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Food Product by Barcode

food.product.barcode
Read-onlyIdempotent

Look up food product details by entering a barcode (EAN/UPC). Retrieve name, brand, nutrition facts, Nutri-Score, NOVA group, and ingredients from a database of over 3 million products.

Instructions

Lookup food product by barcode (EAN/UPC) — name, brand, nutrition (calories, fat, carbs, protein per 100g), Nutri-Score, NOVA group, ingredients. 3M+ products (Open Food Facts)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
barcodeYesProduct barcode (EAN-13, UPC-A, etc.) e.g. "3017620422003" for Nutella

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds source (Open Food Facts) and data coverage (3M+ products), enriching transparency beyond annotations.

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?

Single sentence, no fluff, front-loaded with key verb and resource. Highly efficient.

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?

Even without output schema in view, the description lists all returned fields. With annotations and simple input, the description is complete for decision-making.

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?

Only one parameter (barcode) with full schema description. The tool description does not add new semantics beyond the schema, which is already clear. Baseline 3 is appropriate.

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?

Clearly states the verb (lookup), resource (food product by barcode), and the specific data returned (name, brand, nutrition, etc.). Distinguishes from sibling 'food.product.search' which likely searches by name.

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?

Implicitly clear: use when you have a barcode to look up food products. No explicit when-not or alternative named, but the context is obvious given the sibling tools and description.

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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