fooddata_detail

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

Annotations already signal readOnlyHint=true, and the description adds useful context about the return payload (calories, protein, vitamins, etc.) and that it is a detail lookup requiring an FDC ID. It does not describe exact response units or error behavior, but the annotation lowers that burden.

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 short sentences, each earning its place: what it does, what it returns, and how to get the required ID. Information is front-loaded and there is no 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 simple one-parameter read tool, the description covers purpose, return scope, and prerequisite workflow. The lack of an output schema is partially offset by enumerating the nutrient breakdown, but exact response formatting, units, and edge cases (e.g., unknown FDC ID) are not addressed. This is sufficiently complete for common usage but not exhaustive.

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%, and both the schema and description state that fdcId comes from fooddata_search results. The description reinforces the parameter's source but does not add meaningful semantics beyond what the schema already provides, so a 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 opens with a specific verb phrase ('Get complete nutritional details') and identifies the exact resource and identifier ('specific food by its FDC ID'). It explicitly distinguishes from search tools by naming fooddata_search and lists the nutrient categories returned, so purpose is unambiguous and distinct from 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?

'Use fooddata_search first to find FDC IDs' gives explicit sequential guidance and names the alternative/prerequisite tool. This makes the intended workflow and when-to-use clear, which is better than vague context.

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