Agent skill · data analytics · google-deepmind
clinical-trials-database
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.
Why this skill is useful
Provides a wrapper script for querying ClinicalTrials.gov API with specific filters and pagination, which the AI wouldn't reliably generate on its own.
What it needs
Requires uv installed locally. About 6k tokens when loaded. Last updated 2026-07-07. 2,648 stars on the source repository.
What this skill does
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/clinicaltrialsdatabaseLICENSE.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/clinicaltrialsapi.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/studiesschema.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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills google-deepmind/clinical_trials_database