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Get product food quality

get_product_quality

Assess a product's quality by barcode using Open Food Facts without adding a meal to ReceiptCal.

Instructions

Resolve one barcode through ReceiptCal's bounded Open Food Facts quality assessment without logging a meal. ReceiptCal updates private rate-limit and cache state.

Input Schema

NameRequiredDescriptionDefault
barcodeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations are present but the description adds meaningful context they don't convey: the assessment is 'bounded', it hits an external source (Open Food Facts), and it 'updates private rate-limit and cache state'. That last point justifies the otherwise surprising readOnlyHint=false for a 'get' tool. It stops short of describing failure or rate-limit-exceeded behavior.

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?

Two tight sentences, front-loading the core action before the side-effect note. No filler; every clause carries information. It could arguably merge into one sentence, but the split is defensible.

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

Completeness3/5

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

With no output schema, the description should ideally sketch what a 'quality assessment' returns (score, grade, flags), which it does not. It does cover purpose, non-persistence, and side-effects, so it is adequate but leaves the return shape undocumented.

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 0%, so the burden shifts to the description, which only says 'one barcode' — conveying single (not batch) resolution but no format, length, or source-encoding guidance. The machine-readable pattern and length bounds live in the schema, so the description adds marginal value.

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

Purpose4/5

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

States a specific verb (resolve) plus resource (one barcode) and names the data source and scope ('bounded Open Food Facts quality assessment'). This differentiates it from the sibling resolve_barcode and the broader get_food_quality_overview, though it never names those siblings explicitly.

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 clause 'without logging a meal' implies a usage boundary against prepare_log_barcode / logging tools, which is helpful routing context. However, no alternative tool is named and no when-to-use condition is stated explicitly, so usage is only implied.

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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