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CSOAI-ORG

fsa-food-safety-mcp

allergen_labelling_check

Check allergen labelling for compliance with EU Reg 1169/2011 and Natasha's Law. Get structured assessment, regulation references, and recommended actions.

Instructions

EU Reg 1169/2011 + Natasha's Law allergen disclosure

Args: query: Optional query parameter (regulation ref, identifier, or input data). api_key: Optional MEOK API key for Pro+ tier features.

Returns: JSON with structured assessment, regulation refs, and recommended actions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, so description carries full burden. It describes the return format (JSON with assessment, regulation refs, actions) and mentions optional parameters, but does not disclose whether the tool is read-only, destructive, or requires authentication (api_key is optional for Pro+ but not explained further). Lacks disclosure of side effects or limitations.

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 extremely concise: one line stating the purpose, then a formatted args list, and a returns line. Every sentence serves a purpose. Front-loaded with the main function.

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 the tool has an output schema (as per context signals), the description does not need to detail return values. It mentions the return format adequately. However, it lacks context on when to use this tool versus siblings, and does not explain the overall workflow or prerequisites. For a specific compliance check, it is fairly complete but missing usage guidance.

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

Parameters4/5

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

Schema coverage is 0% (parameters have only titles and defaults), so description must add meaning. It explains that 'query' takes a regulation ref, identifier, or input data, and 'api_key' is for Pro+ tier features. This adds value beyond the bare schema.

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 checks allergen labelling against EU Reg 1169/2011 and Natasha's Law, with a specific verb 'check' and resource 'allergen disclosure'. It distinguishes from sibling tools like search_regulation which likely searches general regulations, and traceability which is about supply chain tracking.

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 allergen labelling compliance but does not explicitly state when to use this tool versus alternatives. No when-not or alternative tool mentions, leaving the agent to infer usage context from the purpose alone.

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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