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list_brands

Resolve a vehicle brand name to its canonical record (used to filter type approvals).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoBrand name substring (e.g. 'KAMAZ').
pageNo1-based page index.
page_sizeNoRows per page (max 50).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It does not state that the tool performs a read-only list operation, returns multiple results with pagination, or uses substring matching. The schema covers parameter behavior, but the description lacks transparency about read-only nature, output format, and side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that immediately conveys the core purpose. It is concise with no unnecessary words, efficiently front-loading the verb and resource.

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?

For a simple list tool with full schema coverage and an output schema, the description is somewhat complete. However, it could be improved by explicitly stating that it returns a list of matching brands and how the result can be used for filtering type approvals. The current phrasing 'resolve to its canonical record' is ambiguous about multiple results.

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 baseline is 3. The description adds no additional meaning beyond the schema; it only repeats the context of 'brand name' already captured in parameter descriptions. Therefore, no extra value is provided.

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 resolves a vehicle brand name to its canonical record and specifies its use case (filtering type approvals). The verb 'resolve' and resource 'canonical record' are specific, and it distinguishes from sibling tools which focus on documents and certificates.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions the tool is used to filter type approvals, providing context. However, it does not explicitly state when to use or not use it, nor list alternatives. Since no sibling brand-resolving tool exists, the lack of exclusions is acceptable, but the guidance is implicit rather than explicit.

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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