Data Analysis
imaging-data-commons
85100Total Score
Core Capability
83 / 100
Functional Suitability
11 / 12
Reliability
9 / 12
Performance & Context
6 / 8
Agent Usability
14 / 16
Human Usability
7 / 8
Security
11 / 12
Maintainability
9 / 12
Agent-Specific
16 / 20
Medical Task
20 / 20 Passed
91Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4
87Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4
85Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4
85Documentation-first workflow with no packaged script requirement
4/4
85End-to-end case for Scope-focused workflow aligned to: Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4
Veto GatesRequired pass for any deployment consideration
Skill Veto✓ All 4 gates passed
✓
Operational Stability
System remains stable across varied inputs and edge cases
PASS✓
Structural Consistency
Output structure conforms to expected skill contract format
PASS✓
Result Determinism
Equivalent inputs produce semantically equivalent outputs
PASS✓
System Security
No prompt injection, data leakage, or unsafe tool use detected
PASSResearch Veto✅ PASS — Applicable
| Dimension | Result | Detail |
|---|---|---|
| Scientific Integrity | PASS | Scientific integrity held because extraction and analysis outputs stayed tied to provided text, metadata, or runtime evidence rather than invented study findings. |
| Practice Boundaries | PASS | The evaluated outputs stayed inside the Use idc-index to query and download public cancer imaging data from NCI Imaging Data... and did not drift into unsupported interpretation beyond the available inputs. |
| Methodological Ground | PASS | Methodological grounding held because the package kept its judgments tied to explicit rubric logic. |
| Code Usability | PASS | The legacy audit did not flag code-usability issues for the packaged imaging-data-commons workflow. |
Core Capability83 / 100 — 8 Categories
Functional Suitability
Related legacy finding for imaging-data-commons: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
11 / 12
92%
Reliability
Reliability was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
9 / 12
75%
Performance & Context
Performance-context scoring suggests the package could handle larger or denser runs a little more gracefully.
6 / 8
75%
Agent Usability
Agent usability was strong, but the workflow could surface its entry conditions a little more directly.
14 / 16
88%
Human Usability
Human usability remained solid, with minor room to simplify the way analysis outcomes are presented.
7 / 8
88%
Security
The packaged workflow stayed safe overall, with only a small remaining deduction around boundary signaling.
11 / 12
92%
Maintainability
Maintainability stayed solid, with only limited room to simplify scripts, dependencies, or packaging structure.
9 / 12
75%
Agent-Specific
The archived deduction in agent specific traces back to: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
16 / 20
80%
Core Capability Total83 / 100
Medical TaskExecution Average: 86.6 / 100 — Assertions: 20/20 Passed
91
Canonical
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4 ✓
87
Variant A
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4 ✓
85
Edge
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4 ✓
85
Variant B
Documentation-first workflow with no packaged script requirement
4/4 ✓
85
Stress
End-to-end case for Scope-focused workflow aligned to: Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
4/4 ✓
91
Canonical✅ Pass
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
The archived run treated Use idc-index to query and download public cancer imaging data from... as a bounded extraction workflow, keeping attention on source fields, fallback logic, and output shape.
Basic 36/40|Specialized 55/60|Total 91/100
✅A1The imaging-data-commons output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
87
Variant A✅ Pass
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
This variant a case stayed focused on extracting and normalizing evidence from the provided records instead of drifting into unsupported interpretation.
Basic 34/40|Specialized 53/60|Total 87/100
✅A1The imaging-data-commons output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
85
Edge✅ Pass
Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
The archived run treated Use idc-index to query and download public cancer imaging data from... as a bounded extraction workflow, keeping attention on source fields, fallback logic, and output shape.
Basic 33/40|Specialized 52/60|Total 85/100
✅A1The imaging-data-commons output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
85
Variant B✅ Pass
Documentation-first workflow with no packaged script requirement
The archived run treated Documentation-first workflow with no packaged script requirement as a bounded analysis workflow rather than a purely narrative instruction path.
Basic 32/40|Specialized 53/60|Total 85/100
✅A1The imaging-data-commons output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
85
Stress✅ Pass
End-to-end case for Scope-focused workflow aligned to: Use idc-index to query and download public cancer imaging data from NCI Imaging Data Commons. Used to access large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Supports metadata querying, in-browser visualization, and license checking
This stress case stayed focused on extracting and normalizing evidence from the provided records instead of drifting into unsupported interpretation.
Basic 29/40|Specialized 56/60|Total 85/100
✅A1The imaging-data-commons output structure matches the documented deliverable
✅A2The instruction path remains actionable for the documented case
✅A3The output stays fully within the documented skill boundary
✅A4The response quality is acceptable for the documented path
Pass rate: 4 / 4
Medical Task Total86.6 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode A
- Static quality score is 83/100 and dynamic average is 78.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: No script verification was applicable