Find a medication's generic group (FR)

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses that NDC returns an honest FR-only coverage note, that zero/multiple keys yield 400, malformed keys yield 400, and that well-formed-but-not-genericized returns found:false and is still billed. It also discloses pricing ($0.01/call, first daily call free) and no-account/no-key requirements, which are unusual behavioral traits an agent needs to know.

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 front-loaded with the core purpose in the first phrase, then flows through scope, coverage constraints, and pricing. It is two substantial sentences plus a docs link, all useful. Minor redundancy exists between the description and the input schema (both discuss the cis/name/dci/ndc keys and edge cases), making it slightly longer than strictly necessary, but every element earns its place.

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 no output schema, no annotations, and a single parameter, the description compensates well by specifying return fields (princeps, role, name, pack price, reimbursement rate), error codes (400 vs 200), billing behavior, coverage scope, and pricing. The main gap is that it doesn't describe the exact JSON response shape or pagination, but for a single-input lookup tool this is adequately 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 100% (1 parameter, fully described). The description adds significant meaning beyond the schema by explaining the four mutually-exclusive keys (cis, name, dci, ndc), the exactness of each, the French BDPM scope for names, and error/edge-case behavior (zero or several keys = 400, malformed = 400, well-formed not genericized = 200 found:false). This substantially enriches agent decision-making about parameter selection.

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 a specific verb+resource+scope: 'Find the French BDPM generic group of a medication before your agent substitutes or sources it.' It explicitly distinguishes from sibling medication tools (medication_availability, medication_report) by focusing on the generic group, princeps, role, price, and reimbursement rate, and by scoping to French BDPM.

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 clearly signals when to use it ('before your agent substitutes or sources it') and defines the French BDPM scope, explicitly stating a US NDC returns an FR-only coverage note. It does not explicitly name alternatives like medication_availability or medication_report, but the use-case framing ('before substituting or sourcing') provides clear context and exclusions (no US data).

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