tooluniverse-drug-drug-interaction
Assess drug-drug interactions — CYP metabolic interactions (substrate/inhibitor/inducer), transporter (P-gp, BCRP, OATP) effects, pharmacodynamic synergy/antagonism, clinical significance scoring, and management recommendations. Use for polypharmacy review, prescribing decision support, and safety analysis when adding or switching drugs.
72
88%
Does it follow best practices?
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Adds up to 20 points to the overall score
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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
In ddi_pipeline.py, the pipeline ingests user-provided drug names (drug_a/drug_b) and passes them into ToolUniverse tool queries (DrugBank interactions, DrugBank pharmacology, DailyMed SPL search, PubMed search, FAERS counts), which causes the LLM runtime to read outsider-authored free text contained in those external database responses (e.g., label text, article abstracts/titles, interaction descriptions).
- Repository
- mims-harvard/ToolUniverse
- Commit
089eb8e
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.