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food_search

Search for food products by name, brand, or UPC barcode. Returns nutrition, ingredients, allergens, REAL-TIME KROGER PRICING, aisle location, and data source origin. Aggregates USDA (3,500+ foods) + Open Food Facts (1,000+ products) + Kroger (6,300+ products with prices).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandNoFilter by brand name
limitNoMax results (default 20)
queryYesProduct name, brand, or UPC barcode to search for
sourceNoWhich data source to searchall
categoryNoFilter by food category

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are present, so the description must cover behavioral traits. It mentions real-time Kroger pricing and data source aggregation but does not disclose any limitations, rate limits, or side effects. It is a search tool and likely read-only, but that is not explicitly stated.

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?

The description is three sentences, front-loaded with the core purpose. It efficiently lists what is returned and the data sources without redundancy. Every sentence adds value.

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

Completeness4/5

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

Given no output schema, the description partially covers return values by listing nutrition, ingredients, etc. It omits details like pagination, error handling, or response format. For a search tool, it is fairly complete but could improve with more behavioral context.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description adds context about search types (name, brand, UPC) matching the query parameter, but does not provide additional semantics beyond the schema for other parameters. It does mention real-time pricing indirectly but not as parameter detail.

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 the tool searches for food products by name, brand, or UPC barcode, and lists the returned data (nutrition, ingredients, allergens, pricing, aisle location, data source origin). It distinguishes from siblings like food_compare or food_commodity_prices by specifying its broad search and aggregation capability.

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

Usage Guidelines3/5

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

The description implies usage for general product search but does not explicitly state when to use this tool vs alternatives, nor does it provide exclusions or prerequisites. Given the sibling list, it is the primary search tool, but guidance is absent.

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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