Get active weather alerts for a U.S. state.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what data is retrieved but lacks details on rate limits, authentication needs, error handling, or response format. It mentions the source (National Weather Service) but not potential limitations like data freshness or coverage.

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 appropriately sized with two sentences that are front-loaded and efficient. The first sentence states the core purpose, and the second adds useful examples without redundancy. Every sentence earns its place by enhancing clarity.

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's moderate complexity (single parameter, no annotations, but with an output schema), the description is mostly complete. It covers the purpose and scope well, but since there is an output schema, it does not need to explain return values. However, it could improve by addressing behavioral aspects like data source reliability.

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 has 0% description coverage, so the description must compensate. It adds meaning by specifying that the 'state' parameter refers to a U.S. state for which alerts are retrieved, though it does not detail format (e.g., abbreviations like 'CA') or validation rules. This partially compensates for the schema gap.

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 specific action ('Retrieves'), resource ('active weather alerts, warnings, and advisories'), and source ('National Weather Service'), and distinguishes it from siblings by focusing on alerts rather than forecasts or general weather data. It provides concrete examples of alert types like severe weather warnings and flood advisories.

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 usage for retrieving active alerts in a U.S. state, but does not explicitly state when to use this tool versus alternatives like get_forecast or get_weather. It provides context (e.g., 'currently active'), but lacks explicit guidance on exclusions or prerequisites.

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