clinical-trials

SkillSearch

ClinicalTrials.gov API client and analysis toolkit. Search, filter, and download trial records. Analyze trial designs, endpoints, enrollment, sponsors, and results. Automate systematic trial discovery.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the clinical-trials skill

What this skill tells your AI

The instructions your AI receives, as published by mkurman/zorai in skills/scientific-skills/clinical-trials/SKILL.md and read by ahel’s review.

Overview

Search, filter, and download clinical trial records from ClinicalTrials.gov. Analyze trial designs, endpoints, enrollment, sponsors, and results. Automate systematic trial discovery.

Installation

uv pip install requests

Search Trials

import requests

params = {
    "query.term": "diabetes AND metformin AND phase 3",
    "pageSize": 25,
    "format": "json",
    "sort": "LastUpdateDate",
}

resp = requests.get("https://clinicaltrials.gov/api/v2/studies", params=params)
data = resp.json()

for study in data.get("studies", []):
    p = study["protocolSection"]
    nct = p["identificationModule"]["nctId"]
    title = p["identificationModule"]["briefTitle"]
    status = p["statusModule"].get("overallStatus", "Unknown")
    print(f"{nct}: {title[:60]} [{status}]")

Study Details

resp = requests.get("https://clinicaltrials.gov/api/v2/studies/NCT04251195")
study = resp.json()
design = study["protocolSection"]["designModule"]
print(f"Purpose: {design.get('primaryPurpose')}")

Workflow

  1. Search trials via ClinicalTrials.gov API v2
  2. Filter by condition, intervention, phase, status
  3. Download structured trial data (JSON)
  4. Extract PICO: Population, Intervention, Comparison, Outcome
  5. Analyze trial designs, enrollment, and results

Signals

GitHub stars
324
Forks
26
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
clinical-trials
Source
github.com/mkurman/zorai