hptsu-mcp

search_zoets

Search ЗОЕТС (vehicle technical expertise conclusion).

Input Schema

TableJSON Schema

Name	Required	Description
`vin`	No	VIN (10-17 chars).
`fuel`	No	Engine fuel type, one of: 'бензин', 'дизель', 'газ', 'электро', 'водород'.
`page`	No	1-based page index.
`type`	No	Type.
`year`	No	Manufacture year.
`brand`	No	Brand.
`motor`	No	Electric motor model.
`engine`	No	ICE engine model.
`issuer`	No	Testing lab name — auto-resolved to id (or pass numeric id).
`number`	No	ЗОЕТС number.
`date_to`	No	Issue date to (YYYY-MM-DD).
`category`	No	Vehicle category.
`comm_name`	No	Commercial name.
`date_from`	No	Issue date from (YYYY-MM-DD).
`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.
`powertrain`	No	Powertrain type: 'ice' (combustion), 'hybrid', 'electric'.
`motor_power`	No	Motor power (kW).
`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.

Changed2 schema fields changedJul 30, 2026

addedInput schema / properties / fuel

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Engine fuel type, one of: 'бензин', 'дизель', 'газ', 'электро', 'водород'.",
+  "title": "Fuel"
+}

addedInput schema / properties / powertrain

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Powertrain type: 'ice' (combustion), 'hybrid', 'electric'.",
+  "title": "Powertrain"
+}

First observedJul 12, 2026

TDQS

C2.6/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It merely says 'Search', implying a read operation, but offers no details about pagination, filtering behavior, or potential side effects. Given the 20 parameters, the description lacks essential behavioral context.

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 sentence with no wasted words. It conveys the core action and resource. While very brief, it is efficiently structured, though it could benefit from slight expansion.

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 an output schema existing, the description for a 20-parameter search tool is incomplete. It does not explain typical search strategies (e.g., when to use VIN vs. other filters) or how results are aggregated. The minimal description leaves significant gaps for effective tool invocation.

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 input schema fully documents all 20 parameters. The description adds no extra meaning beyond 'Search'. Baseline 3 is appropriate since the schema already handles param semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Search ЗОЕТС (vehicle technical expertise conclusion)', which identifies the resource as a vehicle technical expertise conclusion. However, the abbreviation 'ЗОЕТС' is not widely recognized, and the description does not differentiate it clearly from sibling tools like search_otts or search_certificates. The purpose is vague for an unfamiliar agent.

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 use this tool versus the many sibling search tools. There is no mention of typical use cases, contexts, or alternatives. The agent must infer usage from the tool name alone.

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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