Get Fair Price Range

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds valuable context: the data is Japan-specific and in JPY, the danger threshold indicates overcharge suspicion, and the response includes trend and field notes. No contradiction with annotations.

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?

The description is bilingual but each sentence earns its place: what is returned, the use case, examples, and regional/pricing context. It is front-loaded with the primary action and contains no meaningless filler.

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?

For a single-parameter, read-only, output-schema-backed lookup tool, the description covers the return content, use context, scope, and pricing currency. Nothing essential is missing given the low complexity and existing structured metadata.

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 100% (single required query param described as 'construction name or keyword (Japanese)'). The description reinforces this with examples (exterior paint, water heater, unit bath, cross) and confirms the language expectation, adding value beyond the schema.

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 clearly states the tool returns a fair price range (min/avg/max), danger threshold, unit, price trend, and field notes for Japanese construction/renovation jobs. It explicitly names the use case (numerically checking cost fairness) and differentiates from siblings like get_fair_price_sources and verify_fair_price by focusing on the range itself.

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?

It provides clear context: use when you need to check whether a Japanese construction or renovation cost is fair, with examples of applicable queries. It does not mention exclusions or alternatives, but the guidance is clear enough to route an agent to this tool for price-range lookups.

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