Clinicaltrials Get Field Values

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds behavioral context by noting that an empty list is rejected (not treated as 'every field'), which is a useful edge-case disclosure beyond the schema. It also implies the tool returns counts per value, which is behavioral information. No contradiction with 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?

The description is two sentences, front-loaded with the core purpose and immediately followed by a concrete use case. Every sentence earns its place: the first states what it does, the second explains when to use it and gives examples. No fluff or redundancy.

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 tool's simplicity (one parameter, no nested objects) and the presence of an output schema, the description is largely complete. It covers purpose, usage timing, and parameter semantics. The only minor gap is that it doesn't explicitly state the return format, but the output schema presumably covers that. For a read-only exploration tool, this is sufficient.

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 the schema already documents the 'fields' parameter well, including examples and the rejection of empty lists. The description adds value by explaining the purpose of the parameter (exploring filter options) and reinforcing the PascalCase requirement. Since coverage is high, a baseline of 3 applies, but the description's extra context about usage and the empty-list rejection pushes it to 4.

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's purpose: discovering valid values for ClinicalTrials.gov fields with study counts per value. It names specific example fields (OverallStatus, Phase, InterventionType, StudyType, LeadSponsorClass) and positions it as a pre-search exploration step, distinguishing it from sibling tools like clinicaltrials_get_field_definitions.

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 explicitly says to use this tool 'before building a search' to explore filter options, which provides clear context. It doesn't explicitly state when not to use it or name alternatives, but the sibling list and the reference to clinicaltrials_get_field_definitions for finding more field names give some guidance. A clear usage context is present, though exclusions are not explicit.

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