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CSOAI-ORG

fsa-food-safety-mcp

recall_procedure_template

Generate structured food recall and withdrawal procedures with regulatory references and recommended actions based on your query.

Instructions

Food recall + withdrawal procedure generator

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 are provided, so the description must convey behavioral traits, but it only describes the input and output. It does not state whether the tool is read-only, destructive, or requires authentication (though it mentions an optional API key). The behavior of generating a procedure is implied, but side effects or access needs are not disclosed.

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 structured as a docstring with Args and Returns, making it easily scannable. The first sentence front-loads the purpose. It is relatively concise at 6 lines, though some redundancy exists (e.g., 'Optional query parameter' and 'Optional MEOK API key'). Overall, it earns its space.

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?

The description covers the basic purpose, parameters, and return format. Given that an output schema exists, it does not need to detail returns, but it still mentions them. However, it lacks context about default behavior when parameters are omitted, prerequisites, or integration with other tools. Completeness is adequate but not thorough.

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?

The input schema has 0% description coverage, so the description carries the burden. It explains 'query' as optional regulation ref, identifier, or input data, and 'api_key' as optional MEOK API key for Pro+ features. This adds modest meaning beyond the schema's defaults and types, but the explanations are generic and could be more detailed.

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?

The description clearly states 'Food recall + withdrawal procedure generator', which is a specific verb+resource. It provides a succinct summary of the tool's output, including structured assessment, regulation refs, and recommended actions. However, it could be more explicit about what distinguishes it from siblings like 'allergen_labelling_check' or 'haccp_audit', though the procedural generation is distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide guidance on when to use this tool versus siblings or alternatives. It gives parameter descriptions but no context on prerequisites, typical triggers (e.g., a recall event), or conditions under which this tool should be chosen. The absence of usage instructions leaves the agent without decision-making support.

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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