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Paw Multiverse pet food recalls

Search recalls by brand, product, country, reason or year

search_recalls

Keyword search over every recall held, without any AI writing. Returns up to 20 matching notices with their permanent URLs and key facts, newest and best matches first. Filter by country (us, gb, ca, fr) and year.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_recalls"
  }
}

Input Schema

NameRequiredDescriptionDefault
yearNoOptional: four-digit year of the notice.
queryNoBrand, company, product words, reason (for example salmonella), lot code or barcode.
countryNoOptional: us, gb, ca or fr.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the result cap of 20, the ordering ('newest and best matches first'), and that results include permanent URLs and key facts. It does not cover permissions, rate limits, or behavior when the search is broad.

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 three concise sentences and is front-loaded with the core purpose. The phrase 'without any AI writing' is slightly unusual but serves as useful differentiation.

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?

With no output schema, the description supplies important return information: result count, ranking order, and inclusion of URLs and key facts. It is mostly complete, though it does not explain pagination or what happens when no query is supplied even though all parameters are optional.

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 100%, so the parameters are already well documented. The description restates the country filter values and year filtering but adds little beyond the schema's own parameter descriptions.

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 states a specific verb and resource: keyword search over recall records. It implicitly contrasts with AI-answer tools by saying 'without any AI writing', but does not explicitly name sibling alternatives.

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?

Usage is implied: use this for keyword search rather than AI-generated answers. However, there is no explicit when-to-use guidance, no named alternatives, and no guidance on when to choose record lookup or register listing instead.

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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