fda_approvals

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

With no annotations, the description carries the burden, and it does disclose useful traits: record ordering (newest first), inclusion of originals plus supplements, and sponsor alias resolution. It omits permission/auth notes, pagination/max_results truncation behavior, and what the result set looks like beyond what the output schema implies.

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 dense, front-loaded clauses with no filler; the source and scope lead, parameter hints follow. Slightly telegraphic but every fragment carries information.

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?

An output schema exists so return values needn't be explained, but with 0% schema coverage and six parameters, two parameters (max_results, application_number) are undocumented anywhere. For a read-only listing tool that is adequate but not complete.

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 0%, so the description must compensate, and it does for four of six parameters: sponsor (alias-resolved, with examples), since/until (status date, YYYY-MM-DD), and novel_only (original NME/BLA only). max_results and application_number are left undocumented, but the semantic value added is substantial.

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 resource (Drugs@FDA submissions/approvals), source (openFDA), and scope (ORIG + supplements) with ordering (newest first). This is enough to distinguish it from the change-feed siblings like fda_changes_since, though it never explicitly contrasts with them.

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?

Implied usage is clear — query approvals filtered by sponsor and date, or restrict to novel approvals. However, there is no explicit when-to-use versus alternatives such as fda_changes_since or sponsor_pipeline, so routing between siblings 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.