get_hourly_weather

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It only states 'Get hourly weather forecast' but does not describe the response format, potential limitations (e.g., number of hours returned, timezone handling), or any side effects. The description is essentially a restatement of the tool's name with no added behavioral context.

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 concise and well-structured: a one-sentence purpose followed by clearly labeled arguments. Every sentence is essential, and the Args section is formatted for easy parsing. 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?

The tool has no output schema and no annotations, so the description should explain what the tool returns to be fully complete. It only states 'hourly weather forecast' without detailing the response fields (e.g., temperature, precipitation, wind). For an AI agent, this lack of return-value information leaves a significant gap in understanding the tool's full output.

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 provides only parameter names and types, with no descriptions (0% coverage). The description compensates by explaining 'location' as a city or location name with examples, and 'unit' with its default and allowed values ('C' for Celsius, 'F' for Fahrenheit). This adds meaningful semantics beyond the schema, though it could be more comprehensive (e.g., supporting zip codes or other formats).

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's function: 'Get hourly weather forecast for a location.' This is a specific verb (get) and resource (hourly weather forecast), and it is distinct from any potential siblings. No ambiguity in purpose.

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 does not explicitly state when to use this tool versus alternatives, but with no sibling tools listed, the context is clear. It provides the required input (location) and optional unit, implying the tool is for any location's hourly forecast. It lacks explicit exclusions or alternative recommendations, but this is acceptable given no alternatives exist.

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