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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description's job is to add substance — and it does: it discloses that historical baseline anomalies are returned even when the pipeline is ACCEPTED, and disclaims what the result does not certify (completeness, product safety, regulatory validity). It stops short of describing the response structure, which matters since there is no 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?

Three sentences, front-loaded with the trigger condition, then the routing rule, then the caveats. Every sentence carries distinct information; no filler or restatement of the title.

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 zero-argument, read-only status tool with no output schema, the description supplies the trigger, the routing alternative, the anomaly caveat and the scope disclaimers. An agent has everything needed to decide whether to call it and how to interpret a result.

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?

The tool takes zero parameters, so the baseline is 4 and there is nothing for the description to disambiguate. No parameter prose is needed and none is wasted.

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?

Names a specific operation on a specific resource: status/freshness of the NMPA UDI dataset, enumerating the exact facets covered (freshness, snapshot date, row count, readiness, source, quality). It explicitly contrasts itself with the concrete query siblings, so an agent can distinguish it without opening any schema.

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?

Gives an explicit trigger ('when the user asks about ... freshness, snapshot date, row count, readiness, source or quality status'), an explicit anti-trigger ('for a concrete product/company/UDI query call the matching query tool directly'), and even prioritization ('this status check is optional'). Nothing is left to inference.

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