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 real value beyond that: the content domain (the specific foods used per diet type) and hard scope boundaries (no medical diets, kidney disease, allergies, supplements), which tells the agent when to refuse.

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 usage trigger, followed by the output scope and exclusions. The three example queries are slightly redundant with each other but serve keyword-matching value; no filler sentences.

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 carries the burden of explaining what comes back, and it does so at a high level ('builds a sample day' from named foods). It is adequate for a two-parameter, read-only generator, though it could say more about the shape of the returned plan.

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%, with grams (20-250) and the diet enum fully documented in the schema. The description's food list loosely maps to the diet enum (veg/eggetarian/non_veg) but adds no format, unit, or constraint detail beyond the schema, 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 and resource: it 'builds a sample day' of Indian protein food from a named food list (dal, paneer, curd, soya, milk, eggs, chicken, fish). An agent knows exactly what it produces, but the description never names or contrasts with the sibling protein_per_day, so the two are not explicitly disambiguated.

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?

Gives explicit triggering contexts with three quoted user phrasings ('how to get 80 g protein a day vegetarian', etc.) plus explicit exclusions (medical diets, kidney disease, allergies, supplements). The one gap is that it does not point to protein_per_day as the alternative for non-sample or per-food calculations.

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