Other
journal-recommender
90100Total Score
Core Capability
83 / 100
Functional Suitability
11 / 12
Reliability
10 / 12
Performance & Context
8 / 8
Agent Usability
13 / 16
Human Usability
7 / 8
Security
9 / 12
Maintainability
9 / 12
Agent-Specific
16 / 20
Medical Task
20 / 20 Passed
99Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
4/4
95Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
4/4
93Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
4/4
93Packaged executable path(s): scripts/journal_ranker.py
4/4
93End-to-end case for Scope-focused workflow aligned to: Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Use when the user wants to find suitable journals for their research manuscript, especially when they provide a topic, abstract, and target Impact Factor
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
PASSCore 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
11 / 12
92%
Reliability
Reliability was softened by the legacy issue 'Improve stress-case output rigor'. Stress and boundary scenarios show weaker consistency
10 / 12
83%
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 journal-recommender in the archived review.
13 / 16
81%
Human Usability
The archived evaluation left some headroom for journal-recommender under human usability.
7 / 8
88%
Security
A modest deduction remained in security for journal-recommender in the archived review.
9 / 12
75%
Maintainability
A modest deduction remained in maintainability for journal-recommender in the archived review.
9 / 12
75%
Agent-Specific
Related legacy finding for journal-recommender: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
16 / 20
80%
Core Capability Total83 / 100
Medical TaskExecution Average: 94.6 / 100 — Assertions: 20/20 Passed
99
Canonical
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
4/4 ✓
95
Variant A
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
4/4 ✓
93
Edge
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
4/4 ✓
93
Variant B
Packaged executable path(s): scripts/journal_ranker.py
4/4 ✓
93
Stress
End-to-end case for Scope-focused workflow aligned to: Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Use when the user wants to find suitable journals for their research manuscript, especially when they provide a topic, abstract, and target Impact Factor
4/4 ✓
99
Canonical✅ Pass
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
For Recommend academic journals based on manuscript topic, abstract,..., the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.
Basic 38/40|Specialized 60/60|Total 99/100
✅A1The journal-recommender output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
95
Variant A✅ Pass
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
For Recommend academic journals based on manuscript topic, abstract,..., the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.
Basic 36/40|Specialized 59/60|Total 95/100
✅A1The journal-recommender output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
Edge✅ Pass
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
The archived run for Recommend academic journals based on manuscript topic, abstract,... confirmed the helper entrypoint and left the workflow in a stable state.
Basic 35/40|Specialized 58/60|Total 93/100
✅A1The journal-recommender output structure matches the documented deliverable
✅A2The script execution path completed successfully 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 B✅ Pass
Packaged executable path(s): scripts/journal_ranker.py
For Packaged executable path(s): scripts/journal_ranker.py, the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.
Basic 34/40|Specialized 59/60|Total 93/100
✅A1The journal-recommender output structure matches the documented deliverable
✅A2The script execution path completed successfully 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
Stress✅ Pass
End-to-end case for Scope-focused workflow aligned to: Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Use when the user wants to find suitable journals for their research manuscript, especially when they provide a topic, abstract, and target Impact Factor
The archived run for Recommend academic journals based on manuscript topic, abstract, and impact factor expectations confirmed the helper entrypoint and left the workflow in a stable state.
Basic 31/40|Specialized 60/60|Total 93/100
✅A1The journal-recommender output structure matches the documented deliverable
✅A2The script execution path completed successfully 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 Total94.6 / 100
Key Strengths
- Primary routing is Other with execution mode B
- Static quality score is 83/100 and dynamic average is 81.6/100
- Assertions and command execution outcomes are recorded per input for human review
- Execution verification summary: Script verification 1/1; adjustment=5. journal_ranker.py: OK