Evidence Insight
kegg-database
89100Total Score
Core Capability
83 / 100
Functional Suitability
10 / 12
Reliability
9 / 12
Performance & Context
8 / 8
Agent Usability
13 / 16
Human Usability
8 / 8
Security
9 / 12
Maintainability
10 / 12
Agent-Specific
16 / 20
Medical Task
20 / 20 Passed
97You need to fetch KEGG pathway, gene, compound, enzyme, disease, or drug records directly from the KEGG REST API
4/4
93You want to perform gene ↔ pathway mapping (e.g., building inputs for pathway enrichment or reporting)
4/4
91Full coverage of core KEGG REST operations via Python helpers:
4/4
91kegg_info (database metadata)
4/4
91End-to-end case for Full coverage of core KEGG REST operations via Python helpers:
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 | The archived evaluation kept the skill tied to retrieved records or indexed source material rather than invented scientific claims. |
| Practice Boundaries | PASS | The legacy review kept this workflow on the evidence-access side of the boundary, not the advice-giving side. |
| Methodological Ground | PASS | The older review treated the package logic as methodologically aligned with its stated workflow. |
| Code Usability | PASS | The legacy evaluation did not preserve a usability failure in the packaged retrieval path. |
Core Capability83 / 100 — 8 Categories
Functional Suitability
Functional suitability was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
10 / 12
83%
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
The legacy audit gave full marks to performance context for this package.
8 / 8
100%
Agent Usability
A modest deduction remained in agent usability for kegg-database in the archived review.
13 / 16
81%
Human Usability
Human usability reached full score in the archived evaluation.
8 / 8
100%
Security
The legacy audit deducted points for kegg-database in security.
9 / 12
75%
Maintainability
The archived evaluation left some headroom for kegg-database under maintainability.
10 / 12
83%
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: 92.6 / 100 — Assertions: 20/20 Passed
97
Canonical
You need to fetch KEGG pathway, gene, compound, enzyme, disease, or drug records directly from the KEGG REST API
4/4 ✓
93
Variant A
You want to perform gene ↔ pathway mapping (e.g., building inputs for pathway enrichment or reporting)
4/4 ✓
91
Edge
Full coverage of core KEGG REST operations via Python helpers:
4/4 ✓
91
Variant B
kegg_info (database metadata)
4/4 ✓
91
Stress
End-to-end case for Full coverage of core KEGG REST operations via Python helpers:
4/4 ✓
97
Canonical✅ Pass
You need to fetch KEGG pathway, gene, compound, enzyme, disease, or drug records directly from the KEGG REST API
The archived run for You need to fetch KEGG pathway, gene, compound, enzyme, disease, or... remained guidance-driven rather than command-driven.
Basic 36/40|Specialized 60/60|Total 97/100
✅A1The kegg-database 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
93
Variant A✅ Pass
You want to perform gene ↔ pathway mapping (e.g., building inputs for pathway enrichment or reporting)
You want to perform gene ↔ pathway mapping (e.g., building inputs... was evaluated as a bounded documentation path, not as a runnable script workflow.
Basic 34/40|Specialized 59/60|Total 93/100
✅A1The kegg-database 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
91
Edge✅ Pass
Full coverage of core KEGG REST operations via Python helpers:
This edge case stayed inside the documented workflow and remained instruction-led.
Basic 33/40|Specialized 58/60|Total 91/100
✅A1The kegg-database 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
91
Variant B✅ Pass
kegg_info (database metadata)
The archived run for kegg_info (database metadata) remained guidance-driven rather than command-driven.
Basic 32/40|Specialized 59/60|Total 91/100
✅A1The kegg-database 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
91
Stress✅ Pass
End-to-end case for Full coverage of core KEGG REST operations via Python helpers:
End-to-end case for Full coverage of core KEGG REST operations via... was evaluated as a bounded documentation path, not as a runnable script workflow.
Basic 29/40|Specialized 60/60|Total 91/100
✅A1The kegg-database 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 Total92.6 / 100
Key Strengths
- Primary routing is Evidence Insight with execution mode B
- Static quality score is 83/100 and dynamic average is 79.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: Script verification 1/1; adjustment=5. kegg_api.py: OK