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

Annotations already mark the tool read-only, idempotent, and non-destructive. The description adds behavioral value by naming the external source and specifying the summary fields returned per trial, so the agent knows the shape of the result set without an output schema.

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: the first states what the tool searches and by which criteria, the second states what it returns. Every clause earns its place and the key info is front-loaded.

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 7-parameter read-only search tool with no required fields and no output schema, the description covers both query dimensions and return fields, which is sufficient to select and invoke it. It could add combination semantics (AND vs OR) or pagination details, but those are minor gaps given the schema annotations.

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% and each parameter already has a useful description. The tool description largely restates those dimensions rather than adding new meaning, so it earns the baseline for schema-covered parameters.

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 ('Search') with a clear resource (ClinicalTrials.gov) and enumerates search dimensions as well as the exact returned fields (NCT id, title, status, etc.). This clearly distinguishes it from the sibling trials_details, which presumably fetches detailed protocol data for a specific trial.

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 establishes a clear use case: querying clinical studies by condition, intervention, sponsor, status, and/or location. It does not explicitly name alternatives or state when not to use it, but the search-and-summary framing is enough to route an agent to this tool for filtering trials.

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