search_drug_recalls

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

With no annotations, the description carries the full burden. It discloses the output structure (one entry per recall with date, product, reason, classification, status, firm), the ordering (most recent first), and the meaning of an empty result (no recalls found, not a failure). However, it does not mention potential limitations like partial matching or case sensitivity, which prevents a perfect score.

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 well-structured with a clear purpose statement, usage guidance, and a return description, using headings for Args and Returns. Every sentence adds value, though it is somewhat longer than strictly necessary; it remains efficient and 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?

Given the tool has an output schema, the description needn't detail return types, but it still describes the fields. It covers purpose, usage, parameters, and the empty-result case. It is complete enough for an agent to call correctly, though it could mention any error conditions or edge cases.

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 0%, so the description must compensate. It explains drug_name with examples and notes that both generic and brand names are matched, and it specifies max_results range and default. This adds significant value beyond the schema, though it could be slightly more explicit about optionality.

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 action ('Look up') and the resource ('FDA recall and enforcement reports for a drug'), and it explicitly differentiates from siblings by focusing on recalls. It also lists the specific return fields, making the tool's purpose unambiguous.

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?

It explicitly states when to use the tool ('Use this to answer whether a drug has been recalled and why') and provides an alternative ('Use normalize_drug_name first if the spelling is uncertain'). This gives clear guidance and names a sibling tool, leaving no ambiguity about selection.

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