Drug Label, Recall & Adverse Event Check (openFDA)

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

With no annotations, the description carries the behavioral load and does well: it discloses the data sources (openFDA label/recall/FAERS), the causation caveat ("FAERS reports do not prove causation"), a liability disclaimer, and the payment model ($0.003/call, USDC on Base x402). It leaves the auth handshake flow (payment_signature omit-to-get-requirements) to the schema, which is acceptable.

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?

Front-loaded with purpose, then source detail, then caveats and cost. Sentence density is high but every sentence carries meaning; the parenthetical field list is long but justified because no output schema exists.

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?

With no output schema and no annotations, the description compensates by enumerating returned fields (ingredients, manufacturer, boxed warning, indications, warnings, interactions, pregnancy excerpts, recall reports, FAERS counts), stating caveats, and disclosing cost. Nothing an agent needs to call it correctly is missing.

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 the schema already documents both parameters with an example ("Advil or ibuprofen") and the payment_signature behavior. The description adds enumerable return fields but no additional parameter syntax or format detail, so the baseline 3 applies.

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 states a specific verb (check/look up) and resource (a medicine's US label warnings, recalls, adverse reactions), and names the backing source (openFDA). An agent knows exactly what this tool returns without opening the 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?

"Use when an agent needs citable FDA facts about a drug" gives clear positive usage context. There are no siblings and no explicit when-not conditions, so nothing beyond a clear trigger is required.

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