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nutrition_search

Search USDA FoodData Central by food name to get fdc_id, description, and macro summary per 100g. Returns ranked matches for use in other nutrition tools.

Instructions

Find foods in the USDA FoodData Central database by free-text name. Use this FIRST when the user mentions a food by name and you need its fdc_id for any of the other nutrition_* tools. Returns ranked matches with fdc_id, description, brand_owner, and a quick macro summary (calories/protein/carbs/fat per 100g). Charges $0.001 USDC per call.

Args: q: Free-text food name (e.g. "banana", "greek yogurt", "chicken breast"). limit: Max results to return, 1-50. Default 10. Use a small limit unless you need to browse.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so the description carries full burden. It discloses that results are 'ranked matches', lists returned fields, and mentions the cost ($0.001 per call). It does not mention any mutability, rate limits, or auth needs, which are less critical for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the main purpose in the first sentence. The description is brief (5 sentences) and well-structured, with clear separation of parameter guidance. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (a free-text search with one required parameter) and the presence of an output schema (mentioned but not shown), the description is complete. It covers purpose, usage flow, cost, and parameter details, leaving no obvious gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It explains 'q' as 'Free-text food name' with examples, and 'limit' with default value (10) and valid range (1-50), adding significant meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it finds foods in the USDA FoodData Central database by free-text name and explains its primary use case: getting fdc_id for other nutrition tools. It explicitly distinguishes from siblings by positioning it as the first step.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this FIRST when the user mentions a food by name', providing clear context for when to use it. It implies alternatives (other nutrition_* tools) but does not explicitly state when not to use this tool.

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

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