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

Beyond the readOnly/openWorld annotations, the description discloses the actual return content: median, middle-half range, low/high, and every business's lowest published price with source URL and read date. This gives the agent enough behavioral context to know what result to expect and how fresh/sourced the pricing data is.

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 front-loaded with the output shape and then the service list, with no filler. It is appropriately sized, though the long enumerated service list makes it slightly less crisp than an ideal definition.

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 three-parameter read-only pricing tool with no output schema, the description covers the return values, the valid service scope, the omit behavior, and the sibling alternative. Nothing essential for correct invocation is missing.

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%, so parameter documentation is already strong, but the description adds material value by enumerating the valid service slugs rather than only giving schema examples. It also clarifies omission behavior for the optional service parameter.

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 states the exact resource (typical local service cost in a city) and enumerates the returned metrics: median, middle-half range, low/high, and each business's lowest published price with source URL and read date. It also distinguishes itself from the sibling find_prices by explicitly directing other queries there.

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 gives useful usage guidance: omitting service returns all services for the city, and anything else should go to find_prices. The alternative is named, but the boundary between this tool and find_prices is expressed only as 'anything else,' which is slightly vague rather than a crisp when-to-use rule.

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