tooluniverse-adverse-event-detection
Detect and analyze adverse drug event signals using FDA FAERS reports, drug labels, and disproportionality statistics (PRR, ROR, IC). Generates quantitative safety signal scores (0-100) with evidence grading. Use for post-market surveillance, pharmacovigilance, drug safety assessment, regulatory submissions, and detecting rare AE signals not visible in clinical trials.
70
85%
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Low
Low-risk findings worth noting
The canonical home for this skill is tooluniverse-adverse-event-detection in mims-harvard/ToolUniverse
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
Phase 1-2 ingests FAERS-derived adverse event reaction terms from the FAERS dataset via tools like `FAERS_count_reactions_by_drug_event` and `FAERS_calculate_disproportionality`, which are populated from outsider-authored reports (free-text originally submitted by third parties) that the workflow processes without first selecting a specific trusted item.
- Repository
- mims-harvard/ToolUniverse
- Commit
7fe234c
- Audited
- Security analysis
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