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

No annotations are provided, so the description carries the full burden. It discloses important behavioral traits: the data source ('openFDA public-domain records'), pricing ('$0.05/row'), and entity resolution for applicant companies. It also lists the returned fields (brand, ingredient, dosage, approval dates). No contradictions or hidden side effects are noted.

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 four sentences, each adding value. The first sentence sets the context, the second lists search fields, the third describes the output, and the fourth provides source and pricing. It is front-loaded and efficient, though the sentence about returns could be slightly more concise.

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 10 parameters (none required) and no output schema, the description covers purpose, search criteria, return fields, and even pricing and data source. It is complete enough for an agent to understand when and how to use the tool, though a few more details on typical output structure would be beneficial.

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 100%, so the baseline is 3. The description adds minimal new meaning beyond the schema: it groups parameters by category (sponsor company, application type, etc.) and mentions 'suffix/punctuation-insensitive' for company, which is already in the schema. It does not significantly enhance understanding of the parameters.

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 opens with a targeted question ('Which companies just won an FDA drug approval or supplement?') and clearly identifies the resource as FDA drug approvals/supplements. It lists specific searchable fields (sponsor company, application type, route, etc.) and distinguishes itself from sibling tools like fda_clearances_devices and fda_recalls_search by focusing exclusively on drugs.

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?

The description explicitly states the searchable criteria and the intended use case ('a day-one commercial/partnership target list for pharma sellers and CROs'). While it does not directly state when not to use or name alternatives, the sibling tools are in different domains (devices, recalls, warning letters), so the usage context is implicitly clear.

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