fooddata_search

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

Annotations already cover readOnly, idempotent, and non-destructive behavior, so the description need not repeat those. It adds useful behavioral context by stating that results include 'basic nutrient info' and by explaining the data types, which clarifies what kind of data can be filtered. This goes beyond the schema's enum values and adds practical value without contradicting annotations.

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 three sentences with no fluff. The first sentence states the core action, the second gives the return scope and coverage, and the third clarifies data types. Information is front-loaded and each sentence serves a distinct purpose. It is appropriately sized for a search tool.

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 search tool with 7 parameters (all schema-documented), no output schema, and strong annotations, the description is nearly complete. It explains the return type ('basic nutrient info') and the data type filtering options. It does not mention pagination or sorting, but these are covered in the schema. It also doesn't explicitly note that detailed nutrient info may require a follow-up call (e.g., fooddata_detail), but that is not essential for the search function itself.

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%, so the description does not need to repeat parameter definitions. However, it adds semantic meaning by explaining the four data types (Foundation, SR Legacy, Branded, Survey), which the schema lists only as enum values without individual descriptions. This enriches the agent's understanding of the dataType parameter. Other parameters are adequately described in the schema.

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 the tool's function: searching the USDA FoodData Central database by keyword and returning matching foods with basic nutrient info. It specifies the resource, action, and outcome, and the coverage statement (300K+ foods) adds specificity. It is distinct from sibling tools like fooddata_detail (which likely retrieves a specific food's details) and fooddata_list (which may list datasets), though it doesn't explicitly name them.

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 usage: use this when you have a keyword to search for foods. It provides context on data types and their meanings, which helps with filtering, but it does not explicitly state when to use this tool versus alternatives like fooddata_detail or fooddata_list. No exclusions or conditions are given, so the guidance is implied rather than explicit.

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