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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful behavior beyond that: results carry strength, flavours and a fixmeadrinkapp.com page per drink, plus low/zero-proof alternatives sharing flavour or base spirit, and an audience restriction to legal drinking age. No auth or rate-limit detail, but none is plausible for a public read tool.

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?

Usage guidance is front-loaded before the description of output, which is the right ordering. The single opening sentence is long, packing two quoted example utterances into one clause, but every element still carries routing value and nothing is pure 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 an output schema, the description covers the trigger, the filter parameter, the shape of returned content and the audience constraint. There is no ambiguity an agent would need resolved before calling it.

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 schema already defines both parameters, including 'low_proof: True to suggest only low and zero-proof drinks'. The description's restatement of low_proof adds no syntax or semantics beyond that, and 'name' is only loosely characterized as the drink the user likes. 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 uses a specific verb+resource: 'Suggests cocktails similar to that one from the Garçon catalogue.' An agent can tell this is a similarity-recommendation tool rather than a recipe lookup or ingredient search. It stops short of explicitly naming the sibling tools it replaces, so it lands at 4 rather than 5.

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?

It states the triggering condition precisely ('when the user names a drink they like and wants something similar, a lighter or lower-alcohol option, or both') and reinforces it with two concrete example utterances. There is no explicit exclusion clause pointing to get_cocktail_recipe or find_cocktails_by_ingredients, which keeps it from a 5.

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