Inclusion Criteria Gen
aipoch/medical-research-skills
Generate and optimize clinical trial subject inclusion/exclusion criteria to balance scientific rigor with recruitment feasibility.
Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google-deepmind/science-skills clinical-trials-database --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "clinical-trials-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_database into .claude/skills/clinical-trials-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clinical-trials-database", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_databaseType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google-deepmind/science-skills clinical-trials-database --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/clinical_trials_database .agents/skills/clinical-trials-database && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "clinical-trials-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_database into .agents/skills/clinical-trials-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clinical-trials-database", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google-deepmind/science-skills clinical-trials-database --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/clinical_trials_database .cursor/skills/clinical-trials-database && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "clinical-trials-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_database into .cursor/skills/clinical-trials-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clinical-trials-database", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/google-deepmind/science-skills.git --path skills/clinical_trials_database--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google-deepmind/science-skills clinical-trials-database --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/clinical_trials_database .gemini/skills/clinical-trials-database && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "clinical-trials-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_database into .gemini/skills/clinical-trials-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clinical-trials-database", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install google-deepmind/science-skills clinical-trials-databaseInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/clinical_trials_database .github/skills/clinical-trials-database && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "clinical-trials-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_database into .github/skills/clinical-trials-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clinical-trials-database", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google-deepmind/science-skills --skill clinical-trials-database -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install google-deepmind/science-skills clinical-trials-database --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/clinical_trials_database .opencode/skills/clinical-trials-database && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "clinical-trials-database" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/clinical_trials_database into .opencode/skills/clinical-trials-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "clinical-trials-database", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
clinical-trials-databaseQuery ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.
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.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 6883275. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
uvFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
clinicaltrials.govFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
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.
.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.uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.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.
--fields — trial JSON records can be very large; restrict
to the data points you need.--count-total first — check result volume before fetching all
records.--limit with --page-token to
iterate.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.mdto identify exact field paths for--fields.
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
--fieldsparameter to request specific data and keep responses small.
totalCount — Total studies matching query (integer)studies[] — Array of study objectsnextPageToken — cursor string for paginationprotocolSection.identificationModule.nctId (NCTId) — Unique trial IDprotocolSection.identificationModule.briefTitle (BriefTitle) — Short
titleprotocolSection.statusModule.overallStatus (OverallStatus) —
Recruitment statusprotocolSection.descriptionModule.briefSummary (BriefSummary) —
Short descriptionprotocolSection.armsInterventionsModule.interventions
(ArmsInterventionsModule)protocolSection.eligibilityModule.eligibilityCriteria
(EligibilityCriteria) — Inclusion/ExclusionprotocolSection.eligibilityModule.stdAges (StdAge) — CHILD, ADULT,
etc.Consult references/studies_schema.md for full paths (Locations, Outcomes,
Results) and common --fields recipes.
Use for: finding trials by disease, drug, phase, status, age group, or any combination of these filters.
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.jsonAll 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:
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.jsonExample — recruiting atezolizumab trials for esophageal cancer:
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.jsonUse for: fetching full details of a specific trial when you already have the NCT identifier.
uv run scripts/clinical_trials_api.py get-study \
<nct_id> [--fields "<fields>"] \
--output /tmp/study.jsonReturns a useful default set of fields if --fields is omitted:
NCTId,BriefTitle,OverallStatus,Phase,BriefSummary,
ConditionsModule,ArmsInterventionsModule,EligibilityModule
Structure of the default response:
{
"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" ]
}
}
}Use for: pulling inclusion/exclusion rules, age ranges, and sex requirements for patient-matching tasks.
uv run scripts/clinical_trials_api.py \
get-eligibility <nct_id> \
--output /tmp/eligibility.jsonShortcut that returns title and the full eligibility module (inclusion/exclusion criteria, age range, sex).
Example — inclusion criteria for NCT04886804:
uv run scripts/clinical_trials_api.py \
get-eligibility NCT04886804 \
--output /tmp/eligibility_NCT04886804.jsonUse for: exploring the trial landscape — checking how many trials exist for a condition, phase, or status before fetching full records.
uv run scripts/clinical_trials_api.py count \
--condition "<disease>" \
[--status "<status>"] [--phase "<phase>"] ... \
--output /tmp/count.jsonReturns only the total count of clinical trials matching the search criteria
without fetching study records. Accepts the same filter flags as search.
Use for: narrowing trials to a specific country, state, or city.
Use --advanced with AREA[LocationCountry] or AREA[LocationCity] to
restrict results by geography:
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.jsonUse for: identifying a sponsor's or institution's trial portfolio.
Use --sponsor to find trials run by a specific institution or company:
uv run scripts/clinical_trials_api.py search \
--sponsor "National Cancer Institute" \
--fields "NCTId,BriefTitle,LeadSponsorName" \
--limit 20 \
--output /tmp/nci_trials.jsonUse 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:
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.jsonUse for: uncommon endpoints or parameter combinations not covered by the dedicated flags.
uv run scripts/clinical_trials_api.py raw-query \
--endpoint <path> \
--params '<json_dict>' \
--output /tmp/raw_result.jsonWhen results exceed --limit, the response includes a nextPageToken. Pass it
with --page-token to fetch the next page:
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.jsonFor 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 StatesAREA[Phase]PHASE3AND, 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:
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.jsonreferences/clinical_trials_api.md--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
SKILL.md and 4 other files (scripts, references) in skills/clinical_trials_database of google-deepmind/science-skills.
Open the folder on GitHubat commit 6883275
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.
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Clinical Trials Database this skillgoogle-deepmind/science-skills | 3.2k | 3 repos | ~3.2k | Automated safety check: Pass | Apache-2.0 | |
| Inclusion Criteria Genaipoch/medical-research-skills | 2k | — | ~3.3k | Automated safety check: Pass | MIT | |
| Patient Recruitment Ad Genaipoch/medical-research-skills | 2k | — | ~2.7k | Automated safety check: Pass | MIT | |
| Pp Clinical Trialsmvanhorn/printing-press-library | 2.1k | — | ~4.6k | Automated safety check: Notes | Apache-2.0 | |
| Clinicaltrials DBaipoch/medical-research-skills | 2k | — | ~762 | Automated safety check: Pass | MIT | |
| Treatment PlansK-Dense-AI/claude-scientific-writer | 2.4k | 1 repos | ~2.7k | Automated safety check: Pass | MIT |
aipoch/medical-research-skills
Generate and optimize clinical trial subject inclusion/exclusion criteria to balance scientific rigor with recruitment feasibility.
aipoch/medical-research-skills
Generate ethical, compliant, and patient-friendly recruitment advertisements for clinical trials.
mvanhorn/printing-press-library
A multi-source clinical-trials intelligence system — aggregates, normalizes, and analyzes trials across ClinicalTrials.gov, EU CTIS, and biomedical sources, with an offline SQLite engine no…
aipoch/medical-research-skills
Query the ClinicalTrials.gov API v2 to search for clinical trials, retrieve detailed study protocols, and analyze recruitment status; use when you need to find trials by condition/drug, export…
K-Dense-AI/claude-scientific-writer
Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals.
maziyarpanahi/openmed
Searches ClinicalTrials.gov for studies by condition, intervention, and recruitment status using the modern v2 REST API with cursor (pageToken) pagination.
google-deepmind/science-skills
A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.
google-deepmind/science-skills
A skill your agent uses when you want to retrieve quantitative RNA expression data and variant eQTL information from the GTEx (Genotype-Tissue Expression) Project across 54 non-diseased tissue sites.
google-deepmind/science-skills
A skill your agent uses when you want to retrieve semi-quantitative protein expression and spatial localisation data from the Human Protein Atlas (HPA).
google-deepmind/science-skills
Retrieve and analyze AlphaFold predicted structures for a protein.
google-deepmind/science-skills
Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.
google-deepmind/science-skills
Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures.
Categories
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.
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.
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.
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.
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.
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.
SKILL.md names 1 domain. As links in the text: clinicaltrials.gov. This is read from the text; nothing was executed.
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.
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.
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.
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.
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.