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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, covering the safety profile. The description adds nothing behavioral beyond that – no pagination/limit behavior, no rate-limit or result-count expectations for an open-world search.

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?

A single dense sentence with the resource and its three datasets front-loaded immediately after the verb. No filler and nothing to trim.

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?

Seven parameters with 14% schema coverage and no output schema demand more than one sentence. The description says nothing about result limits/pagination, date-range interpretation, or what a result record contains, leaving several parameters effectively undocumented.

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 only 14% (just the dataset enum), so the description compensates by naming the filter dimensions: drug, firm, application number, and date. That is real added meaning, but it still leaves the 'limit' parameter and the exact date-range semantics (since/until) unexplained.

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?

States a specific verb (Search) and resource (openFDA) and enumerates the three concrete datasets with their API paths and human-readable meanings. An agent can immediately see this is regulatory/FDA data, cleanly distinct from the clinical-trials siblings.

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?

Usage is only implied: the dataset-to-meaning mapping ('approvals', 'recalls', 'labeling') hints at which source to pick for which question, but there is no explicit when-to-use/when-not-to-use guidance or mention of the clinical-trials siblings as alternatives.

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