Clinical trial search and status from ClinicalTrials.gov
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Average 4/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: searching for trials, getting detailed info on a specific trial, and obtaining statistics. No overlap in functionality.
All tool names follow a consistent verb_noun snake_case pattern: get_trial_details, get_trial_stats, search_trials.
Three tools is an appropriate scope for a clinical trials server, covering search, details, and statistics without being too few or too many.
The set covers the main operations: search, details, and statistics. However, some potential gaps exist, such as a tool to list all trials by sponsor or location, though search can approximate these.
get_trial_detailsAInspectGet 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") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return fields and mentions 'if available', which is good. However, it does not mention error handling, authentication needs, or rate limits, leaving gaps for a simple retrieval 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 concise with two sentences. The first sentence states the purpose directly, and the second enumerates return fields. No redundant or unnecessary information.
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 lists the return fields comprehensively. It is almost complete for a single-item retrieval tool, though it could mention that the NCT ID must be valid and what happens if not found.
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?
The input schema already describes the nct_id parameter with a type string and example, achieving 100% schema coverage. The description does not add any additional meaning or constraints beyond what the schema provides, so baseline score of 3 is appropriate.
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?
Description clearly states 'Get full details of a specific clinical trial by NCT ID', which is a specific verb-resource pair. It lists the types of details returned, distinguishing it from sibling tools like search_trials (searching) and get_trial_stats (statistics).
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 when an NCT ID is available. While it does not explicitly state when not to use or list alternative tools, the context of siblings (search_trials, get_trial_stats) provides implicit guidance. Clear context but no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_trial_statsAInspectGet 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") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explains the output (counts by status/phase/sponsor), but does not disclose whether it's a simple read operation, potential side effects, or error behavior (e.g., unknown condition). Adequate but not comprehensive.
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, front-loaded with action and output. Every sentence adds value with 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 no output schema, the description adequately explains what the tool returns. However, it could mention output limits or format (e.g., JSON structure) to be fully complete.
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 repeats the grouping options already in the schema without adding new semantic meaning or examples beyond the generic one.
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?
Clearly states it gets clinical trial statistics and trends for a condition, listing specific output dimensions (status, phase, sponsors). Distinct from siblings get_trial_details and search_trials, which focus on individual trials or lists.
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?
Provides an example query to illustrate use ('How many Alzheimer's trials are recruiting right now?'), but does not explicitly contrast with siblings or state when not to use this tool. Implicit guidance is strong but could be more explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_trialsAInspectSearch 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") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose pagination, rate limits, error handling, or behavior when no parameters or results. Only states output fields without behavioral specifics.
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, front-loaded with action and scope, efficient and clear.
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?
Covers basic purpose and return fields, but lacks details on pagination, default filters, sorting, and empty results behavior. No annotations to fill gaps.
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% with descriptions for each param. Description adds meaning by summarizing output fields (IDs, titles, etc.), which compensates for lack of output schema. Does not elaborate on format or constraints beyond 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?
Clearly states it searches clinical trials by multiple criteria and returns key fields. Differentiates from get_trial_details (single trial) and get_trial_stats (aggregates).
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?
Lists searchable dimensions (condition, intervention, etc.), implying usage context. Lacks explicit when-not or alternatives, but sibling differentiation is clear.
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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