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upc_lookup

Read-onlyIdempotent

Checksum + Open Food Facts product hit — Validate UPC/EAN/GTIN checksum offline, then look up the barcode on Open Food Facts when it is a food/consumer item. Non-food codes often checksum-ok with no product match. Required input: code. Priced $0.01 per call over x402 on Base; send a prepaid x-credit-token header for unlimited calls, or get 1 free call/day per tool. No API key required.

Input Schema

NameRequiredDescriptionDefault
codeYesBarcode digits

Output Schema

NameRequiredDescriptionDefault
dataNoThe result payload. Shape is service-specific; every field is documented in the tool description.
serviceNoThe service id that answered.
checkedAtNoISO-8601 timestamp of when the underlying reads were taken.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, open-world, non-destructive, so the description is not obligated to repeat those. It adds genuinely useful operational context: offline-first checksum stage, the no-match outcome for non-food codes, x402 pricing at $0.01/call on Base, prepaid x-credit-token header, free daily call, and no API key requirement.

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?

Front-loads the core two-stage behavior before the pricing/payment detail, and every sentence is relevant. The payment mechanics sentence is dense but justifies its length given the x402 context.

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?

For a single-parameter tool with rich annotations and an output schema, the description covers the behavior model, partial-failure expectation, cost model, and auth requirements. Nothing an agent needs to invoke it correctly is missing.

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% ('Barcode digits' documents the single parameter), so the schema already carries parameter meaning. The description only restates 'Required input: code' plus the acceptable formats (UPC/EAN/GTIN) implied by the purpose, meeting the baseline without adding format syntax or validation rules.

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?

States a specific verb and resource ('Validate UPC/EAN/GTIN checksum', 'look up the barcode on Open Food Facts') and precisely delineates the two-phase behavior. The agent immediately knows this is a barcode validation + product-lookup tool, with no ambiguity against siblings like hs_code or bin_check.

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?

Explains when the tool applies (food/consumer barcodes) and gives the caveat that non-food codes often pass checksum with no product match. It doesn't name an alternative tool or an explicit when-not-to-use case, but the context is clear enough for correct selection.

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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