clinicaltrials-database

clinicaltrials-database is a skill for Claude Code, Codex from beita6969/ScienceClaw. It costs 47 tokens per session (3,610 once invoked), scanned A, a copy of clinicaltrials-database, MIT.

A direct API tool for ClinicalTrials.gov, the U.S. National Library of Medicine's public registry of clinical studies. It searches trials and retrieves detailed records using filters such as condition, drug, location, status, phase, or trial ID.

In plain words
What is it for?
Use it to find recruiting studies, match patients with possible trials, research drugs or interventions, track study status, inspect eligibility, monitor sponsors, and export trial data.
Why use it?
It makes structured trial records available for repeatable searches and data analysis instead of requiring manual browsing of the registry.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python3 scripts/query_clinicaltrials.py.

Good fit Use it to find recruiting studies, match patients with possible trials, research drugs or interventions, track study status, inspect eligibility, monitor sponsors, and export trial data.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/beita6969/ScienceClaw
agentmods
npx agentmods add skills/beita6969/scienceclaw/clinicaltrials-database

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for clinicaltrials-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/beita6969/scienceclaw/clinicaltrials-database/github.svg)](https://agentmods.dev/skills/beita6969/scienceclaw/clinicaltrials-database)
Your own site
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/clinicaltrials-database"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/clinicaltrials-database/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for clinicaltrials-database

Your own site · 80×15
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/clinicaltrials-database"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/clinicaltrials-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,610 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 83% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.03610
Opus 5 $0.00023 $0.01805
Sonnet 5 $0.00009 $0.00722
Haiku 4.5 $0.00005 $0.00361

Measured 10d ago against content hash 4ec0470f79e2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

clinicaltrials-database scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

response = requests.get(url, params=params)
Origin

This is a copy

83% identical to clinicaltrials-database — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/clinicaltrials-database/SKILL.md · 507 lines

How it starts

The opening of the file, as written. The whole thing — 507 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ClinicalTrials.gov Database

Overview

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.

When to Use This Skill

This skill should be used when working with clinical trial data in scenarios such as:

  • Patient matching - Finding recruiting trials for specific conditions or patient populations
  • Research analysis - Analyzing clinical trial trends, outcomes, or study designs
  • Drug/intervention research - Identifying trials testing specific drugs or interventions
  • Geographic searches - Locating trials in specific locations or regions
  • Sponsor/organization tracking - Finding trials conducted by specific institutions
  • Data export - Extracting clinical trial data for further analysis or reporting
  • Trial monitoring - Tracking status updates or results for specific trials
  • Eligibility screening - Reviewing inclusion/exclusion criteria for trials

Quick Start

Basic Search Query

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")

Retrieve Specific Trial

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']

Read the full file on GitHub · 507 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 507 lines · 47 tokens per session scan A 4ec0470f79e2

Subscribe to this mod's changes

clinicaltrials-database is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 3,610 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 83% identical to clinicaltrials-database, differing in 6 lines, and is treated as a copy.

Related

Other skills, from other repositories

biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…

synthetic-sciences/openscience · 76 tokens

scanpy

Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use…

synthetic-sciences/openscience · 68 tokens

structure-prediction

Protein structure prediction from sequence. ESMFold-based, single GPU, no MSA needed. Predicts 3D structures with pLDDT confidence scores for drug discovery targets.

synthetic-sciences/openscience · 42 tokens

biomcp

Search and retrieve biomedical data - genes, variants, clinical trials, diagnostic tests, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. Use for gene function, variant pathogenicity, trials, diagnostics, drug safety, pathway context, disease workups…

genomoncology/biomcp · 70 tokens

biomcp-research

Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.

genomoncology/biomcp · 36 tokens

biological-expert

Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.

personamanagmentlayer/pcl · 59 tokens