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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds that data is estimated from published sources, not measurements, alerting the agent to potential inaccuracy. This context is valuable beyond annotations, though no further behavioral details are needed.

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 two sentences, front-loading the purpose and then providing data source and ordering details. Every sentence adds value with no redundancy, demonstrating excellent conciseness.

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 simple 1-parameter tool with an output schema, the description sufficiently covers purpose, scope, limitations, and alternatives. No gaps remain for effective tool selection and invocation.

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% with a single 'limit' parameter already described. The description does not add extra meaning about the parameter beyond what's in the schema, so baseline score of 3 is appropriate.

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 explicitly states it answers queries like 'loudest cities in the world' and 'noisiest cities ranking', specifying 50 major world cities ordered by estimated daytime noise. It clearly distinguishes from sibling tools by naming alternatives for US and Europe.

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 provides explicit when-to-use guidance (for global loudest cities) and when-not-to-use (for US or Europe), naming alternative tools (get_us_city_noise_exposure, get_europe_city_noise). This helps the agent select the correct tool.

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