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

Beyond the read-only/idempotent annotations it discloses non-obvious behavior: rankings combine the saved profile with conversation preferences when the connection may read it, allergy/dislike hits are excluded with a stated reason, matching is on printed menu text only, and the call does not consume the recognition allowance. Those are exactly the trust caveats an agent needs before acting on the output.

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?

It is front-loaded with the 'Use this when' trigger and every sentence carries information; nothing is filler. It is dense — three long clauses in one paragraph — and the phrase 'recognition allowance' assumes product jargon the agent may not know.

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 an output schema present, return values need not be explained, and the 100%-documented schema covers parameter formats. The description supplies the missing conceptual layer (profile vs. passed preferences, exclusion logic, text-only matching); only the exclusion of a plain 'just list the menu' fallback leaves a small gap.

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 baseline is 3, but the description adds real meaning: preferences are used together with the saved profile, and allergies/dislikes act as hard exclusions rather than soft ranking signals — a semantic the schema does not convey. The useSavedProfile toggle and its interaction with passed preferences are left to the schema.

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 names a specific verb and resource — ranking a saved menu's dishes against a taste profile — and scopes it to the 'what should I order' situation. It is clearly distinguishable from siblings such as get_menu or get_taste_profile, which only retrieve raw data.

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 explicitly when to reach for it (user asks what to order and tastes, dislikes, allergies or diets matter) and what it will not do (does not decide diets; check picks yourself). It never names a sibling alternative such as get_menu for plain retrieval, so the boundary is implied rather than stated.

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