get_weather

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

With no annotations provided, the description carries the full burden and does it well: it discloses the Open-Meteo data source, no API key requirement, sub-200ms performance, enriched interpretation/formatting, and the return structure. It also implies read-only behavior by describing a forecast retrieval operation.

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?

The description is front-loaded with a one-sentence summary and then well-structured into Examples, Provides, Data Source, Performance, Use this tool when, Args, and Returns. It is longer than strictly necessary because 'Provides' and 'Returns' partially overlap, but every section adds useful decision or invocation context.

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?

The description, combined with the output schema, covers what the tool does, when to use it, how to provide each parameter, what the response contains, and operational details like data source and performance. There are no significant missing pieces an agent would need to call it correctly.

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 schema has zero description coverage, but the Args section adds example coordinates, decimal-degree context, the valid 1-16 range for forecast_days, defaults for include_hourly and timezone, and the meaning of timezone for timestamps. This fully compensates for the schema gap.

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 uses a specific verb ('retrieves') and resource ('weather forecast for a location'), and enumerates concrete output fields (temperature, rain, sunshine, wind, humidity). It clearly identifies this as the general weather tool rather than snow, air quality, alerts, historical, or marine conditions.

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?

A dedicated 'Use this tool when' section lists concrete triggers: weather questions, outdoor activities, travel impact, and journey planning. It gives clear context but does not explicitly name sibling alternatives or state when not to use this tool, so it stops short of a 5.

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