Voxcars (Portugal)

search_cars_by_description

Read-onlyIdempotent

Search Portugal listings by describing the car in plain language, matched against listing text by meaning rather than keywords. Use this for wants that are not filter fields — 'a family SUV good in the snow', 'a low-mileage hybrid for the city', 'a used 4x4 to restore'. Prefer search_cars for entirely structural queries (make/model/budget); use this when the request is descriptive. Combine both by passing structural filters here too — they act as hard constraints while the description only ranks. Results are ordered by relevance, so total is the number matching the structural filters, not the number that fit the description.

Input Schema

TableJSON Schema

Name	Required	Description
`fuel`	No	Fuel type. GASOLINE = gasolina, ELECTRIC = eléctrico, HYBRID = full hybrid, PLUG_IN_HYBRID = PHEV.
`make`	No	Make slug (e.g. toyota, bmw, volkswagen). Not free text — the slug is the same in every market.
`kmMax`	No	Maximum kilometres on the odometer.
`limit`	No	Maximum number of results (default 10, max 20).
`yearMin`	No	Minimum registration year.
`bodyType`	No	Body style. SEDAN = berlina, HATCHBACK = citadino, COMBI = carrinha, CABRIO = descapotável, MINIVAN = monovolume.
`priceMax`	No	Maximum price in the market currency. Listings with no published price are excluded by either bound.
`description`	Yes	What the user is looking for, in their own words. Full phrases work better than keywords. Pass the qualities here and the hard limits in the other arguments.

Output Schema

TableJSON Schema

Name	Required	Description
`cars`	Yes	Ordered by relevance to the description, most relevant first.
`shown`	Yes
`total`	Yes	Listings matching the structural filters. The description narrows the ranking, not this count.
`market`	Yes
`currency`	No

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the read-only/idempotent annotations, the description discloses important behavior: semantic ranking rather than keyword matching, structural filters acting as hard constraints, and the subtle `total` semantics (matching structural filters, not description relevance). This is exactly the kind of non-obvious behavioral context an agent needs.

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?

Five sentences, all dense with useful information: purpose, examples, sibling routing, combination strategy, and a critical caveat. The description front-loads the core purpose and immediately moves to actionable guidance without redundancy.

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?

For a semantic-search tool with a rich schema and output schema already present, the description covers everything essential: what it searches, when to use it vs the sibling, how filters interact, and how to interpret `total`. No critical gap remains for correct invocation.

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

Parameters4/5

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, but the description adds meaningful guidance for the `description` parameter (full phrases work better than keywords) and clarifies how structural parameters interact with the semantic search. This goes beyond simply repeating schema descriptions.

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 states a specific verb+resource ('Search Portugal listings') and the distinctive method ('matched against listing text by meaning rather than keywords'). It also differentiates this tool from search_cars by naming the alternative explicitly, so an agent can tell them apart immediately.

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?

It gives concrete when-to-use guidance with examples ('a family SUV good in the snow' vs structural queries), explicitly says to prefer search_cars for structural queries, and explains how to combine both tools by passing structural filters as hard constraints. This is clear routing with no inference required.

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

All Voxcars (Portugal) tools Inspect

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TDQS

A4.1/5.0

Disambiguation4/5

Most tools have clear boundaries: search_cars handles structural queries, search_cars_by_description handles descriptive queries, and find_similar_cars finds alternatives to a reference listing. There is some overlap between search_cars and find_similar_cars when finding comparable cars, but the descriptions clarify which to use for each intent.

Naming Consistency4/5

Names broadly follow a verb_noun pattern: search_cars, get_car_detail, get_price_stats, search_articles. The main inconsistency is mixing 'search' and 'find' verbs, and search_cars_by_description is longer and less symmetric than the others, but the pattern remains readable and predictable.

Tool Count5/5

Six tools is well-scoped for a car search and market-analysis server. Each tool serves a distinct user need from listing search to price statistics to editorial content, with no redundancy or bloat.

Completeness5/5

The tool surface covers the complete read-only lifecycle of a car-search domain: structural search, descriptive search, similar-car discovery, detail retrieval, market-level price stats, and supporting editorial articles. No obvious dead ends or missing operations within the stated purpose.

Resources

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