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

Annotations already cover safety (readOnly, idempotent, closed-world), so the bar is lower, and the description nonetheless adds real semantics: food_pairing is null when the text names no dish, default_variant_id is null unless that bottle is purchasable, and on_request sizes cannot be ordered online. These null/edge-case semantics are the kind of detail that prevents misreading results; it stops short of describing price/availability freshness or caching behavior.

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 the operation and payload, then field-level clarifications. Dense but every clause carries information; the return-field enumeration is somewhat lengthy relative to an existing output schema, but nothing is filler.

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?

For a two-parameter read tool with a full output schema and rich annotations, the description is sufficient: it explains identifier forms, response language default, and the meaning of the ambiguous variant/availability fields. Only the discovery workflow (how to obtain a slug) is left unaddressed.

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%, so both the 'wine' identifier formats and the 'language' enum are already fully documented in the schema. The description repeats the identifier forms but adds no new meaning about them, so 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?

States a specific verb ('Returns') and resource ('one wine') plus the accepted identifiers, and enumerates the payload (description, grapes, taste notes, bottle variants, related wines). An agent can tell it apart from search_wines (list/query) without opening either 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?

The 'returns one wine' framing implies lookup-by-identity usage, but there is no explicit when-to-use guidance, no statement that search_wines should be used first to discover a slug/id, and no mention of alternatives. Usage is inferable rather than stated.

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