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ביטוחון: Israeli car data and car-insurance facts

Open recall check / בדיקת ריקול פתוח

check_open_recall
Read-onlyIdempotent

Use when the person asks whether their car has an open recall: checks the plate against the Ministry of Transport list of vehicles that have not completed a manufacturer recall, with what the recall is about and how it is fixed. בדיקה אם לרכב יש ריקול פתוח לפי מאגר משרד התחבורה, ומה עושים.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plateYesIsraeli licence plate, 7 or 8 digits; dashes/spaces allowed (e.g. "12-345-67"). / מספר רישוי.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
errorNo
modelNo
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).
open_recallsNo
disclaimer_enNo
has_open_recallNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds useful domain context about the data source (Ministry of Transport list) and the nature of the result (what the recall is about and how it is fixed), which goes beyond 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the usage trigger, then the mechanism, then the return content. The bilingual duplication is functional for localization rather than wasteful, though it doubles length.

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?

With an output schema present, the description needn't explain return values, and annotations carry the safety profile. A single required param with full schema coverage means little is missing; only sibling differentiation is thin.

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% and the single 'plate' parameter is fully documented in the schema (length, format, examples). The description adds nothing about parameter format, so the baseline of 3 is appropriate.

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?

States a specific verb+resource ('checks the plate against the Ministry of Transport list of vehicles that have not completed a manufacturer recall') and clearly distinguishes itself from siblings like lookup_vehicle or theft_by_model. The recall-specific scope is unambiguous.

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

Usage Guidelines4/5

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

Opens with an explicit trigger: 'Use when the person asks whether their car has an open recall.' That gives clear context for invocation, but it does not name alternatives or state when NOT to use it (e.g. versus lookup_vehicle).

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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