tooluniverse-adverse-event-detection

Detect and analyze adverse drug event signals using FDA FAERS reports.

What this skill does for you

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.

Quoted from the skill description in the pinned source

Who made it

Publishermims-harvard

Repositorytooluniverse

Installs360as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the tooluniverse-adverse-event-detection skill from mims-harvard/tooluniverse.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/mims-harvard/tooluniverse
Pinned skill file: View source at revision
Revision: 40aabf8fbe7b153061f76eeb4be70415dc6f1126
Package hash: sha256:945eb9708c5e56e0ddca46908d566f6b8ccfd620d527ca3781669748af9cb324
Licence: Apache-2.0