Other

adaptyv

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
99Cloud laboratory platform for automated protein testing and validation
4/4
95Cloud laboratory platform for automated protein testing and validation
4/4
93Cloud laboratory platform for automated protein testing and validation
4/4
93Packaged executable path(s): scripts/validate_skill.py
4/4
93End-to-end case for Scope-focused workflow aligned to: Cloud laboratory platform for automated protein testing and validation; use when you have designed protein sequences and need wet-lab experimental validation (e.g., binding, expression, thermostability, enzyme activity) and API-based submission/status/result retrieval
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
PASS

Core Capability83 / 100 — 8 Categories

Functional Suitability
Related legacy finding for adaptyv: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
11 / 12
92%
Reliability
Related legacy finding for adaptyv: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
10 / 12
83%
Performance & Context
Performance context reached full score in the archived evaluation.
8 / 8
100%
Agent Usability
A modest deduction remained in agent usability for adaptyv in the archived review.
13 / 16
81%
Human Usability
The legacy audit deducted points for adaptyv in human usability.
7 / 8
88%
Security
A modest deduction remained in security for adaptyv in the archived review.
9 / 12
75%
Maintainability
The legacy audit deducted points for adaptyv in maintainability.
9 / 12
75%
Agent-Specific
Related legacy finding for adaptyv: 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
Cloud laboratory platform for automated protein testing and validation
4/4 ✓
95
Variant A
Cloud laboratory platform for automated protein testing and validation
4/4 ✓
93
Edge
Cloud laboratory platform for automated protein testing and validation
4/4 ✓
93
Variant B
Packaged executable path(s): scripts/validate_skill.py
4/4 ✓
93
Stress
End-to-end case for Scope-focused workflow aligned to: Cloud laboratory platform for automated protein testing and validation; use when you have designed protein sequences and need wet-lab experimental validation (e.g., binding, expression, thermostability, enzyme activity) and API-based submission/status/result retrieval
4/4 ✓
99
Canonical✅ Pass
Cloud laboratory platform for automated protein testing and validation

The Cloud laboratory platform for automated protein testing and validation path verified the packaged helper command without exposing a deeper execution issue.

Basic 38/40|Specialized 60/60|Total 99/100
✅A1The adaptyv 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
Cloud laboratory platform for automated protein testing and validation

For Cloud laboratory platform for automated protein testing and validation, the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.

Basic 36/40|Specialized 59/60|Total 95/100
✅A1The adaptyv 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
Cloud laboratory platform for automated protein testing and validation

The archived run for Cloud laboratory platform for automated protein testing and validation confirmed the helper entrypoint and left the workflow in a stable state.

Basic 35/40|Specialized 58/60|Total 93/100
✅A1The adaptyv 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/validate_skill.py

For Packaged executable path(s): scripts/validate_skill.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 adaptyv 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: Cloud laboratory platform for automated protein testing and validation; use when you have designed protein sequences and need wet-lab experimental validation (e.g., binding, expression, thermostability, enzyme activity) and API-based submission/status/result retrieval

The Cloud laboratory platform for automated protein testing and validation path verified the packaged helper command without exposing a deeper execution issue.

Basic 31/40|Specialized 60/60|Total 93/100
✅A1The adaptyv 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. validate_skill.py: OK