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driveate

TiresVote MCP

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by driveate

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tires_search
Read-onlyIdempotent

Search tire models by name to resolve a query into brand and product slugs, with season, region, rating, and pagination details.

Instructions

Search tire models by name.

Rows carry slug/display, brand slug, canonical_link, season/automobile-type slugs, year, status flags, counters, region slugs, rating (score = CoreScore and popularity as separate metrics) and has_modes (always {} here — this endpoint has no sizes filter).

Unlike tires_search_advanced this search applies no discontinued/RunFlat/OE defaults — discontinued models may appear in results (live-observed).

Follow next_page while has_more — never request a returned URL. If pagination_limited is true the upstream paging cap was reached; site_url (when present) is a citation link to the TiresVote site, not a fetch target. Per-row regions and rating.tags are capped (regions_more/tags_more count the rest; the model's canonical_link is the complete-record route). Responses cap at ~40 KB serialized (roughly 8–10k tokens) — lower per_page if a page overflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoAPI page number (>=1). Default 1.
queryYesFree-text model search, max 100 characters, e.g. 'pilot sport'. Use it to resolve a name into brand+product slugs.
per_pageNoResults per API page (1–20). Default 10.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive, yet the description goes well beyond them: pagination cap signaling (pagination_limited), what site_url and canonical_link actually are, capping of regions/rating.tags with *_more counters, has_modes always being empty, and the ~40 KB / 8-10k token response ceiling with remediation (lower per_page). This is unusually rich 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?

Front-loaded with the core purpose, then progressively adds pagination and cap semantics. It is dense and somewhat long, with several parenthetical asides, but nearly every sentence carries operational value; a small amount of row-field enumeration is arguably waste.

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?

Covers selection, pagination, response-size limits, and truncated-field recovery routes, which is the critical missing context for a search endpoint. Some row-shape detail is redundant given an output schema exists, but nothing important to correct invocation is omitted.

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 page/query/per_page are already documented in the schema; baseline is 3. The description adds indirect guidance ('lower per_page if a page overflows') and clarifies the paging mechanism, but adds no new syntax or constraints beyond the schema.

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?

States a specific verb+resource ('Search tire models by name') and immediately differentiates from the sibling tires_search_advanced by naming the exact behavioral difference (no discontinued/RunFlat/OE defaults). An agent can select this tool correctly without opening any schema.

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?

Provides an explicit contrast with an alternative tool and the condition (defaults applied vs. not), and gives concrete pagination rules (follow next_page while has_more; never request a returned URL). It stops short of stating plainly 'use this when you want broad recall including discontinued models', leaving the routing decision partly inferential.

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