Data Analysis
code-refactor-for-reproducibility
Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications.
85100Total Score
Core Capability
82 / 100
Functional Suitability
11 / 12
Reliability
10 / 12
Performance & Context
8 / 8
Agent Usability
13 / 16
Human Usability
6 / 8
Security
9 / 12
Maintainability
9 / 12
Agent-Specific
16 / 20
Medical Task
18 / 20 Passed
100Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
4/4
92Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format
4/4
91Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
4/4
89Packaged executable path(s): scripts/main.py
4/4
63End-to-end case for Scope-focused workflow aligned to: Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
2/4
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 | No scientific-integrity problem was surfaced because the package did not claim more than the available records, article text, or script evidence supported. |
| Practice Boundaries | PASS | Practice boundaries held because the package remained focused on Use when refactoring research code for publication, adding documentation to existing... rather than overclaiming what the records supported. |
| Methodological Ground | PASS | Methodological grounding was preserved through the documented inputs, transformations, and expected artifacts. |
| Code Usability | PASS | Code usability passed because the package still exposed a reviewable execution surface for its documented workflow. |
Core Capability82 / 100 — 8 Categories
Functional Suitability
Related legacy finding for code-refactor-for-reproducibility: 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
The archived review left some headroom in how quickly an agent can lock onto the intended analysis path.
13 / 16
81%
Human Usability
The archived deduction in human usability traces back to: Stabilize executable path and fallback behavior. Some inputs only reached PARTIAL due to execution gaps or weak boundary handling
6 / 8
75%
Security
Security remained strong, though the archived review still left some room for clearer execution guardrails.
9 / 12
75%
Maintainability
The analysis package is maintainable overall, though the archived score suggests modest cleanup headroom.
9 / 12
75%
Agent-Specific
Agent specific was softened by the legacy issue 'Stabilize executable path and fallback behavior'. Some inputs only reached PARTIAL due to execution gaps or weak boundary handling
16 / 20
80%
Core Capability Total82 / 100
Medical TaskExecution Average: 87 / 100 — Assertions: 18/20 Passed
100
Canonical
Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
4/4 ✓
92
Variant A
Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format
4/4 ✓
91
Edge
Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
4/4 ✓
89
Variant B
Packaged executable path(s): scripts/main.py
4/4 ✓
63
Stress
End-to-end case for Scope-focused workflow aligned to: Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
2/4 ⚠
100
Canonical✅ Pass
Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
The Use when refactoring research code for publication, adding... scenario completed within the documented Use when refactoring research code for publication, adding documentation to existing... boundary.
Basic 40/40|Specialized 60/60|Total 100/100
✅A1The code-refactor-for-reproducibility output structure covers required deliverable blocks
✅A2Script execution path is available (command exit code is 0)
✅A3The output stays within declared skill scope and target objective
✅A4Required research safety/boundary guidance is present without overclaims
Pass rate: 4 / 4
92
Variant A✅ Pass
Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format
The archived evaluation treated Use this skill for data analysis tasks that require explicit... as a clean in-scope run.
Basic 36/40|Specialized 56/60|Total 92/100
✅A1The code-refactor-for-reproducibility output structure covers required deliverable blocks
✅A2Script execution path is available (command exit code is 0)
✅A3The output stays within declared skill scope and target objective
✅A4Required research safety/boundary guidance is present without overclaims
Pass rate: 4 / 4
91
Edge✅ Pass
Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
The archived run for Use when refactoring research code for publication, adding... confirmed the helper entrypoint and left the workflow in a stable state.
Basic 36/40|Specialized 55/60|Total 91/100
✅A1The code-refactor-for-reproducibility output structure covers required deliverable blocks
✅A2Script execution path is available (command exit code is 0)
✅A3The output stays within declared skill scope and target objective
✅A4Required research safety/boundary guidance is present without overclaims
Pass rate: 4 / 4
89
Variant B✅ Pass
Packaged executable path(s): scripts/main.py
Packaged executable path(s): scripts/main.py remained well-aligned with the documented contract in the preserved audit.
Basic 36/40|Specialized 53/60|Total 89/100
✅A1The code-refactor-for-reproducibility output structure covers required deliverable blocks
✅A2Script execution path is available (command exit code is 0)
✅A3The output stays within declared skill scope and target objective
✅A4Required research safety/boundary guidance is present without overclaims
Pass rate: 4 / 4
63
Stress⚠️ Warning
End-to-end case for Scope-focused workflow aligned to: Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications
The preserved weakness for End-to-end case for Scope-focused workflow aligned to: Use when refactoring research code for publication, adding documentation to existing analysis scripts, creating reproducible computational workflows, or preparing code for sharing with collaborators. Transforms research code into publication-ready, reproducible workflows. Adds documentation, implements error handling, creates environment specifications, and ensures computational reproducibility for scientific publications was concentrated in one point: The output stays within declared skill scope and target objective.
Basic 25/40|Specialized 38/60|Total 63/100
✅A1The code-refactor-for-reproducibility output structure covers required deliverable blocks
✅A2Script execution path is available (command exit code is 0)
❌A3The output stays within declared skill scope and target objective
❌A4Required research safety/boundary guidance is present without overclaims
Pass rate: 2 / 4
Medical Task Total87 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 82/100 and dynamic average is 87.0/100
- Assertions and command execution outcomes are recorded per input for human review