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search_zotts

Search vehicle conformity assessment conclusions by number, VIN, brand, or other parameters to retrieve compliance documents from the Russian/EAEU registry.

Instructions

Search ЗОТТС (vehicle conformity assessment conclusion).

Input Schema

TableJSON Schema

Name	Required	Description
`vin`	No	VIN substring.
`page`	No	1-based page index.
`type`	No	Type.
`brand`	No	Brand.
`issuer`	No	Certification body name — auto-resolved to id (or pass numeric id).
`number`	No	ЗОТТС number.
`category`	No	Vehicle category.
`eco_class`	No	Ecological class — '5' or name; auto-resolved to reference id.
`page_size`	No	Rows per page (max 50).
`axis_count`	No	Axle count (e.g. '2') or exact 'axes / wheels' (e.g. '2 / 4') — auto-resolved to reference id. A bare axle count may match several wheel configs; then candidates are returned to pick from.
`wheel_formula`	No	Wheel formula (e.g. '4x2'); auto-resolved to reference id.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.1Jul 12, 2026

TDQS

C2.7/5.0

Behavior1/5

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

No annotations exist, so the description carries full burden for behavioral disclosure. The description provides zero behavioral details—no mention of pagination, result structure, authentication, or side effects. This is a severe gap for a search tool.

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 a single, concise sentence that wastes no words. It is appropriately sized for the amount of information it conveys, though it could be moderately expanded without sacrificing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description is far from complete. It fails to explain the tool's scope, typical use cases, or how it differs from similar search tools (e.g., by entity type or constraints). Given the tool's complexity (11 parameters, many siblings), more context is necessary for effective selection.

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 schema already documents all 11 parameters. The tool description adds no parameter-specific information beyond what is in the schema. Baseline 3 is appropriate as the description does not degrade or enhance parameter understanding.

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 the verb 'Search' and the resource 'ЗОТТС (vehicle conformity assessment conclusion)', making the tool's function obvious. However, it does not distinguish this tool from many sibling search tools targeting similar entities (e.g., search_otts, search_zoets), which share the same verb and pattern.

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?

No guidance is provided on when to choose this tool over alternatives (e.g., search_otts, search_zoets). There are no descriptions of when to use, when not to use, or references to other tools for different purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.