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search_deals

Search below-market used-car deals with filters (brand, model, price, year, mileage, fuel, body type, country, discount). Paginated; returns each deal with its listing, market stat, deal score and % below median.

Input Schema

NameRequiredDescriptionDefault
pageNo1-indexed page (default 1)
fuelsNoFuel types, e.g. ["diesel","benzín","elektro","hybrid"]
brandsNoBrand names, e.g. ["BMW","Audi"]
modelsNoModel names (fuzzy matched), e.g. ["A4","Octavia"]
sortByNoSort order (default deal_score)
sourceNoRestrict to source slugs, e.g. ["sauto","tipcars"]
yearMaxNo
yearMinNo
pageSizeNoResults per page (default 20, max 100)
priceMaxNoMaximum price in CZK
priceMinNoMinimum price in CZK
bodyTypesNoe.g. ["kombi","suv","sedan"]
countriesNoMarkets to include (default CZ)
maxMileageNoMaximum mileage in km
minDiscountNoMinimum % below market median (e.g. 20)
priceDroppedNoOnly listings whose price recently dropped
vehicleTypesNoe.g. ["used","new","demo"]

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses pagination and the shape of each returned deal (listing, market stat, deal score, % below median), but says nothing about what defines 'below-market', permission/auth requirements, or result ordering semantics beyond what the schema covers.

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?

Two sentences, front-loaded with the core verb and scope, with the pagination/return contract second. The inline filter enumeration is dense and slightly redundant with the schema, but it aids fast scanning and nothing is padded.

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?

No output schema exists, and the description compensates by naming the returned fields per deal. For a 17-parameter, all-optional filter tool this is close to sufficient; only the meaning of 'deal score' and 'below median' and pagination totals are left unexplained.

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 coverage is 88%, so the schema already documents nearly every parameter including units (CZK, km) and examples. The description's parenthetical filter list mirrors the schema rather than adding interpretation, so baseline 3 is appropriate.

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?

States a specific verb+resource: search used-car deals filtered by market below-median pricing, with the filter dimensions enumerated. An agent immediately knows this is the browsable/filterable listing tool, though it does not explicitly distinguish itself from siblings like list_hot_deals or list_recently_reduced.

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

Usage Guidelines3/5

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

Usage is implied by 'Search below-market used-car deals with filters' and the paginated return, but there is no explicit when-to-use, when-not-to-use, or routing to alternatives such as get_deal (single record) or list_hot_deals (curated subset). The agent must infer the boundary from names 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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