Convert a US street address into latitude/longitude coordinates (US Census geocoder). Use this first when you have an address but need coordinates for the weather/elevation tools. US addresses only.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | A US street address, e.g. '1600 Pennsylvania Ave NW, Washington DC' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It explains the geocoding process using US Census. Lacks details like rate limits or authentication, but the behavior is simple and well-defined. Score 4 as it's very clear.
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 sentences, front-loaded with action and resource. Every sentence is essential and there is no wasted text.
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 only one required parameter, no nested objects, no output schema, and a simple task, the description fully covers what an agent needs to know: the purpose, usage context, and constraint (US only).
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?
Schema coverage is 100% with one parameter 'address' described. The description adds context: US street address format and an example. This adds meaningful information beyond the schema.
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 converts US street addresses to lat/lng coordinates, names the data source (US Census geocoder), and distinguishes itself by noting it's for weather/elevation tools. Specific verb 'convert' and resource 'address'.
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?
Explicit usage guidance: 'Use this first when you have an address but need coordinates for the weather/elevation tools. US addresses only.' Clearly states when to use and the constraint of US addresses.
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.