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imaging-data-commons

Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.

66

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Medium

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SKILL.md
Quality
Evals
Security

Quality

Content

72%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A highly actionable, well-structured skill body with excellent progressive disclosure and executable examples. Its main weaknesses are length/redundancy and the absence of explicit validation feedback loops in the batch-download workflow.

Suggestions

Add an explicit validate-then-retry feedback loop to the batch download section (e.g., verify each batch's file count/integrity before proceeding to the next, retry failed series) to lift workflow_clarity above the batch cap.

De-duplicate the idc-index version-check logic into one canonical block and reference it, removing the repeated upgrade snippets.

Trim the generic pydicom/SimpleITK 'Integration with Analysis Pipelines' examples, which re-explain library usage Claude already knows; keep only the IDC-specific wiring.

DimensionReasoningScore

Conciseness

Mostly efficient with dense code/tables, but the ~830-line body includes redundancy (version-check logic repeated in multiple places) and generic pydicom/SimpleITK integration examples that assume concepts Claude already knows.

3 / 5

Actionability

Abundant copy-paste-ready, executable code and CLI commands covering query, download, visualize, license-check, citation, and batch cases with specific examples throughout.

5 / 5

Workflow Clarity

A clear 3-step core workflow and an upfront version-check checkpoint exist, but batch download operations lack explicit validate-then-retry feedback loops between batches; the batch cap guidance holds this at 3.

3 / 5

Progressive Disclosure

Clear overview with a Quick Navigation table mapping each of the 9 reference guides (all confirmed present in ./references/) to a load trigger; references are one level deep, well-signaled, and detail is appropriately split out.

5 / 5

Total

16

/

20

Passed

Description

88%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states capabilities and use-cases with concrete actions and explicit 'Use for...' trigger guidance. Minor gaps in natural-term synonyms (DICOM, TCIA, standalone IDC) keep trigger coverage just short of comprehensive.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('Query and download', 'Query by metadata, visualize in browser, check licenses') using a named tool (idc-index), giving comprehensive coverage of capabilities.

5 / 5

Completeness

Explicitly answers both what ('Query and download public cancer imaging data... Query by metadata, visualize in browser, check licenses') and when ('Use for accessing large-scale radiology... datasets for AI training or research') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Good natural-term coverage including 'NCI Imaging Data Commons', 'radiology (CT, MR, PET)', 'pathology datasets', 'AI training or research', but omits common synonyms a user might say like 'DICOM', 'TCIA', or standalone 'IDC'.

4 / 5

Distinctiveness Conflict Risk

Clearly niched to NCI Imaging Data Commons / cancer imaging with distinct triggers, but could see minor overlap with generic medical-imaging or public-data-download skills.

4 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (848 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
foryourhealth111-pixel/Vibe-Skills
Reviewed

Table of Contents

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