get_restaurants

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does but gives no details about pagination, ordering, rate limits, authentication, or side effects. This is a significant gap for a data retrieval tool.

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 a single concise sentence that front-loads the main action and resource. Every word earns its place, with no filler or redundancy.

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?

Given the tool has three optional parameters and no output schema, the description provides a basic sense of what it returns ('order counts and spending stats') but lacks details on return structure, filtering behavior, or how the parameters affect results. It is adequate but not comprehensive.

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?

The input schema already provides clear descriptions for all three parameters (start_date, end_date, min_orders) with 100% coverage, so the baseline is 3. The tool description does not add any additional semantic meaning beyond what the schema already states.

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 uses a specific verb ('Get') and resource ('restaurants') and states the data returned ('order counts and spending stats'). This clearly identifies the tool's purpose, but it does not explicitly distinguish it from sibling tools like get_orders or get_analytics beyond the resource name.

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 implies the tool is for retrieving restaurant-level aggregate data, but it does not explicitly state when to use this tool versus alternatives, nor any exclusions or prerequisites. Usage context is inferred from the resource and data mentioned.

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