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

The annotations already mark it read-only, but the description adds substantial behavioral context beyond that: substring matching, case/diacritic insensitivity, ranking order (exact > prefix > suffix > substring), result cap of 25, and the list of summary fields returned. This gives the agent a detailed model of what the tool does without any contradiction with annotations.

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 three sentences, each earning its place: core behavior with examples, return format with ranking, and usage guidance with alternatives. It is front-loaded with the most important information and contains zero 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 search tool with no output schema, the description fully covers the return value (up to 25 summary results with name, page URL, family, glassware), matching behavior, ranking, and a clear link to the next step (get_cocktail_recipe). Combined with annotations and schema, nothing essential is missing.

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?

Although the schema covers the query parameter well (name or part, examples, minLength), the description adds meaningful semantics: it clarifies that query is a single drink name, and describes the matching behavior (substring, case/diacritic-insensitive) and the ranking effect. This goes beyond the schema's description, enriching the parameter meaning significantly.

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 the tool searches the cocktail catalogue by name, with specific matching behavior (substring, case/diacritic-insensitive) and returns summary results with a defined ranking. It also distinguishes this from sibling tools by explicitly naming get_cocktail_recipe and find_cocktails_by_ingredient as alternatives, so purpose and differentiation are both clear.

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 explicitly states when to use this tool: when the user names a drink (even fuzzily) to confirm existence or disambiguate similar names. It also provides exclusions and alternatives: use get_cocktail_recipe once a single name is known, and use find_cocktails_by_ingredient for ingredient-based discovery. This is exemplary usage guidance.

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