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recall_check

Search local U.S. CPSC data for up to 10 recall notices that may match — check the notice. May not cover every batch or country; read the notice. No CPSC endorsement. (API Tool Calls, by Cowerx)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesProduct name, brand, model number or UPC.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations present, the description carries the full burden and does disclose real behavioral traits: results are capped at 10, coverage may be incomplete by batch or country, the data is a local copy, and there is no CPSC endorsement. It still omits whether the call is read-only and how fresh the local data is, but the coverage caveats are genuinely useful context an agent could not infer elsewhere.

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 definition is short and front-loads the core action and result limit before the caveats. The em-dash fragments ("may match — check the notice") read as slightly choppy but cost no real space.

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?

For a single-parameter search tool with no output schema, the description covers scope, result cap, and data-coverage limitations. Return-field detail is not required since there is no output schema, though noting that results are recall notices with dates/hazards would have helped the agent interpret them.

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% and the single parameter's accepted inputs (product name, brand, model number, UPC) are fully documented in the schema. The description adds no additional query semantics beyond what the schema provides, so the baseline of 3 applies.

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 names a specific verb ("Search") and resource ("local U.S. CPSC data ... recall notices") with an explicit result cap of 10, so an agent immediately knows this is a recall-lookup tool. No sibling differentiation is offered, but none of the sibling tools (barcode, SEO, transcript) are close enough to require it.

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 only usage directive is the repeated "read/check the notice," which tells the agent to verify returned data but not when to choose this tool over anything else or what preconditions apply. There is no statement of when the tool is inappropriate, so guidance is effectively absent.

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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