Agent skill

Clinical Trials Database

by google-deepmind in google-deepmind/science-skills

Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.

Apache-2.0Auto-check passedResearch & Science

Install Clinical Trials Database

skills CLI
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install google-deepmind/science-skills clinical-trials-database --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/clinical_trials_database .claude/skills/clinical-trials-database && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
clinical-trials-database
GitHub stars
3.2k
Used in
3 other repos
Token cost
~3.2k tokens
SKILL.md length
1,003 words
Files
5 (incl. scripts, references)
Skills in repo
40
Repo updated
First seen
Licence
Apache-2.0

At a glance

Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.

  • Works in 2 steps: uv: Read the uv skill and follow its… → User Notification: If…
  • You want to search for trials by condition
  • SKILL.md covers Prerequisites, Overview, Core Rules and Context Efficiency Warning, plus 5 more sections
  • Runs Python scripts from its folder; calls uv

What it does

Clinical Trials Database is an agent skill from google-deepmind/science-skills. Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility/inclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/clinical_trials_api.md`, `references/studies_schema.md` and `scripts/clinical_trials_api.py`).

It sits in Research & Science, covering Clinical and healthcare research and Recruiting and HR. The repository describes itself as: GDM Science Skills to speed up agentic scientific workflows with better grounding and higher token efficiency. Integrate insights from AlphaGenome, AFDB, UniProt and 30+ other… The licence is Apache-2.0.

When your agent uses it

  • You want to search for trials by condition
  • Retrieve trial details by NCT ID
  • Check eligibility/inclusion criteria
  • Count trials across conditions

Example prompts

  • “/clinical-trials-database”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. uv: Read the uv skill and follow its Setup instructions to ensure
  2. User Notification: If .licenses/clinical_trials_database_LICENSE.txt

What it can do on your machine

Read from SKILL.md and the folder at commit 6883275. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • clinicaltrials.gov

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Clinical Trials Database loads about 3.2k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 88 tokens; SKILL.md has 1,003 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from google-deepmind/science-skills at commit 6883275, republished under its Apache-2.0 licence (© google-deepmind). 1,003 words, ~3,160 tokens.

Download SKILL.mdSave it as .claude/skills/clinical-trials-database/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
clinical-trials-database
description
Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility/inclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.

Clinical Trials Database

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. User Notification: If .licenses/clinical_trials_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://clinicaltrials.gov/, then (2) create the file recording the notification text and timestamp.

Overview

Access worldwide clinical trial data from ClinicalTrials.gov via the REST API v2. The CLI script at scripts/clinical_trials_api.py wraps the API with dedicated flags for common filters (phase, age group, status, intervention, sponsor, etc.) so you rarely need to construct raw queries.

Core Rules

  • Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
  • Always use --fields — trial JSON records can be very large; restrict to the data points you need.
  • Use --count-total first — check result volume before fetching all records.
  • Paginate large result sets — use --limit with --page-token to iterate.
  • Trust Search Filters: Do not manually re-filter results unless explicitly asked to verify detailed eligibility.
  • Notification: If this skill is used, ensure this is mentioned in the output.

Context Efficiency Warning

Trial JSON records can be very large. Always use the --fields parameter to restrict the response to only the data points you need. After writing to file, read only the fields you need rather than the entire file.

[!TIP] Use references/studies_schema.md to identify exact field paths for --fields.

Response Layout Summary

API responses contain a list of studies (usually in a studies[] array). Each study is split into protocolSection and optional resultsSection.

[!Tip] Use the shorthand aliases below with the --fields parameter to request specific data and keep responses small.

Top-Level Fields
  • totalCount — Total studies matching query (integer)
  • studies[] — Array of study objects
  • nextPageToken — cursor string for pagination
Common Study Fields (and shorthand alias)
  • Identification
    • protocolSection.identificationModule.nctId (NCTId) — Unique trial ID
    • protocolSection.identificationModule.briefTitle (BriefTitle) — Short title
  • Status
    • protocolSection.statusModule.overallStatus (OverallStatus) — Recruitment status
  • Description
    • protocolSection.descriptionModule.briefSummary (BriefSummary) — Short description
  • Arms & Interventions
    • protocolSection.armsInterventionsModule.interventions (ArmsInterventionsModule)
  • Eligibility
    • protocolSection.eligibilityModule.eligibilityCriteria (EligibilityCriteria) — Inclusion/Exclusion
    • protocolSection.eligibilityModule.stdAges (StdAge) — CHILD, ADULT, etc.

Consult references/studies_schema.md for full paths (Locations, Outcomes, Results) and common --fields recipes.

Commands

Search for studies

Use for: finding trials by disease, drug, phase, status, age group, or any combination of these filters.

bash
uv run scripts/clinical_trials_api.py search \
  --condition "<disease>" \
  --intervention "<drug_or_treatment>" \
  --status "<status>" \
  --phase "<phase>" \
  --age-group "<age_group>" \
  --study-type "<study_type>" \
  --sponsor "<sponsor_name>" \
  --has-results \
  --sort "<field>:<asc|desc>" \
  --fields "<fields>" \
  --limit <N> \
  --count-total \
  --page-token "<token>" \
  --output /tmp/search_results.json

All flags are optional and combine via AND logic.

Flag reference:

  • --condition — Disease or condition to search for (e.g. "cystic fibrosis").
  • --intervention — Drug, device, or treatment name (e.g. "pembrolizumab").
  • --status — Recruitment status filter. Values: RECRUITING, COMPLETED, NOT_YET_RECRUITING, ACTIVE_NOT_RECRUITING, ENROLLING_BY_INVITATION, TERMINATED, SUSPENDED, WITHDRAWN.
  • --phase — Trial phase filter. Values: PHASE1, PHASE2, PHASE3, PHASE4, EARLY_PHASE1, NA.
  • --age-group — Patient age group filter. Values: CHILD (0–17), ADULT (18–64), OLDER_ADULT (65+).
  • --study-type — Type of study. Values: INTERVENTIONAL, OBSERVATIONAL, EXPANDED_ACCESS.
  • --sponsor — Lead sponsor or institution name (e.g. "National Cancer Institute").
  • --has-results — Boolean flag (no value needed). When present, filters for studies that have results available on ClinicalTrials.gov.
  • --sort — Sort order as FieldName:asc or FieldName:desc. Common fields: LastUpdatePostDate, EnrollmentCount, StudyFirstPostDate, StartDate.
  • --fields — Comma-separated list of JSON field names to include in the response. Use this to keep responses small (e.g. "NCTId,BriefTitle,OverallStatus,Phase"). See references/studies_schema.md for available field paths.
  • --limit — Maximum number of studies to return per request (1–1000, default 10).
  • --count-total — Boolean flag (no value needed). When present, the response includes a totalCount field showing the total number of matching studies across all pages.
  • --page-token — An opaque cursor string used to fetch the next page of results. Obtain this value from the nextPageToken field in a previous search response. Do not construct this string yourself; always copy it verbatim from the API response. See the Pagination section below.
  • --advanced — Raw Essie filter expression for structured queries beyond the dedicated flags (e.g. "AREA[LocationCountry]United States"). Combined with other flags via AND. See references/clinical_trials_api.md for syntax.
  • --output — (Required) File path where the JSON response is written.

Example — actively recruiting Phase 3 pediatric cystic fibrosis trials:

bash
uv run scripts/clinical_trials_api.py search \
  --condition "cystic fibrosis" \
  --status RECRUITING \
  --phase PHASE3 \
  --age-group CHILD \
  --fields "NCTId,BriefTitle,OverallStatus,Phase" \
  --limit 10 \
  --output /tmp/cf_trials.json

Example — recruiting atezolizumab trials for esophageal cancer:

bash
uv run scripts/clinical_trials_api.py search \
  --condition "esophageal cancer" \
  --intervention "Atezolizumab" \
  --status RECRUITING \
  --fields "NCTId,BriefTitle,Phase" \
  --limit 10 \
  --output /tmp/atezolizumab_trials.json
Show full SKILL.md (353 more words)Show less
Retrieve a study by NCT ID

Use for: fetching full details of a specific trial when you already have the NCT identifier.

bash
uv run scripts/clinical_trials_api.py get-study \
  <nct_id> [--fields "<fields>"] \
  --output /tmp/study.json

Returns a useful default set of fields if --fields is omitted: NCTId,BriefTitle,OverallStatus,Phase,BriefSummary, ConditionsModule,ArmsInterventionsModule,EligibilityModule

Structure of the default response:

json
{
  "protocolSection": {
    "identificationModule": {
      "nctId": "NCT00000000",
      "briefTitle": "Study Title"
    },
    "statusModule": {
      "overallStatus": "RECRUITING"
    },
    "descriptionModule": {
      "briefSummary": "This study is about..."
    },
    "conditionsModule": {
      "conditions": [ "Condition Name" ]
    },
    "armsInterventionsModule": {
      "interventions": [ { "type": "DRUG", "name": "Drug Name" } ]
    },
    "eligibilityModule": {
      "eligibilityCriteria": "Inclusion:\n- ...",
      "stdAges": [ "ADULT" ]
    }
  }
}
Get eligibility / inclusion criteria

Use for: pulling inclusion/exclusion rules, age ranges, and sex requirements for patient-matching tasks.

bash
uv run scripts/clinical_trials_api.py \
  get-eligibility <nct_id> \
  --output /tmp/eligibility.json

Shortcut that returns title and the full eligibility module (inclusion/exclusion criteria, age range, sex).

Example — inclusion criteria for NCT04886804:

bash
uv run scripts/clinical_trials_api.py \
  get-eligibility NCT04886804 \
  --output /tmp/eligibility_NCT04886804.json
Count matching studies

Use for: exploring the trial landscape — checking how many trials exist for a condition, phase, or status before fetching full records.

bash
uv run scripts/clinical_trials_api.py count \
  --condition "<disease>" \
  [--status "<status>"] [--phase "<phase>"] ... \
  --output /tmp/count.json

Returns only the total count of clinical trials matching the search criteria without fetching study records. Accepts the same filter flags as search.

Search by location / geography

Use for: narrowing trials to a specific country, state, or city.

Use --advanced with AREA[LocationCountry] or AREA[LocationCity] to restrict results by geography:

bash
uv run scripts/clinical_trials_api.py search \
  --condition "cystic fibrosis" \
  --status RECRUITING \
  --advanced "AREA[LocationCity]New York" \
  --fields "NCTId,BriefTitle" \
  --limit 20 \
  --output /tmp/nyc_cf_trials.json
Search by sponsor / organization

Use for: identifying a sponsor's or institution's trial portfolio.

Use --sponsor to find trials run by a specific institution or company:

bash
uv run scripts/clinical_trials_api.py search \
  --sponsor "National Cancer Institute" \
  --fields "NCTId,BriefTitle,LeadSponsorName" \
  --limit 20 \
  --output /tmp/nci_trials.json

Use for: complex queries that layer multiple filters (condition and drug and phase and geography and sponsor, etc.).

All flags combine via AND, so you can layer conditions, interventions, status, phase, geography, and sponsor in a single query:

bash
uv run scripts/clinical_trials_api.py search \
  --condition "pancreatic cancer" \
  --intervention "immunotherapy" \
  --status RECRUITING \
  --phase PHASE3 \
  --advanced "AREA[LocationCountry]United States" \
  --fields "NCTId,BriefTitle,Phase,LeadSponsorName" \
  --limit 20 \
  --output /tmp/panc_trials.json
Raw API query (escape hatch)

Use for: uncommon endpoints or parameter combinations not covered by the dedicated flags.

bash
uv run scripts/clinical_trials_api.py raw-query \
  --endpoint <path> \
  --params '<json_dict>' \
  --output /tmp/raw_result.json

Pagination

When results exceed --limit, the response includes a nextPageToken. Pass it with --page-token to fetch the next page:

bash
uv run scripts/clinical_trials_api.py search \
  --condition "breast cancer" \
  --status RECRUITING \
  --limit 50 --count-total \
  --output /tmp/breast_cancer_p1.json

uv run scripts/clinical_trials_api.py search \
  --condition "breast cancer" \
  --status RECRUITING \
  --limit 50 --page-token "CAo=" \
  --output /tmp/breast_cancer_p2.json

Advanced Querying

For complex filtering beyond the dedicated flags, use --advanced with an Essie expression.

What is an Essie Expression? Essie is the search engine powering ClinicalTrials.gov. An Essie expression is a structured query that targets specific fields (e.g., country, phase) rather than doing general keyword searches.

  • AREA[Field]Value: Targets a specific field.
    • AREA[LocationCountry]United States
    • AREA[Phase]PHASE3
  • Boolean operators: Combine with AND, OR, NOT.
  • RANGE[min, max]: For numeric/date fields (e.g. RANGE[500, MAX]).

See references/clinical_trials_api.md for syntax and available fields.

It is combined with other flags via AND:

bash
uv run scripts/clinical_trials_api.py search \
  --condition "diabetes" \
  --advanced "AREA[LocationCountry]United States \
    AND AREA[EnrollmentCount]RANGE[500, MAX]" \
  --fields "NCTId,BriefTitle,EnrollmentCount" \
  --output /tmp/diabetes_us_large.json

References

  • API parameters, enum values, and Essie syntax: references/clinical_trials_api.md
  • JSON field paths and --fields recipes: references/studies_schema.md

© google-deepmind, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/clinical_trials_database of google-deepmind/science-skills.

  • SKILL.md
  • references/citation.bib
  • references/clinical_trials_api.md
  • references/studies_schema.md
  • scripts/clinical_trials_api.py

Open the folder on GitHubat commit 6883275

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in google-deepmind/science-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Clinical Trials Database next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Clinical Trials Database compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Clinical Trials Database this skillgoogle-deepmind/science-skills3.2k3 repos~3.2kAutomated safety check: PassApache-2.0
Inclusion Criteria Genaipoch/medical-research-skills2k—~3.3kAutomated safety check: PassMIT
Patient Recruitment Ad Genaipoch/medical-research-skills2k—~2.7kAutomated safety check: PassMIT
Pp Clinical Trialsmvanhorn/printing-press-library2.1k—~4.6kAutomated safety check: NotesApache-2.0
Clinicaltrials DBaipoch/medical-research-skills2k—~762Automated safety check: PassMIT
Treatment PlansK-Dense-AI/claude-scientific-writer2.4k1 repos~2.7kAutomated safety check: PassMIT

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Questions about Clinical Trials Database

What does Clinical Trials Database do?

Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills. Clinical Trials Database is an agent skill from google-deepmind/science-skills.gov via APIv2.

When should I use Clinical Trials Database?

Clinical Trials Database fits situations like: you want to search for trials by condition; retrieve trial details by NCT ID; check eligibility/inclusion criteria; count trials across conditions.

How do I install Clinical Trials Database in Claude Code?

Run `npx skills add google-deepmind/science-skills --skill clinical-trials-database -a claude-code`. Or copy the skill folder (skills/clinical_trials_database in google-deepmind/science-skills) into .claude/skills/clinical-trials-database in your project. Claude Code loads it when a task matches its description.

How do I install Clinical Trials Database in Codex?

Run `npx skills add google-deepmind/science-skills --skill clinical-trials-database -a codex`. Or copy the skill folder (skills/clinical_trials_database in google-deepmind/science-skills) into .agents/skills/clinical-trials-database in your project. Codex loads it when a task matches its description.

Can I use Clinical Trials Database in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google-deepmind/science-skills --skill clinical-trials-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clinical-trials-database, .gemini/skills/clinical-trials-database, .github/skills/clinical-trials-database and .opencode/skills/clinical-trials-database in your project.

What does Clinical Trials Database need to run?

Going by SKILL.md and its folder, Clinical Trials Database needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Clinical Trials Database access the network?

SKILL.md names 1 domain. As links in the text: clinicaltrials.gov. This is read from the text; nothing was executed.

Is Clinical Trials Database safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Clinical Trials Database use?

Clinical Trials Database is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Clinical Trials Database use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3k tokens, read only when the agent opens those files.

What are the alternatives to Clinical Trials Database?

Skills that share tags, products or a category with Clinical Trials Database: Inclusion Criteria Gen (aipoch/medical-research-skills, 2k stars), Patient Recruitment Ad Gen (aipoch/medical-research-skills, 2k stars), Pp Clinical Trials (mvanhorn/printing-press-library, 2.1k stars) and Clinicaltrials DB (aipoch/medical-research-skills, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Clinical Trials Database?

google-deepmind (a GitHub organization) maintains it in google-deepmind/science-skills, which has 3,220 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on September 15, 2026.

Source: google-deepmind/science-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.