# Clinicaltrials > Search the ClinicalTrials.gov registry through its version 2 REST API for interventional and observational studies, their phases, enrolment, endpoints, sponsors, and posted results. Use this skill to survey who is developing what against an indication, date a competitor's programme, read primary and secondary outcome measures, find eligibility criteria, and distinguish a study that completed from… - **Type:** Skill - **Install:** `agentstack add skill-k-dense-ai-drug-discovery-agent-skills-clinicaltrials` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [K-Dense-AI](https://agentstack.voostack.com/s/k-dense-ai) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [K-Dense-AI](https://github.com/K-Dense-AI) - **Source:** https://github.com/K-Dense-AI/drug-discovery-agent-skills/tree/main/skills/clinicaltrials - **Website:** www.k-dense.ai ## Install ```sh agentstack add skill-k-dense-ai-drug-discovery-agent-skills-clinicaltrials ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # ClinicalTrials.gov The world's largest trial registry: roughly 560 000 studies, sponsor-submitted, going back to 2000. It answers the question that no bench assay can — *has anyone already tried this in people, and what happened to them when they did.* For a target or an indication it is the cheapest competitive and feasibility intelligence available. **Base URL:** `https://clinicaltrials.gov/api/v2` — REST, no key. **Docs:** [data-api](https://clinicaltrials.gov/data-api/api) · [search areas](https://clinicaltrials.gov/data-api/about-api/search-areas) **Checked against:** the live v2 API, August 2026. The classic API was retired in June 2024. Read [references/api-reference.md](references/api-reference.md) before writing a query by hand, [references/study-structure.md](references/study-structure.md) before reaching for a field, and [references/reading-a-registry.md](references/reading-a-registry.md) before drawing a conclusion from anything you find — **that one is judgement, not syntax.** ## The three scripts | Script | Answers | |---|---| | `ct_search.py` | What is registered against this condition or drug, and how much of it? | | `ct_study.py` | What exactly did this one study set out to do? | | `ct_landscape.py` | Who else is in this indication, and what stops trials here? | ## COMPLETED does not mean it worked This is the single thing to get right. `overallStatus: COMPLETED` means the study finished running. It says nothing about whether the intervention succeeded — a trial that comprehensively missed its primary endpoint completes normally. Three separate facts, routinely conflated: | | Means | |---|---| | `overallStatus: COMPLETED` | the study finished | | `hasResults: true` | results were posted to the registry | | whether the endpoint was met | **not recorded in the registry at all** | `hasResults` is a top-level sibling of `protocolSection`, not part of the status module, and it is the easiest useful field to miss. `ct_study.py show` prints a warning when a study completed without posting results. ## Searching ```bash python skills/clinicaltrials/scripts/ct_search.py search \ --condition "non-small cell lung cancer" --phase PHASE3 --limit 3 ``` ``` # 1019 studies match nct_id status phase enrollment sponsor start has_results NCT06357533 RECRUITING PHASE3 675 AstraZeneca 2024-04-11 false NCT05278052 RECRUITING PHASE3 190 Tata Memorial Hospital 2020-04-20 false NCT00268684 UNKNOWN PHASE3 381 Tel-Aviv Sourasky 2005-05 false ``` `UNKNOWN` is not an error: it is what the registry assigns when the sponsor has stopped verifying the record. On a 2005 study, read it as "probably abandoned". `count --by phase` and `count --by status` give the shape of a field without walking it. Note that **phase counts overlap** — a phase 2/3 study carries `["PHASE2","PHASE3"]` and is returned by a filter for either — so they do not sum to the total. ## One study in detail ```bash python skills/clinicaltrials/scripts/ct_study.py show NCT02142738 python skills/clinicaltrials/scripts/ct_study.py outcomes NCT02142738 ``` ``` nct_id NCT02142738 status COMPLETED phase PHASE3 allocation RANDOMIZED enrollment 305 (ACTUAL) sponsor Merck Sharp & Dohme LLC start 2014-08-25 has_results True ``` `outcomes` separates the primary endpoint — what the study was *powered for* — from the secondaries. A positive secondary in a study that missed its primary is hypothesis-generating, not evidence, and the registry will not make that distinction for you. `eligibility` splits the criteria blob back into inclusion and exclusion. There is no structured form in the registry; it is one newline-delimited string with headings inside it. ## Landscape and attrition ```bash python skills/clinicaltrials/scripts/ct_landscape.py attrition \ --condition "pancreatic cancer" --phase PHASE3 --limit 120 ``` ``` phase studies completed recruiting terminated withdrawn stopped_pct PHASE3 120 43 25 16 5 18.3 # 21 stated reasons for stopping - Preliminary data showed no survival benefit in the GV1001 group compared to gemcitabine. - recruitment prematurely stopped due to a lack of eligible patients. ``` **`whyStopped` is the richest field in the registry** and the reason `attrition` prints reasons rather than counting them. Those two examples are completely different facts: the first is a real negative result about the biology, often the only public record of it; the second says nothing about the drug and everything about whether you can recruit for your own trial. `sponsors` reports total enrolment and highest phase alongside the study count, because counting registrations measures activity, not investment — twenty investigator-initiated phase 1s are not two 800-patient phase 3s. ## Four ways this registry misleads quietly 1. **Nobody verifies any of it.** Sponsors submit and update at their own pace. A record is evidence of stated intent, not of what happened. 2. **Drug names are free text with no identifier.** `MK-3475`, `pembrolizumab`, and `Keytruda` do not group together. Resolve names with `chembl` first and search each synonym. 3. **Missing results usually mean nothing.** FDAAA compliance is well below 100% and does not reach phase 1, most non-US studies, or products never filed with the FDA. 4. **`ESTIMATED` enrolment is a plan.** Everything is estimated at registration; the gap between it and the final `ACTUAL` is itself a feasibility finding. ## When to stop using this API The registry has no aggregation endpoint, so every breakdown here walks studies one page at a time. For corpus-wide analysis, use the bulk download rather than the API. For European trials, many of which never appear here, use the EU CTR; the WHO ICTRP federates the national registries. ## Composing with the rest of the bundle - `open-targets` → here: is anyone already running trials against this target? - `chembl` → here: resolve a compound's synonyms before searching free-text intervention names. - `openfda` → alongside: the registry is what was attempted, openFDA is what was approved. - `depmap` → here: a genetic dependency, checked against whether the clinic has tried it. - `pkpd-translation` → after: a registered dose and schedule as a translation anchor. ## Reporting results honestly Give the query, the number of studies actually walked rather than the number matched, and the date. Say "N studies are registered", never "N studies show". Quote `whyStopped` verbatim instead of paraphrasing it into a cause. If asked whether a trial succeeded, say the registry does not record that. ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [K-Dense-AI](https://github.com/K-Dense-AI) - **Source:** [K-Dense-AI/drug-discovery-agent-skills](https://github.com/K-Dense-AI/drug-discovery-agent-skills) - **License:** MIT - **Homepage:** www.k-dense.ai Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-k-dense-ai-drug-discovery-agent-skills-clinicaltrials - Seller: https://agentstack.voostack.com/s/k-dense-ai - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.