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PolicyVera insurance quotes

States with licensed insurance agents ready to quote

list_states
Read-only

Which US states have licensed insurance agents ready to quote on PolicyVera today. A state missing from the list has no licensed insurance agent ready today.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_states"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description does add genuine behavioral context beyond that: the absence semantics ('a state missing from the list has no licensed insurance agent ready today') and the time-sensitivity implied by 'today'. However, it says nothing about how fresh the data is, refresh cadence, or the shape/ordering of the returned states.

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?

Two short sentences, front-loaded with the positive case followed by the negative-case clarification, with no filler. The first sentence is a sentence fragment ('Which US states have...') rather than a statement of what the tool returns, which is a minor stylistic stumble but costs no comprehension.

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 zero-parameter read tool with annotations covering the safety profile, the description supplies everything needed to call it correctly and to interpret an empty or partial list. The remaining gap is return-value form — whether states come back as two-letter codes or full names, and whether ordering is guaranteed — which matters slightly since no output schema exists.

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?

The tool takes zero parameters and schema coverage is 100%, so there is no parameter meaning for the description to add. Baseline 4 applies; nothing is missing or misleading on this dimension.

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?

The description names the resource precisely ('US states have licensed insurance agents ready to quote on PolicyVera') and states the scope is current-day availability. It is immediately distinguishable from list_agents, which presumably lists the agents themselves rather than the states. It stops short of an explicit verb-plus-object framing ('Returns the list of...'), which is why it isn't a 5.

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?

There is no explicit when-to-use guidance, no mention of the natural next step (send_quote_request) and no exclusions against sibling tools such as list_agents. The intended use — pre-checking whether coverage exists in a state — is only implied by the word 'ready to quote'. Minimum viable but leaves routing to inference.

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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