Get current weather and forecast for a location. Returns conditions, temperature, humidity, wind, and multi-day forecast.
Args: location: City name or coordinates (e.g. 'London, UK', 'New York, NY', '37.7749,-122.4194')
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations include readOnlyHint=true, so the description does not need to re-state safety. It adds value by disclosing the return data (conditions, temperature, humidity, wind, forecast), which is especially important since there is no output schema. It does not mention potential limitations like units or availability, but the safety profile is already covered by annotations.
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 concise: one sentence for the main purpose and a clear Args section with a single parameter. Every word is informative, no fluff or redundancy. The structure is front-loaded with the main action, making it easy to scan.
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 simplicity (one parameter, no output schema, no siblings), the description covers the essential aspects: what it does, what it returns, and how to specify the location. It does not mention unit systems or potential errors, but these are minor for a basic weather tool. The existing coverage is strong enough for an agent to use 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 input schema has zero description coverage (0%), so the description must fully explain the parameter. It does so effectively by providing the type (city name or coordinates) and concrete examples (e.g., 'London, UK', '37.7749,-122.4194'). This is exactly what the parameter needs for correct invocation.
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's purpose: 'Get current weather and forecast for a location.' This is a specific verb+resource pair that accurately describes the functionality. It also lists the return fields (conditions, temperature, humidity, wind, multi-day forecast), further clarifying what the tool does.
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 usage by stating it retrieves current weather and forecast, which is clear context. There are no sibling tools to differentiate from, so explicit alternatives are not applicable. However, it does not explicitly state when not to use the tool or mention any exclusions, so a score of 4 is appropriate.
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.
Only one tool exists, so there is no possibility of confusing it with another. The tool's purpose is clearly described and distinct.
The single tool name 'get_weather' follows the conventional verb_noun pattern. With only one tool, consistency is trivially achieved, and the name is clear and descriptive.
A single tool feels thin for a weather server, but it covers both current conditions and forecast, so it is not a trivial tool. This is borderline in terms of count, but not extreme.
The tool covers the core weather use cases (current conditions and multi-day forecast). Minor gaps exist, such as lack of separate current/forecast endpoints or geocoding support, but these can be worked around since the tool accepts city names and coordinates directly.