Clinical Trials
Server Details
Clinical trial search and status from ClinicalTrials.gov
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.8/5 across 3 of 3 tools scored.
Each tool has a clear, distinct purpose: search_trials returns lists of trials, get_trial_details provides full details for a specific trial by ID, and get_trial_stats gives aggregated statistics. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern with snake_case: search_trials, get_trial_details, get_trial_stats. This pattern is predictable and easy to understand.
Three tools is a minimal but reasonable set for the domain, covering search, detail retrieval, and statistics. While more tools could be added (e.g., for filtering or comparison), the current count is not inappropriate.
The tool set covers the core operations for clinical trials: finding trials, viewing full details, and getting aggregate stats. Minor gaps exist (e.g., no tool to compare trials or access raw data), but the surface is sufficient for most common queries.
Available Tools
3 toolsget_trial_detailsAInspect
Get full details of a specific clinical trial by NCT ID. Returns title, summary, description, eligibility criteria, primary/secondary outcomes, sponsor, collaborators, locations, and results summary if available.
| Name | Required | Description | Default |
|---|---|---|---|
| nct_id | Yes | ClinicalTrials.gov NCT ID (e.g. "NCT03232697") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It lists returned data but does not disclose behavioral details like whether it calls an external API, if it's read-only, rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-structured sentence that front-loads the purpose and then enumerates the return data efficiently. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 param, no output schema, no annotations), the description covers the main functionality and return values. However, it lacks behavioral context (e.g., error handling, safety) and does not leverage the sibling context for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already documents the single parameter 'nct_id' with an example. The description adds meaning by specifying the tool returns 'full details' and listing what is included, enhancing understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves full details of a clinical trial by NCT ID, listing specific fields (title, summary, eligibility, outcomes, etc.). This distinguishes it from siblings like 'search_trials' and 'get_trial_stats'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied (when you have an NCT ID and need full details), but no explicit guidance on when to use this vs. siblings, or any prerequisites like requiring a prior search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trial_statsAInspect
Get clinical trial statistics and trends for a condition. Returns counts by status (recruiting, completed, etc.), by phase, and top sponsors. Useful for: "How many Alzheimer's trials are recruiting right now?"
| Name | Required | Description | Default |
|---|---|---|---|
| group_by | No | Grouping dimension: status (default), phase, or sponsor | status |
| condition | Yes | Disease or condition to analyze (e.g. "alzheimer", "lung cancer", "covid") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral aspects. It describes the output (counts) but does not disclose data freshness, permissions, rate limits, or whether the tool is idempotent/safe. This is minimal disclosure for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus an example, all front-loaded. Every sentence adds essential information: what it does, what it returns, and a concrete use case. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description explains the return content (counts by status, phase, sponsors). It does not specify format or limits, but the core information is sufficient for an agent to decide and partially anticipate output. Sibling tools cover other needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds value by explaining what each grouping yields (e.g., counts per status, per phase, top sponsors). This goes beyond the schema's basic value enumeration and default, helping the agent understand output variability.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves clinical trial statistics and trends, with specific outputs like counts by status, phase, and sponsors. The example query reinforces the purpose. It distinguishes itself from siblings (get_trial_details, search_trials) by focusing on aggregate data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage example showing when to use the tool, but does not explicitly state when not to use it or mention alternatives. The context of sibling tools implies differentiation, but the description itself lacks direct guidance on choosing this over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_trialsAInspect
Search clinical trials on ClinicalTrials.gov by condition, intervention, sponsor, status, or phase. Returns trial IDs, titles, status, phases, conditions, interventions, enrollment, and locations count.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results (max 20) | |
| phase | No | Trial phase: PHASE1, PHASE2, PHASE3, PHASE4 | |
| status | No | Trial status: RECRUITING, COMPLETED, ACTIVE_NOT_RECRUITING, NOT_YET_RECRUITING, TERMINATED | |
| sponsor | No | Sponsor name (e.g. "Pfizer", "NIH", "Mayo Clinic") | |
| condition | No | Disease or condition (e.g. "diabetes", "breast cancer", "alzheimer") | |
| intervention | No | Drug, device, or intervention (e.g. "metformin", "pembrolizumab") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses return fields but does not mention behavioral traits like rate limits, pagination, query complexity, or potential imprecision of search results. Could be more transparent about underlying source behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that efficiently capture the tool's purpose and return values. No filler or redundant information. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description provides return fields which compensates partially for missing output schema. However, it doesn't mention pagination, total count, sorting, or that no parameters are required. Adequate but could be more complete for a search tool with 6 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds overall context but does not provide additional meaning for individual parameters beyond what the schema's own descriptions already cover. No examples or constraints added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches clinical trials on ClinicalTrials.gov by multiple criteria, and lists the return fields. This distinguishes it from siblings like get_trial_details (which likely returns full details for one trial) and get_trial_stats (aggregated stats).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by listing searchable criteria, but does not explicitly state when to use this tool vs alternatives. No exclusion criteria or prerequisites are mentioned. The context is clear but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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