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Ny Dmv Driving Schools

ny_dmv_driving_schools
Read-onlyIdempotent

Find driving schools licensed by the New York State DMV, with school name, street address, city, ZIP, phone number, DMV school number, coordinates, and which courses each school is licensed to teach (5-hour pre-licensing, auto, motorcycle, bus, truck, tractor-trailer). Covers 573 licensed schools statewide, answering "licensed driving schools in Brooklyn", "which New York driving schools teach the 5-hour pre-licensing course", "motorcycle driving school near Syracuse", or "CDL tractor-trailer schools in New York".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNoFive-digit ZIP code, e.g. "11201".
cityNoCity or town, matched as a substring, e.g. "Brooklyn", "Syracuse".
nameNoSchool-name substring, e.g. "Safety", "Ace".
limitNoMax schools to return (default 50, max 200).
courseNoCourse the school must be licensed for: "pre_licensing" (the 5-hour course), "auto", "motorcycle", "bus", "truck", "tractor_trailer".

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) are consistent; the description adds detail on scope (573 schools statewide) and expected behavior (returns licensed schools). No contradictions.

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 paragraph that front-loads the main purpose and lists fields. It is efficient but could be slightly shorter without losing key information.

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?

Despite no output schema, the description explains the return fields and provides multiple query examples. For a simple listing tool, this is adequate and sufficiently complete.

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 description coverage is 100%, so the baseline is 3. The description adds example usage and clarifies the 'course' parameter, but does not significantly exceed what the schema already provides.

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 the tool finds driving schools licensed by NY DMV, listing specific fields (name, address, courses) and providing concrete example queries. It distinguishes itself from sibling tools (e.g., offices, road test sites) by its unique scope.

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?

The description implies usage through examples (e.g., 'licensed driving schools in Brooklyn'), but does not explicitly state when to use this tool vs. alternatives or provide exclusions. Clear context but no direct guidance.

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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