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yevhen-kalyna

autoria-mcp

raw_search

Run raw V1 search parameters directly to query the Ukrainian used-car market, bypassing automatic name resolution for advanced control.

Instructions

Run a raw /auto/search with V1 params (power users).

Bypasses the curated name-resolution of search_used_cars; you supply V1 wire params directly (e.g. marka_id[0], category_id, s_yers[0]). Cached briefly (volatile). By default returns the same compact shape as search_used_cars (ids + count); pass verbose=True for the full raw payload (~150 lines of echoed params/metadata).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYesRaw AUTO.RIA V1 search params, e.g. {'marka_id[0]': 9}.
verboseNoFalse (default) returns the compact {count, page, page_size, ids} shape (OfferOfTheDay filtered out). True returns the full raw API response — large; use only when you need the echoed params/metadata.
Behavior5/5

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

No annotations provided, so description carries full burden. It discloses caching is brief/volatile, default compact output filters OfferOfTheDay, and verbose returns full raw payload.

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?

Four sentences with no fluff. Front-loaded with purpose, then comparison, caching, and output behavior. Every sentence earns its place.

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

Completeness5/5

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

No output schema, but description explains return shapes (compact vs verbose) and mentions caching. Differentiates from sibling search_used_cars clearly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and description adds value by explaining bypassing of name-resolution, providing example params, and detailing verbose behavior.

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 it runs a raw /auto/search with V1 params for power users, bypassing curated name-resolution of search_used_cars. This distinguishes it from siblings like search_used_cars.

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

Usage Guidelines5/5

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

Explicitly says when to use (power users needing raw wire params) and when not to (as alternative to search_used_cars). Also mentions caching and default vs verbose output.

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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