List foods

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

The description adds value beyond the readOnlyHint annotation by explaining that an empty result is a valid state, not an error, and that many instances store ingredients as plain text. This helps the agent interpret results correctly.

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 description is just two sentences, front-loaded with the action and context. It packs important nuance (empty result) without fluff, making it highly efficient.

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?

Given the simple structure (no output schema, only pagination params), the description covers the key contextual points: the tool's purpose and the meaning of empty results. It could mention the response shape, but annotations and schema cover the rest reasonably.

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 75%, so the schema already documents most parameters. The description adds no parameter-level detail, and the search parameter lacks a description in the schema. Since coverage is not low, baseline 3 is appropriate.

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 clearly identifies the tool's function: listing structured foods, and specifies the domain (ingredient vocabulary). It distinguishes itself from sibling tools by explaining the semantic role and adding a key clarification about empty results.

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?

The description implies when to use this tool (to read the ingredient vocabulary) and gives contextual guidance about empty results, but does not explicitly contrast with alternatives like create_food or list_units. The readOnlyHint and wording convey a read operation sufficiently.

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