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Glama

Georgia Insurance

Get indicative quotes

get_quotes
Read-only

Return indicative auto insurance prices from multiple carriers, where this entity is licensed to show them. Takes rating facts only — no name, phone, email, SSN or licence number is required for an indicative price. Where we are not licensed to show prices, the request is still registered and a quote_id returned so licensed agents can quote it. If facts are missing the server asks for exactly what it needs and nothing more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNoOptional; derived from the ZIP when absent
coverageYes
garaging_zipYesFive-digit ZIP where the vehicle is kept
vehicle_yearYes
date_of_birthYes
annual_mileageNo
violations_3yrNo
years_licensedNo
prior_continuousNo
vehicle_make_modelYes

Schema Changelog

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

  1. First observed

TDQS

A3.5/5.0
Behavior1/5

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

The annotations set readOnlyHint to true, yet the description states that an unlicensed request 'is still registered and a quote_id returned' — implying a side effect or resource creation. This contradicts the read-only annotation. The additional privacy and dynamic-request details are useful, but the contradiction is severe.

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, each earning its place: core purpose, data-minimization rule, unlicensed fallback, and dynamic missing-facts behavior. The main action is front-loaded with no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the main output, licensing constraints, fallback behavior, and privacy boundaries, and the schema defines required fields. However, the contradiction between the readOnlyHint annotation and the 'request is still registered' behavior leaves operational expectations ambiguous, and no explicit sibling routing is provided.

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 only 20%, so the description carries some burden. It adds useful meaning by stating the inputs are limited to rating facts and that missing facts are requested dynamically. However, it does not define the individual parameters such as prior_continuous, violations_3yr, or annual_mileage beyond their names.

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 uses a specific verb and resource: 'Return indicative auto insurance prices from multiple carriers.' It also clarifies the licensing scope and the rating-facts-only nature of the tool, which distinguishes it from non-quoting siblings like register_agency or request_agent_contact.

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 gives clear context for when the tool is appropriate: generating indicative quotes using only rating facts, plus a fallback behavior when the entity is not licensed. However, it does not explicitly name sibling alternatives or state when to prefer them, so it stops short of full routing 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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TDQS

A4/5.0
Disambiguation5/5

Each public- to-consumer and agency-facing tool serves a clearly separate step in the workflow: eligibility, quotes, consent, contact, registration, status, queue draining, and data purchase. There is no meaningful overlap between tool purposes.

Naming Consistency4/5

All tool names are snake_case and generally descriptive, but they mix action-oriented names like get_quotes and pull_requests with noun-style resource names like market_data and agency_status. This is a minor consistency deviation rather than a chaotic pattern.

Tool Count5/5

Eight tools cover the platform's distinct functional areas without bloat: consumer quote/contact flow, agency registration and queue management, and data market access. Each tool appears necessary and the total count is well-scoped for the server's purpose.

Completeness4/5

The core workflows are supported end to end: eligibility check leads to quotes, consent leads to agent contact, and agencies can register, check status, and pull routed records. The main gaps are minor administrative operations such as updating agency details or an explicit tool for revoking consent, although POST /forget is referenced.

Resources