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QuoteOS

Full Auto Quote Pipeline

getAutoQuotes
Read-onlyIdempotent

Run the full auto insurance quoting pipeline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
auto_input_jsonYesJSON string of the full AutoInput model. Required keys: garaging_address, drivers[], vehicles[], coverage See engine/validator.py AutoInput for full schema.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no behavioral context beyond repeating that it runs a pipeline, so it does not disclose other relevant behaviors such as whether it returns stored quotes, performs external lookups, or has side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loaded, which is good, but it is also under-specified. A single sentence conveys the general purpose but does not enrich the tool definition enough to justify a higher score.

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 tool has one parameter, complete schema documentation, output schema presence, and safety annotations, so the minimal description may suffice for a simple invocation. However, it lacks guidance on distinguishing this from sibling tools and does not clarify what 'full pipeline' means in practice, leaving some ambiguity.

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 the auto_input_json parameter is fully documented in the schema, including required keys and a reference to the full AutoInput model. The description adds little beyond the schema, so baseline 3 is appropriate.

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 uses a specific verb ('Run') and identifies the resource ('the full auto insurance quoting pipeline'). It distinguishes itself from siblings by focusing on a comprehensive auto quote, versus checkEligibility for eligibility and getHomeQuotes for home quotes, though it does not explicitly state those distinctions.

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?

The phrase 'full auto insurance quoting pipeline' implies this tool is for generating complete auto insurance quotes, but the description provides no explicit guidance on when to prefer it over checkEligibility or getHomeQuotes. Usage context is implied rather than stated.

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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