Get the latest observed weather conditions for a US location by latitude/longitude, from the nearest NWS observation station: temperature, humidity, wind, and text description.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude in decimal degrees, e.g. 36.1867. US coverage only (National Weather Service). | |
| lon | Yes | Longitude in decimal degrees, negative in the western hemisphere, e.g. -94.1288. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose the source (NWS), the nearest-station behavior, and the returned fields, which is useful. However, it does not mention potential staleness, coverage limitations beyond 'US location', or what happens when no station is near, leaving some behavioral ambiguity.
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?
A single, front-loaded sentence that states the action, resource, location scope, coordinate method, data source, and returned fields. There is no filler or redundancy, every phrase earns its place.
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 low complexity and high schema coverage, the description is nearly complete for an agent to call it correctly. It names the returned fields despite no output schema, and distinguishes current observations from forecasts. It could be marginally improved by stating units or staleness, but nothing essential is missing.
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 strong descriptions for both parameters, including examples and US-only coverage, so schema coverage is 100%. The description adds context about the nearest NWS station but does not need to explain the parameters further; baseline 3 is appropriate.
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 starts with a specific verb ('Get') and a clear resource ('latest observed weather conditions for a US location by latitude/longitude'), then lists the data fields returned. It also names the data source and the nearest-station behavior, which clearly separates it from the sibling weather_forecast and weather_alerts tools.
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 when to use the tool: for current/observed conditions rather than forecasts or alerts. It does not explicitly say 'use weather_forecast for future conditions,' but the word 'observed' and 'latest' provide a clear context, and the sibling list makes the alternative obvious. Slight deduction for lack of explicit exclusions.
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.