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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety needs no restating. The description adds genuinely useful context the annotations do not carry: the data provenance (USDA FoodData Central), the per-100 g basis, and the presence of a plain-language summary and serving ideas in the payload. It stops short of describing result shape or how many profiles come back.

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?

Effectively one front-loaded sentence plus a short disclaimer; nothing is repeated and the nutrient list is informative about output. The enumeration is long but each item earns its place as a returned-field disclosure in the absence of an output schema.

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 return-value burden and does it reasonably well by naming the nutrients, the per-100 g unit, the source, and the accompanying summary and serving ideas. The gaps are behavioral rather than content-level: whether an unfiltered call returns everything, and how results are ordered or limited.

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%, and the schema already documents lang (with its six allowed values and English fallback) and query (partial name or id, with examples). The description adds nothing about either parameter, so the 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?

The description names the resource precisely (nutrition profiles for common fruit and vegetables FreshCheck knows) and enumerates the fields returned, so an agent knows exactly what data it gets. It does not explicitly say it returns a *list* keyed by the optional query, nor differentiate itself from freshcheck_list_articles / freshcheck_get_article, but the resource is unmistakable.

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?

There is no guidance on when to call this versus the article tools, nor on how the optional query and lang parameters should be used (all-produce listing vs. name lookup). The only usage signal is the scope caveat 'General information, not dietary advice', which constrains framing rather than invocation.

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