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willhaben_search_cars

Search willhaben.at car listings with filters for make, model, price, year, mileage, fuel type, and transmission to find used or new cars.

Instructions

Search willhaben.at car listings (used cars, new cars). Filter by make, model, price, year, mileage, fuel type, and transmission.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeNoCar brand (e.g., 'BMW', 'Audi', 'Volkswagen'). Matched as a keyword unless a numeric willhaben make ID is given.
modelNoCar model (matched as a keyword)
locationNoLocation: Austrian state, city, place, or postal code (e.g. 'Wien', 'Graz', '6020'). Resolved to an area automatically.
price_fromNoMinimum price
price_toNoMaximum price
year_fromNoMinimum year of construction
year_toNoMaximum year of construction
mileage_fromNoMinimum mileage in km
mileage_toNoMaximum mileage in km
fuel_typeNoFuel type: 'petrol', 'diesel', 'electric', 'hybrid_petrol', 'hybrid_diesel'
transmissionNoTransmission: 'manual' or 'automatic'
conditionNoCondition: 'used', 'new', 'year_old'
sortNoSort: 'newest', 'nearby', 'price_asc', 'price_desc', 'mileage_asc', 'mileage_desc', 'year_desc', 'year_asc', 'relevance'
rowsNoResults per page (default: 30)
pageNoPage number (default: 1)
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden. It reveals the tool is for searching and filtering but omits traits like pagination (though present in schema), rate limits, authorization, or error behavior. It adds minimal context beyond the functional purpose.

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 that is concise and front-loaded with the verb 'Search'. It wastes no words, though it could be slightly more structured (e.g., bullet points) for a tool with 15 parameters. Still, it is efficient.

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?

Given 15 parameters and no output schema or annotations, the description is too minimal. It does not explain the platform (willhaben.at), result format, error handling, or ordering of filters. A more complete description would cover these aspects for an AI agent to use effectively.

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 100%, so the baseline is 3. The description lists some filters but does not add new meaning beyond what is already in the schema's parameter descriptions. It summarizes a subset but does not enhance understanding significantly.

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 'Search willhaben.at car listings' with a specific verb and resource. It lists key filters like make, model, price, year, mileage, fuel type, and transmission, and the name includes 'cars', distinguishing it from sibling search tools for jobs, real estate, etc.

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?

The description implies usage for car searches but does not explicitly state when to use this tool versus siblings like willhaben_search or willhaben_search_marketplace. No when-not-to-use or alternative guidance is provided, leaving ambiguity for an AI agent.

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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