Agent skill · Data & Analytics

medical-data-api

Access FDA drug data and WHO global health statistics for research

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeNOASSERTION
Install
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill medical-data-api --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 9 KB
Bundled scripts: none
Path: skills/43-wentorai-research-plugins/skills/domains/biomedical/medical-data-api/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 3,244
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Medical Data API Guide (openFDA + WHO GHO) ## Overview This skill covers two major open medical data APIs for academic research: **openFDA** is the U.S. Food and Drug Administration's public API providing access to drug labeling (SPL), adverse event reports (FAERS), recalls, and NDC directory. The FAERS dataset contains over 722,000 reports for common drugs like aspirin, making it a primary phar

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About this skill
What does the medical-data-api skill do?

Access FDA drug data and WHO global health statistics for research

How do I install it?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill medical-data-api --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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