fooddata_detail

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds useful behavioral context beyond that by specifying what the response contains: "full nutrient breakdown: calories, protein, fat, carbs, vitamins, minerals, amino acids." This helps set expectations for the no-output-schema case.

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?

Three concise sentences with no filler. The main purpose is front-loaded, the return scope is summarized, and the prerequisite is given last. Each sentence contributes useful 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 single-parameter, annotation-rich read tool, the description is complete: it explains what the tool does, what it returns, and how to obtain the required ID. With no output schema, the return-value summary is sufficient for an agent to invoke this correctly.

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 parameter description already says the ID comes from fooddata_search results. The tool description repeats this but adds no new semantic information about the fdcId parameter, so the baseline score 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 states a specific verb and resource: "Get complete nutritional details for a specific food by its FDC ID." It also names the return content (nutrients) and the prerequisite workflow (use fooddata_search first), which helps distinguish it from sibling search/list tools.

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 explicitly says "Use fooddata_search first to find FDC IDs," giving a clear prerequisite and workflow context. It doesn't enumerate alternatives or exclusions, but for a detail-by-ID tool the intended usage is clear.

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