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Glama

Ny Dmv Offices

ny_dmv_offices
Read-onlyIdempotent

Find New York State DMV offices with street address, public phone number, weekday opening hours and coordinates. Covers all 175 county offices, district offices, mobile offices and traffic violations bureaus in the NYS DMV directory, so it answers "DMV office in Buffalo", "where is the DMV in ZIP 12207", "NYS DMV phone number in Albany", or "which New York DMV offices are mobile". For the sites where the road test itself is given use ny_dmv_road_test_sites.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipNoFive-digit ZIP code, e.g. "12207".
cityNoCity name, matched as a substring, e.g. "Buffalo", "Albany", "Brooklyn".
nameNoOffice-name substring, e.g. "Harlem", "Utica".
limitNoMax offices to return (default 50, max 200).
office_typeNoOne of "COUNTY OFFICE", "DISTRICT OFFICE", "MOBILE OFFICE", "TRAFFIC VIOLATIONS BUREAU", matched as a substring.

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and behavior. The description adds context about the data returned (address, phone, hours, coordinates) and coverage (175 offices), but does not elaborate beyond what annotations imply.

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?

Four sentences, front-loaded with purpose, includes examples and sibling reference. No redundant information.

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?

Given the tool has 5 optional parameters, no output schema, and annotations cover safety, the description adequately explains what the tool does, what data it retrieves, and when to use it. It covers common user intents and distinguishes from a sibling tool.

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 parameters are fully described. The description adds value by showing example queries and clarifying substring matching for city and office_type, but this is auxiliary. Baseline 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?

The description clearly states the tool finds NYS DMV offices with specific data fields (address, phone, hours, coordinates). It lists all covered office types and distinguishes from sibling ny_dmv_road_test_sites.

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?

The description provides explicit guidance on when to use this tool (general DMV offices) and when to use the alternative ny_dmv_road_test_sites. It also includes example queries to illustrate usage.

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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