Search clinical trials by medical condition(s). Returns trials matching any of the specified conditions.
| Name | Required | Description | Default |
|---|---|---|---|
| fields | No | Specific fields to return | |
| conditions | Yes | Medical conditions to search for | |
| max_studies | No | Maximum number of studies to return |
Changes observed during successful MCP inspections.
Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / properties / fields / anyOfRemoved value: -[
- {
- "items": {
- "type": "string"
- },
- "type": "array"
- },
- {
- "type": "null"
- }
-]Input schema / properties / fields / defaultRemoved value: -nullInput schema / properties / fields / itemsAdded value: +{
+ "type": "string"
+}Input schema / properties / fields / typeAdded value: +"array"Input schema / properties / max_studies / typePrevious value: -"integer"New value: +"number"Output schema / (root)Previous value: -{
- "additionalProperties": true,
- "type": "object"
-}New value: +nullDoes 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 crucial OR matching behavior ('matching any') not evident in the schema, and implies read-only operation via 'Search' and 'Returns'. However, it lacks explicit safety declarations, rate limits, or pagination behavior details that annotations would typically cover.
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, zero waste. First sentence establishes purpose and resource; second sentence discloses matching logic. Every word earns its place. Appropriately front-loaded with the core action.
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?
For a straightforward 3-parameter search tool with 100% schema coverage and no nested objects, the description is adequately complete. It specifies the search dimension and matching logic. While there is no output schema, the phrase 'Returns trials...' provides sufficient context for a list/search operation, though more detail on return structure would strengthen it.
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?
With 100% schema description coverage, the baseline is 3. The description adds value by explaining the relationship between multiple conditions ('matching any'), clarifying that the conditions parameter uses OR logic rather than AND. This semantic detail is not present in the schema's straightforward 'Medical conditions to search for' description.
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 uses specific verb 'Search' with resource 'clinical trials' and explicitly scopes to 'medical condition(s)'. It distinguishes from sibling tools (search_trials_by_acronym, search_trials_by_intervention, etc.) by specifying the search dimension. The addition of 'matching any of the specified conditions' clarifies the OR logic, further differentiating its behavior.
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 through the condition-specific focus and clarifies the OR matching logic ('matching any'), which guides how to use the conditions parameter. However, it lacks explicit when-to-use guidance or comparisons to alternatives (e.g., when to use search_trials_combined vs this tool).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.