clinicaltrialsgov-mcp-server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover read-only/idempotent aspects, so description appropriately focuses on adding hierarchical behavior context: explains it returns a 'field tree' with 'nesting structure' and supports progressive discovery (top-level overview vs drilling). Mentions output is used for filters, clarifying its role in the broader workflow. Does not contradict annotations.

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?

Three well-structured sentences: purpose (sentence 1), output structure (sentence 2), and usage workflow (sentence 3). Every sentence earns its place with zero redundancy. Front-loaded with action verb and resource.

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 2-parameter metadata tool with 100% schema coverage and existing output schema, the description is complete. It covers the data model context (ClinicalTrials.gov), return structure (tree, piece names, types), and consumption context (fields parameter, AREA[] filters). No gaps requiring additional explanation.

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 has 100% coverage establishing baseline 3. Description adds valuable workflow semantics: clarifies that path enables drill-down from 'top-level overview' to specific sections, and implies the hierarchical relationship between empty path and nested paths. This operational context exceeds what the schema provides.

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 explicitly states 'Get field definitions from the ClinicalTrials.gov study data model' with specific verb and resource. It distinguishes from siblings by focusing on metadata/schema (piece names, data types, nesting) rather than actual study records, and explicitly mentions these definitions are 'used in the fields parameter and AREA[] filters' linking to query tools.

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 explicit invocation pattern: 'Call with no path for a top-level overview, then drill into a section with the path parameter.' Implicitly indicates when to use by referencing 'fields parameter and AREA[] filters' (likely for search_studies), but lacks explicit 'when-not-to-use' or direct comparison to siblings like get_field_values vs get_field_definitions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.