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

Annotations already indicate readOnly, idempotent, and non-destructive behavior, so the description doesn't need to repeat safety. It adds useful context about the source (FDA Data Dashboard) and the nature of the data (refusals, leading indicator), but does not disclose details like pagination, rate limits, or that results may be sorted by date. 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 a single, dense paragraph that front-loads the core purpose, then provides use-case context and search guidance. It is concise, with no filler, and each sentence adds value. Slightly long but acceptable; could be broken up for readability, but it's efficient.

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 read-only filterable dataset tool with no output schema, the description adequately explains what data is returned and how to query it. It doesn't specify the output format or sorting order, but given the simplicity of refusal records and the fact that no output schema exists, this is not a critical gap. The source attribution adds credibility. Overall, it is complete enough for an agent to use correctly.

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 description that includes examples and clarifications (e.g., firm is a substring, state accepts postal code or full name). The description's mention of 'product code' and 'date range' aligns with parameters but adds little beyond the schema. The _apiKey parameter is well documented in the schema, and the description doesn't need to explain credentials.

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 returns shipments refused entry by the FDA, specifies the key attributes (charges, product code, date), and identifies it as a leading indicator of supply risk. It distinguishes itself from sibling FDA tools (e.g., fda_483_citations, fda_inspections) by focusing on border refusals, so an agent can tell them apart.

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 lists search dimensions (firm, country, product, date range) and provides a clear use case ('leading indicator of supply risk'), which helps an agent decide when to use it. It does not name alternatives, but given the specific scope (border refusals) and the rich sibling set, the guidance is sufficient to avoid confusion with other FDA tools.

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