Data Analysis
survival-curve-risk-table
Analyze data with `survival-curve-risk-table` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
88100Total Score
Core Capability
86 / 100
Functional Suitability
11 / 12
Reliability
10 / 12
Performance & Context
7 / 8
Agent Usability
14 / 16
Human Usability
7 / 8
Security
10 / 12
Maintainability
10 / 12
Agent-Specific
17 / 20
Medical Task
18 / 20 Passed
100Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
4/4
97Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format
4/4
92Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
4/4
91Packaged executable path(s): scripts/main.py
4/4
65End-to-end case for Scope-focused workflow aligned to: Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
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 | 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 Analyze data with survival-curve-risk-table using a reproducible workflow, explicit... and did not drift into unsupported interpretation beyond the available inputs. |
| Methodological Ground | PASS | The legacy review kept the package aligned with its named analysis library, data structure, or processing workflow. |
| Code Usability | PASS | Code usability passed because the package still exposed a reviewable execution surface for its documented workflow. |
Core Capability86 / 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
The archived deduction in reliability traces back to: Improve stress-case output rigor. Stress and boundary scenarios show weaker consistency
10 / 12
83%
Performance & Context
Performance-context scoring suggests the package could handle larger or denser runs a little more gracefully.
7 / 8
88%
Agent Usability
The packaged analysis path is understandable, though the archived score suggests slightly clearer routing would help.
14 / 16
88%
Human Usability
Related legacy finding for survival-curve-risk-table: Stabilize executable path and fallback behavior. Some inputs only reached PARTIAL due to execution gaps or weak boundary handling
7 / 8
88%
Security
The packaged workflow stayed safe overall, with only a small remaining deduction around boundary signaling.
10 / 12
83%
Maintainability
Maintainability stayed solid, with only limited room to simplify scripts, dependencies, or packaging structure.
10 / 12
83%
Agent-Specific
The archived deduction in agent specific traces back to: Stabilize executable path and fallback behavior. Some inputs only reached PARTIAL due to execution gaps or weak boundary handling
17 / 20
85%
Core Capability Total86 / 100
Medical TaskExecution Average: 89 / 100 — Assertions: 18/20 Passed
100
Canonical
Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
4/4 ✓
97
Variant A
Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format
4/4 ✓
92
Edge
Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
4/4 ✓
91
Variant B
Packaged executable path(s): scripts/main.py
4/4 ✓
65
Stress
End-to-end case for Scope-focused workflow aligned to: Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
2/4 ⚠
100
Canonical✅ Pass
Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
Analyze data with survival-curve-risk-table using a reproducible... remained well-aligned with the documented contract in the preserved audit.
Basic 40/40|Specialized 60/60|Total 100/100
✅A1The survival-curve-risk-table 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
97
Variant A✅ Pass
Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format
Use this skill for data analysis tasks that require explicit... remained well-aligned with the documented contract in the preserved audit.
Basic 40/40|Specialized 57/60|Total 97/100
✅A1The survival-curve-risk-table 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
Edge✅ Pass
Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
The archived evaluation treated Analyze data with survival-curve-risk-table using a reproducible... as a clean in-scope run.
Basic 36/40|Specialized 56/60|Total 92/100
✅A1The survival-curve-risk-table 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
Variant B✅ Pass
Packaged executable path(s): scripts/main.py
The Packaged executable path(s): scripts/main.py scenario completed within the documented Analyze data with survival-curve-risk-table using a reproducible workflow, explicit... boundary.
Basic 36/40|Specialized 55/60|Total 91/100
✅A1The survival-curve-risk-table 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
65
Stress⚠️ Warning
End-to-end case for Scope-focused workflow aligned to: Analyze data with survival-curve-risk-table using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation
The main issue in this stress run was: The output stays within declared skill scope and target objective.
Basic 25/40|Specialized 40/60|Total 65/100
✅A1The survival-curve-risk-table 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 Total89 / 100
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 86/100 and dynamic average is 89.0/100
- Assertions and command execution outcomes are recorded per input for human review