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product-barcode

Full product truth from an EAN/UPC barcode: name, brand, quantity, categories, complete ingredients, allergens, additives, nutrition per 100g, Nutri-Score / NOVA / Eco-Score, packaging materials with recycling info, plus any linked CPSC or FDA recall for the same barcode. Covers food, general products and cosmetics (Open Food/Products/Beauty Facts). JSON response. [Paid: $0.02 USDC per call via x402 on Base; the calling client pays automatically.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eanYesEAN/UPC barcode, 8-14 digits

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

The description discloses the cost ($0.02 USDC per call) and response format (JSON), but lacks details on error handling, rate limits, authentication requirements, or behavior when barcode is not found. With no annotations, more behavioral context would be helpful.

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

Conciseness4/5

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

The description is a single, information-dense paragraph. It could benefit from bullet points for readability, but it is concise and front-loads the core purpose.

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?

For a lookup tool with no output schema or annotations, the description fairly comprehensively lists the data returned and notes coverage areas and cost. Minor gaps in error behavior and completeness of output naming.

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 coverage is 100% with a clear description of the 'ean' parameter. The description adds context on the return value but no additional constraints or formatting instructions for the parameter itself.

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 specifies the tool's function: retrieve comprehensive product information from an EAN/UPC barcode, including name, brand, ingredients, nutrition, scores, packaging, and recalls. It distinguishes itself from siblings like 'recall-check' by offering a broader data set.

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 any barcode lookup, but does not explicitly state when to use this tool versus alternatives like 'brand-visibility' or 'recall-check'. No exclusions or alternative recommendations are provided.

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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