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

Annotation Contradiction: readOnlyHint=true indicates the tool does not modify state, yet the description says 'the request is still registered and a quote_id returned' even when unlicensed. This implies a persisted quote/request record, which is a state-changing side effect. The description directly contradicts the annotation, so the behavioral transparency score must be 1.

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

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

Four sentences cover the core outcome, input constraints, licensing fallback, and missing-facts behavior without excessive filler. It is appropriately sized for the tool's complexity and front-loads the primary purpose before edge conditions.

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

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

With 10 parameters, no output schema, and only 20% schema description coverage, the description leaves major gaps: return structure beyond 'prices' or 'quote_id', validation behavior, optional parameter details, and licensing conditions. The licensing fallback is helpful, but the definition is not complete enough for an agent to call this robustly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20%, so the description must compensate for the other 8 parameters. It only broadly says 'takes rating facts only' and lists what is not required, but it does not explain annual_mileage, violations_3yr, years_licensed, prior_continuous, or vehicle_make_model semantics beyond their names. The missing-facts sentence hints the server will ask, but it does not document parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: 'Return indicative auto insurance prices from multiple carriers.' It also explains the licensing-dependent behavior and the no-PII input rule, which clearly separates this from sibling tools like request_agent_contact or check_eligibility. The purpose is unambiguous and agent-actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context: it takes rating facts only, requires no personal identifiers, and explains what happens when the entity is not licensed to display prices. It does not explicitly name alternative tools or state when not to use it, but the context is specific enough for an agent to know when this tool applies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.