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

Annotations already declare readOnly, idempotent, and closed-world behavior. The description adds genuine behavioral context beyond them: results are grouped by brand/ingredient and ranked 'in the order a person would pick, not packages', which tells the agent about result shape and ordering.

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?

Two tight sentences, front-loaded with the search behavior and then the result-ordering nuance. Every clause carries information; nothing is padding.

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, the description compensates by explaining the return grouping and ordering, and annotations cover the safety profile. It lacks only minor operational details such as what happens on no matches or how limit interacts with grouping, which is acceptable for a search tool.

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 query, limit, and as_of are already documented in the schema. The description's gloss on query (brand, ingredient or everyday name) is broadly consistent with the schema's example but adds little new syntax or constraint detail, so the baseline of 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?

States a specific verb (typeahead search) and resource (medications via brand/ingredient/everyday names), and explicitly scopes it against package-level results, which differentiates it from siblings like get_packages and lookup_ndc.

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 'typeahead' framing and 'what a person typed, at least 3 characters' semantics clearly convey the prefix-search use case, and 'not packages' steers the agent away from get_packages. However, no explicit when-not-relevant or named alternative (e.g. get_drug for a known exact drug) is given.

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