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

Annotations already declare a safe read (readOnly, idempotent, non-destructive), so the description is free to add domain behavior — condition names resolving despite physiological titles, the presence of evidence notes with their own rating, and the NICE-based caveat that diet is not a treatment for ADHD/autism. That is meaningful behavior beyond the annotations; only return/pagination detail is absent.

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 purpose and the accepted argument forms are front-loaded, and each sentence carries distinct information about inputs and evidence behavior. It is fairly dense in the middle, but no sentence is redundant 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 read-only lookup with full annotation coverage and no output schema, the description supplies enough: what it returns conceptually (nutrients, reasons, recipes), input resolution rules, and the caveat content. Return format detail is omitted, but that is a minor gap given the tool's simplicity.

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 the baseline is 3, but the description adds real semantics: condition names ("PCOS", "anaemia") resolve even though topic titles are physiological, and omitting the argument lists everything. This clarifies the topic parameter's accepted forms beyond the schema text.

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 states a specific resource (goal-oriented nutrition topics) and scope (nutrients, rationale, raw recipes), and frames the exact question it answers ("what should I eat for X"). It clearly distinguishes itself from narrow siblings like lookup_food or nutrient_ranking by covering the goal-level synthesis, though it never names a sibling explicitly.

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 tells the agent the trigger question ("what should I eat for X") and the argument forms that work (goal vs. named condition), plus the no-argument behavior. It gives clear context but no explicit exclusions or direct routing to alternatives such as search_recipes or nutrient_ranking.

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