LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill clinicaltrials-database --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/clinicaltrials-databaseContext preview
The summary Claude sees to decide when to auto-load this skill.
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
name: clinicaltrials-database
description: Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
license: Unknown
metadata:
skill-author: K-Dense Inc.ClinicalTrials.gov is a comprehensive registry of clinical studies conducted worldwide, maintained by the U.S. National Library of Medicine. Access API v2 to search for trials, retrieve detailed study information, filter by various criteria, and export data for analysis. The API is public (no authentication required) with rate limits of ~50 requests per minute, supporting JSON and CSV formats.
This skill should be used when working with clinical trial data in scenarios such as:
Search for clinical trials using the helper script:
cd scientific-databases/clinicaltrials-database/scripts python3 query_clinicaltrials.py
Or use Python directly with the `requests` library:
import requests
url = "https://clinicaltrials.gov/api/v2/studies"
params = {
"query.cond": "breast cancer",
"filter.overallStatus": "RECRUITING",
"pageSize": 10
}
response = requests.get(url, params=params)
data = response.json()
print(f"Found {data['totalCount']} trials")Get detailed information about a trial using its NCT ID:
import requests
nct_id = "NCT04852770"
url = f"https://clinicaltrials.gov/api/v2/studies/{nct_id}"
response = requests.get(url)
study = response.json()
# Access specific modules
title = study['protocolSection']['identificationModule']['briefTitle']
status = study['protocolSection']['statusModule']['overallStatus']Find trials studying specific medical conditions or diseases using the `query.cond` parameter.
**Example: Find recruiting diabetes trials**
from scripts.query_clinicaltrials import search_studies
results = search_studies(
condition="type 2 diabetes",
status="RECRUITING",
page_size=20,
sort="LastUpdatePostDate:desc"
)
print(f"Found {results['totalCount']} recruiting diabetes trials")
for study in results['studies']:
protocol = study['protocolSection']
nct_id = protocol['identificationModule']['nctId']
title = protocol['identificationModule']['briefTitle']
print(f"{nct_id}: {title}")**Common use cases:**
Search for trials testing specific interventions, drugs, devices, or procedures using the `query.intr` parameter.
**Example: Find Phase 3 trials testing Pembrolizumab**
from scripts.query_clinicaltrials import search_studies
results = search_studies(
intervention="Pembrolizumab",
status=["RECRUITING", "ACTIVE_NOT_RECRUITING"],
page_size=50
)
# Filter by phase in results
phase3_trials = [
study for study in results['studies']
if 'PHASE3' in study['protocolSection'].get('designModule', {}).get('phases', [])
]**Common use cases:**
Find trials in specific locations using the `query.locn` parameter.
**Example: Find cancer trials in New York**
from scripts.query_clinicaltrials import search_studies
results = search_studies(
condition="cancer",
location="New York",
status="RECRUITING",
page_size=100
)
# Extract location details
for study in results['studies']:
locations_module = study['protocolSection'].get('contactsLocationsModule', {})
locations = locations_module.get('locations', [])
for loc in locations:
if 'New York' in loc.get('city', ''):
print(f"{loc['facility']}: {loc['city']}, {loc.get('state', '')}")**Common use cases:**
Find trials conducted by specific organizations using the `query.spons` parameter.
**Example: Find trials sponsored by NCI**
from scripts.query_clinicaltrials import search_studies
results = search_studies(
sponsor="National Cancer Institute",
page_size=100
)
# Extract sponsor information
for study in results['studies']:
sponsor_module = study['protocolSection']['sponsorCollaboratorsModule']
lead_sponsor = sponsor_module['leadSponsor']['name']
collaborators = sponsor_module.get('collaborators', [])
print(f"Lead: {lead_sponsor}")
if collaborators:
print(f" Collaborators: {', '.join([c['name'] for c in collaborators])}")**Common use cases:**
Filter trials by recruitment or completion status using the `filter.overallStatus` parameter.
**Valid status values:**
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
Repo: foryourhealth111-pixel/Vibe-Skills
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding…
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection,…
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code,…
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the…
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex…