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Aster National Insurance Group

Send a quote request to the agency

request_quote

Send a quote request to Aster National Insurance Group's licensed staff. Ask the person for their name, an email or phone, the line, the state and what they need covered, and get their OK before calling. A licensed agent replies; this is not a bound policy and no price is promised.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lineYesThe line of insurance.
nameYesThe person's name.
emailNo
phoneNo
stateYesTwo-letter US state.
consentYesTrue only if the person agreed to have the agency contact them.
detailsYesWhat they need covered, in their words: operations, vehicles, payroll, current policy, dates.
businessNoBusiness name, for commercial lines.

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 openWorldHint=true and destructiveHint=false, so the bar is lower, and the description adds meaningful context: a licensed agent replies, the request is not a bound policy, and no price is promised. It does not cover timing, rate limits, or error behavior, keeping it short of a 5.

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?

Three tight sentences, front-loaded with the action and recipient, then the required inputs, then the expectation-setting caveat. No filler.

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?

There is no output schema, so the description carries the return expectation and does so ('a licensed agent replies', 'not a bound policy'). For an 8-parameter open-world submission tool the essentials are covered, though it says nothing about turnaround or failure modes.

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?

With 75% schema coverage the baseline is 3, but the description goes further by framing how to elicit data conversationally and revealing the schema-level under-specification that an email OR phone is needed for contact, plus the consent gate before calling. That adds real meaning beyond the field descriptions.

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?

States a specific verb and resource ('Send a quote request to Aster National Insurance Group's licensed staff') and clarifies the recipient is a human agent. It implicitly separates itself from start_online_quote by being a request routed to staff rather than an online flow, but it does not name siblings to make the distinction explicit.

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?

Usage context is implied ('get their OK before calling') and a prerequisite (consent) is stated, but there is no explicit when-to-use-this-vs-start_online_quote or check_appetite guidance, nor any exclusions.

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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