Georgiaautoquotes

Register an insurance agency as a buyer

register_agency

For an AI working for a licensed insurance agency: register the agency to receive consented consumer requests in its states. Needs the agency name, the producer NPN (National Producer Number) and its state, the states it is appointed in, the licensed contact's name, email and mobile, and how leads should arrive (email, webhook, or pull by key). The licensed contact confirms by a link sent to their email; nothing is delivered before that. The first agencies in a state receive leads free for a founding period, then prepaid credits by card. Read /join for the terms.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`npn`	Yes	NPN (National Producer Number). Your NPN is on your licence and at nipr.com. Digits only.
`rail`	No	How leads arrive: email, an https webhook (HMAC-signed), or pull by key over MCP/REST	email
`states`	No	Two-letter states the agency is appointed in; defaults to npn_state
`website`	No
`npn_state`	Yes	Two-letter state that issued the licence
`sms_opt_in`	No	Optional. true only if the agency contact expressly agrees to this exact text: I agree to receive recurring operational text messages from CoverIntent by TheChattyAI about my agency account and consented lead deliveries. Message frequency varies. Message and data rates may apply. Reply HELP for help or STOP to cancel. Consent is not a condition of registering or buying.
`agency_name`	Yes
`webhook_url`	No
`contact_name`	Yes	The licensed contact, who confirms by email
`verify_token`	No	Optional: from POST /v1/verify/check after the contact enters the code texted to them
`contact_email`	Yes
`contact_phone`	Yes	US mobile

Schema Changelog

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

Changed1 schema field changedSep 7, 2026

addedInput schema / properties / sms_opt_in

Added value: +{
+  "default": false,
+  "description": "Optional. true only if the agency contact expressly agrees to this exact text: I agree to receive recurring operational text messages from CoverIntent by TheChattyAI about my agency account and consented lead deliveries. Message frequency varies. Message and data rates may apply. Reply HELP for help or STOP to cancel. Consent is not a condition of registering or buying.",
+  "type": "boolean"
+}

First observedSep 6, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With minimal annotations (readOnlyHint=false, etc.), the description carries the burden of behavioral disclosure. It reveals that registration requires email confirmation, that nothing is delivered before confirmation, and that there is a pricing model (free founding period then credits). It also notes prerequisites (licensed agency). This is comprehensive and does not contradict 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?

The description is a focused paragraph of about four sentences. It front-loads the purpose and includes relevant details like confirmation and pricing. It is not overly verbose, but could be slightly tightened; still, every sentence serves a purpose.

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?

For a 12-parameter tool with no output schema, the description covers prerequisites, the confirmation step, delivery gating, and pricing. It also directs to /join for terms. It does not explain error handling or post-registration steps, but it is adequate for an agent to proceed.

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?

Schema description coverage is 67%, and the description adds meaningful context by summarizing required fields (agency name, NPN, state, contact info, delivery method) and explaining the rail options. It does not detail every parameter (e.g., verify_token, sms_opt_in), but it compensates for the coverage gap on the core parameters.

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 states a specific action ('register the agency') on a specific resource ('insurance agency as a buyer') and clarifies the purpose: to receive consented consumer requests in its states. This clearly distinguishes it from sibling tools like agency_status or check_eligibility, which serve different functions.

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 provides clear context: it is for an AI working for a licensed insurance agency and describes the registration process. However, it does not explicitly mention when not to use this tool or name alternatives, so it falls short of a 5.

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

A3.9/5.0

Disambiguation4/5

Tools are largely distinct, with clear separation between eligibility checks, quote retrieval, lead queue pulls, and agency registration. Minor potential confusion between 'pull_requests' and 'request_agent_contact' exists, but descriptions clarify their different purposes.

Naming Consistency3/5

Names mix verb-first patterns (check_eligibility, get_quotes, register_agency) with noun-phrase patterns (market_data, agency_status, data_use_terms). The inconsistency is noticeable but not chaotic, and each name remains understandable.

Tool Count5/5

Eight tools is well within the reasonable range for this domain, covering the core workflows without unnecessary bloat or missing essential functionality.

Completeness4/5

The tool set covers registration, eligibility, quotes, consumer contact, lead pulling, market data, terms, and status checks. Minor gaps such as agency update/removal or quote customization exist, but the primary domain workflows are well represented.

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