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ביטוחון: Israeli car data and car-insurance facts

Search models / חיפוש דגמים

search_models
Read-onlyIdempotent

Find car models by name in Hebrew or Latin ("קורולה", "corolla", "toyota corolla", "cx5"), optionally within a make or a vehicle class ("commercial" = vans, pickups and light trucks up to 3.5 t). With vehicle_class and no query it lists that class by cars on the road. Neutral order (match quality, then cars on the road). חיפוש דגם בעברית או באנגלית, אפשר לסנן רכב מסחרי.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeNoOptional filter. Make in Hebrew, English or slug, e.g. "קיה", "Kia", "kia". / יצרן.
limitNo
queryNoModel name, Hebrew or Latin. May be empty when vehicle_class is given.
vehicle_classNoOptional: private cars or commercial vehicles up to 3.5 t.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
queryNo
modelsNo
sourceNo
handoffNoHow the person can ask the operator for a quote (offer only when relevant; never automatic).
data_dateNoYYYY-MM-DD the data is correct to.
disclaimerYesHebrew disclaimer; relay it.
citation_urlNoPage to cite (link it when you use the facts).
disclaimer_enNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds real value beyond that with sorting behavior ('Neutral order (match quality, then cars on the road)') and the weight ceiling implied by the commercial class, which an agent cannot get from the annotations.

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?

Front-loaded with the core action and canonical examples, then the optional filters and ordering rule. The bilingual mirror sentence carries only the essential filter hint, so no sentence is wasted.

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?

An output schema exists, so return formatting need not be described, and the ordering rule plus enum semantics fill the behavioral gaps. The only shortfall is the undocumented 'limit' parameter and the absence of any sibling routing, both minor given the tool's simplicity.

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 coverage is 75% and 'limit' has no description anywhere. The description compensates by explaining the 'commercial' enum in plain terms ('vans, pickups and light trucks up to 3.5 t'), showing query format examples in both scripts, and clarifying that query may be empty when vehicle_class is supplied.

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?

The description gives a specific verb and resource ('Find car models by name') with concrete Hebrew/Latin examples and scope constraints on make and vehicle class. It is unambiguous about what the tool returns, though it never names or contrasts a sibling (e.g. list_makes, model_info, lookup_vehicle) to sharpen the boundary.

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?

It documents an accepted input combination ('With vehicle_class and no query it lists that class by cars on the road'), which is useful implied usage guidance. However, it never states when to prefer this tool over lookup_vehicle, model_info, or list_makes, so the routing decision is left to inference.

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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