resolves from the repository root. | | shape_matches_nifti fails | The JSON output no longer matches the saved NIfTI artifact. | Inspect the source pack and regenerate the evidence after fixing the converter. |

Example

python verifiers/dicom_volume_quality_v1/scripts/grade.py \
  examples/evidence_packs/dicom_series_to_volume_pass

python eval_engine/run.py verifiers/dicom_volume_quality_v1 \
  --fixture examples/evidence_packs/dicom_series_to_volume_pass \
  --out runs/dicom_volume_quality

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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