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

With no annotations, the description carries the full behavioral burden. It discloses the paid fee structure ($0.0033 inbound and proxy), that data is live government data requiring no API key, and that the call is a GET returning clean JSON. This goes well beyond the generic schema and helps an agent understand cost, auth, and expected response shape.

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 dense line that packs purpose, output fields, cost, data source, method, and an example. It is front-loaded with the core purpose and every piece of information is relevant, though the upstream URL and pricing could arguably be trimmed without losing the main message.

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 GET API with no output schema, the description provides return fields, an example parameter, and cost/auth context. It lacks explicit error behavior or edge-case handling (e.g., invalid state code, missing area), but the core information needed to invoke the tool correctly is present.

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 only describes generic 'body' and 'query' objects with no specific parameters, so the description adds essential meaning by showing the ?area=CA query parameter and an example query object. This compensates for the schema's lack of domain-specific parameter documentation.

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 returns Active National Weather Service alerts for a US state, and enumerates the specific output fields (event, severity, headline, affected areas, onset/expiry). This distinguishes it from sibling weather tools that provide forecasts, current conditions, or METARs.

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 gives a clear usage context: US state alerts from the NWS, with a concrete example query ?area=CA and the HTTP method GET. It does not explicitly name alternative sibling tools or say when not to use it, but the specificity of 'alerts for a US state' provides enough context for an agent to select it over other weather tools.

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