toxicity-structure-alert
Analyze data with `toxicity-structure-alert` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
Veto GatesRequired pass for any deployment consideration
| 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 | The evaluated outputs stayed inside the Analyze data with toxicity-structure-alert 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 Capability88 / 100 — 8 Categories
Medical TaskExecution Average: 84.4 / 100 — Assertions: 17/20 Passed
Analyze data with toxicity-structure-alert using a reproducible... remained well-aligned with the documented contract in the preserved audit.
The Use this skill for data analysis tasks that require explicit... scenario completed within the documented Analyze data with toxicity-structure-alert using a reproducible workflow, explicit... boundary.
For Analyze data with toxicity-structure-alert using a reproducible..., the preserved evidence is lightweight but positive: the packaged validation command behaved as expected.
The Packaged executable path(s): scripts/main.py workflow remained defined, but this run surfaced a recoverable execution problem.
This stress case was mostly intact, but the archived review centered its concern on: The output stays within declared skill scope and target objective.
Key Strengths
- Primary routing is Data Analysis with execution mode B
- Static quality score is 88/100 and dynamic average is 84.4/100
- Assertions and command execution outcomes are recorded per input for human review