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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses the underlying data source ('real quotes we collected'), the geographic granularity (3-digit ZIP region, US-only), the fields returned (median, sample size, optional verdict), and that this call is free while the fuller distribution costs $0.25 elsewhere. That is material context an agent cannot get from annotations or schema.

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 tight sentences, front-loaded with the trigger condition, then data basis, then return values, then cost/fallback. Every sentence carries a distinct piece of information with no restatement of the name or title.

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?

There is no output schema, and the description compensates fully by stating the returned fields and the conditional verdict. Data sourcing, region granularity, cost and a paid escalation path are all covered, so an agent has everything needed to call it and interpret the result.

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 coverage is already 100%, so the baseline is 3; the description adds real meaning on top by clarifying that ZIP is resolved to a 3-digit region and that supplying quoted_usd is what unlocks the low/fair/high verdict. Remaining gap is minor: it does not restate that trade/job_type ids come from list_job_types, though the schema does.

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-plus-resource (compares a contractor quote against collected real quotes for the same job type and 3-digit ZIP region) and enumerates what is returned. It is clearly distinct from the sibling tools list_job_types, get_quote_job and request_quotes, which handle lookup and quote solicitation rather than price benchmarking.

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 trigger condition is stated plainly: 'Use this when the user asks whether a contractor price or quote is fair, or what a job typically costs in their area (US).' It also names an alternative path for deeper data (the paid x402 endpoint). It stops short of saying when NOT to use it versus get_quote_job or request_quotes, so it falls just under full when/when-not coverage.

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