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Hourly Forecast (up to 16 days)

weather_hourly
Read-onlyIdempotent

Hour-by-hour forecast: temperature, apparent temperature, precipitation probability + amount, humidity, cloud cover, wind speed/gusts/direction, and a WMO condition label per hour. For event timing, energy-demand curves, and logistics windows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNo
lonNo
hoursNo
unitsNoimperial
zip_codeNoUS ZIP (preferred). Or pass lat+lon.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering safety and side effects. The description adds context about the output data (fields returned) but does not disclose additional behavioral traits like rate limits, authentication needs, or error scenarios. It goes slightly beyond annotations by listing the output fields, but does not add deep behavioral context. Therefore, a 3 is appropriate.

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?

The description is two sentences: the first front-loads the essential 'hour-by-hour forecast' and enumerates the data fields; the second provides concise use cases. There is no filler or redundant repetition of the title or schema. It is well-structured and efficient.

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

Completeness3/5

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

Given the tool has 5 parameters and no output schema, the description should explain the semantics of parameters and the full output. It lists the returned fields, which is helpful, but it does not explain parameter formats (e.g., how to pass lat/lon vs zip_code, units options, hours range). The title mentions 'up to 16 days' but the description omits this detail. It is adequate but not complete, leaving a medium gap for an agent to correctly call the tool.

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

Parameters2/5

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

Schema description coverage is only 20% (only zip_code has a description). The tool description does not compensate; it lists output fields but provides no guidance on input parameters like lat, lon, hours, or units. It does not explain that lat/lon can be used interchangeably with zip_code, the meaning of hours (though the title mentions up to 16 days), or the units enum values. This is a significant gap for a tool with 5 parameters.

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 clearly states the tool's function: providing hour-by-hour weather forecasts with a specific list of data fields (temperature, humidity, wind, etc.). It distinguishes from siblings like weather_current (current) and weather_forecast (likely daily) by emphasizing 'hour-by-hour' and 'per hour'. The mention of use cases (event timing, energy-demand curves) further clarifies its niche.

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 clear usage context via the phrase 'For event timing, energy-demand curves, and logistics windows,' which implies these are the ideal scenarios for hourly data. However, it does not explicitly contrast with alternatives (e.g., when to choose weather_forecast over this) or state exclusions. Since it provides actionable context without explicit exclusions, it earns a 4.

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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