tooluniverse-diagnostic-test-evaluation
Diagnostic test / biomarker accuracy — sensitivity, specificity, PPV, NPV, likelihood ratios, accuracy from a 2x2 table; ROC curve, AUC, and the optimal cutoff (Youden) for a continuous biomarker; and post-test probability via Bayes. Use when you have test results vs a gold standard (binary 2x2, or a continuous score + true labels) and need to judge how good the test is, pick a threshold, or compute the probability of disease given a result. Emphasizes the prevalence-dependence of PPV/NPV.
76
95%
Does it follow best practices?
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow for `ROC_analysis`/ROC evaluation only consumes user-supplied numeric arrays or a CSV file of (label, score) provided as an input argument, and the code itself does not fetch or ingest any outsider-authored free text from an external feed/queue at runtime.
- Repository
- mims-harvard/ToolUniverse
- Commit
089eb8e
- Audited
- Security analysis
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