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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description goes beyond them with two genuinely useful traits: the dataset is US-foods-only USDA data, and a null means unknown rather than zero. It does not mention result caps or what happens when a food is not found, leaving the remaining behavioral surface to the output schema.

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 tool's identity and scope, then the nutrient list, then triggers, then the exclusion — a sensible order with no filler. It is dense, packing four clauses into the first sentence, but every clause carries information.

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 and full annotations, the description covers what to query, what comes back, the data source and its US scope, and null semantics. An agent can call it correctly without inspecting anything else.

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 both params (query, limit) are fully documented there and the baseline is 3. The description notes the per-serving vs per-100 g basis and the protein-calorie share, but those are output semantics rather than added meaning for the inputs.

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 ("look up nutrition for a food") plus the backing source (USDA FoodData Central, US foods) and the exact nutrient set returned. It is unmistakably distinct from the logging and calculation siblings.

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 three concrete trigger phrasings ("how much protein is in cottage cheese", "compare tofu and chicken", "is a turkey sandwich high in protein") and one explicit exclusion ("Don't use to log food"). The exclusion, however, routes to malai_how_to_connect rather than naming malai_log_food, which is the actual sibling an agent would otherwise reach for.

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