List active NWS weather alerts (warnings, watches, advisories) for a US state or marine area. Pass a two-letter state code like CA, TX, FL. Returns event type, severity, headline, affected area and expiry.
| Name | Required | Description | Default |
|---|---|---|---|
| area | Yes | Two-letter US state/territory code, e.g. CA, TX, FL, PR. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the type of alerts (warnings, watches, advisories) and return fields, but lacks details on potential behavioral traits like rate limits or authentication. A minor inconsistency exists between 'state or marine area' and focusing solely on state codes.
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?
Two concise sentences: first states purpose, second provides example usage and expected output. No wasted words, front-loaded.
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 single-parameter tool with no output schema, the description adequately covers purpose and output fields. It could mention that no output schema means the agent must parse the response, but overall it is sufficient.
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?
With 100% schema coverage, the description adds marginal value by repeating the parameter info and providing examples. It does not explain marine area codes or clarify if they differ from state codes.
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 lists active NWS weather alerts for a US state or marine area, specifying the verb (list), resource (weather alerts), and scope. It is distinct from sibling tools like weather_current and weather_forecast.
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 clear context by instructing to pass a two-letter state code with examples. However, it does not explicitly state when not to use this tool or mention alternatives for weather data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool maps to a distinct data source and purpose: geocode converts addresses, elevation samples terrain, earthquakes returns seismic events, and the weather_* tools clearly separate alerts, current observations, and forecast. No two tools would plausibly return the same data.
All names are lowercase snake_case and descriptive, with weather_ prefix clearly grouping NWS tools. geocode is a verb-like single word rather than a noun/resource, and earthquakes/elevation lack the weather_ prefix, so there are minor deviations from a fully uniform pattern.
Six tools is well-scoped for a US-focused weather and environmental intel server. Each tool covers a separate dataset with no redundant utilities, while keeping the surface small enough for an agent to navigate easily.
The server covers the essential US weather workflows: geocoding from an address, current conditions, multi-day forecast, and alerts, plus related elevation and earthquake data. No critical gaps are implied by the stated purpose and tool surface.