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weather-intel-mcp

weather_forecast

Get a multi-day weather forecast for a US location by latitude/longitude (National Weather Service). Returns named periods (Today, Tonight, ...) with temperature, wind, and a short + detailed forecast. Use geocode first if you only have an address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude in decimal degrees, e.g. 36.1867. US coverage only (National Weather Service).
lonYesLongitude in decimal degrees, negative in the western hemisphere, e.g. -94.1288.
hourlyNoIf true, return the hourly forecast instead of daily periods.

TDQS

A4.2/5.0
Behavior4/5

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 reveals the source (National Weather Service), the response pattern (named periods), and the returned fields (temperature, wind, short and detailed forecast). It does not discuss rate limits, auth, or failure modes, but for a straightforward read-only forecast lookup the disclosed behavior is useful and sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences each earn their place: the first states the core function, the second describes the return value, and the third gives routing guidance. The key purpose is front-loaded and there is no filler or repetition of schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema and annotations, the description does a good job summarizing what the agent should expect: multi-day periods, fields, and forecast text. It also covers the main routing prerequisite via geocode. Minor gaps such as the hourly mode being absent from the description are covered by the schema, so the description remains adequately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents lat, lon, and hourly with examples and units. The description adds only the high-level idea of 'by latitude/longitude' and the geocode-first hint, which does not go beyond the schema. Baseline 3 is appropriate because the description does not need to compensate for schema gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Get a multi-day weather forecast for a US location by latitude/longitude', which states a specific action, resource, and geographic scope. It also mentions returning named periods with weather details, which clearly distinguishes this tool from siblings like weather_current and weather_alerts. The distinction is easy for an agent to make without inspecting schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit guidance to 'Use geocode first if you only have an address', which tells the agent when a sibling tool should be used instead. It does not explicitly mention when to use weather_current or weather_alerts as alternatives, but the forecast-vs-current distinction is strongly implied by 'multi-day forecast' and 'named periods (Today, Tonight, ...)'.

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

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TDQS

A4.3/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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.

Tool Count5/5

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.

Completeness5/5

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.