Get organized list of available fields for customizing search results, grouped by category.
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Optional: specific category to return (identification, status, conditions, design, interventions, arms, outcomes, eligibility, locations, sponsors, descriptions, contacts, results) |
Changes observed during successful MCP inspections.
Input schema / $schemaAdded value: +"http://json-schema.org/draft-07/schema#"Input schema / properties / category / anyOfRemoved value: -[
- {
- "type": "string"
- },
- {
- "type": "null"
- }
-]Input schema / properties / category / defaultRemoved value: -nullInput schema / properties / category / typeAdded value: +"string"Output schema / (root)Previous value: -{
- "additionalProperties": true,
- "type": "object"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It adequately describes the output organization ('grouped by category'), but omits other behavioral traits like whether the data is static, response size, or caching characteristics. The mention of grouping provides some value beyond a generic description.
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 a single, efficient sentence that front-loads the action verb. Every phrase earns its place: 'organized list' implies structure, 'customizing search results' provides context, and 'grouped by category' describes output behavior. No redundant or filler text.
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 single-parameter tool without output schema, the description adequately explains what the tool returns (a categorized list of fields). However, without an output schema, it could benefit from describing the return format (e.g., whether it's a flat list or nested object) to complete the picture for the agent.
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%, establishing a baseline of 3. The description mentions 'grouped by category' which aligns with the category parameter, but does not add semantic meaning beyond what the schema already provides (including the explicit list of valid category values).
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 a specific verb ('Get') and resource ('available fields') and clarifies the context ('for customizing search results'). It implicitly distinguishes from sibling search tools by positioning itself as a metadata discovery utility rather than a search execution tool, though it could more explicitly contrast with get_field_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?
No guidance is provided on when to use this tool versus alternatives. Given the presence of numerous search siblings (search_trials_by_*, get_trial_details), the description should explicitly state when to call this field-discovery utility versus executing searches directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.