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theYahia

@metarebalance/dadata-mcp

clean_vehicle

Recognize car brand and model from a user-provided string, standardizing inputs like 'тойота камри' or 'BMW X5'.

Instructions

Recognize car brand and model from a string. Paid: 0.20 RUB/req.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vehicleYesVehicle description, e.g. 'тойота камри' or 'BMW X5'
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It merely states the functionality without clarifying behavior on no match, output format, rate limits, or any side effects. For a paid API call, more transparency is needed.

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 very concise (one sentence plus payment info) and front-loaded with the core function. Every element earns its place, though the payment info could be considered secondary.

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?

Given the simplicity of the tool (1 parameter, no output schema), the description is minimally adequate but lacks details on output format, error handling, or examples. It does not fully inform an agent about what to expect upon successful or failed recognition.

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 100% description coverage for the single parameter 'vehicle', including an example. The tool description does not add additional meaning beyond the schema, so baseline score of 3 is appropriate.

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's purpose: to recognize car brand and model from a string. The verb 'Recognize' and resource 'car brand and model' are specific, and it is distinguishable from sibling tools like 'clean_address' or 'suggest_car_brand'.

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 provides no guidance on when to use this tool over alternatives, nor does it mention any exclusions or prerequisites. The only extra detail is the cost (0.20 RUB/req), which is helpful but not about usage context.

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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