Retrieve the weather forecast for a specific location using its latitude and longitude coordinates.
Get weather forecast for a location.
Args:
latitude: Latitude of the location
longitude: Longitude of the location
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | ||
| longitude | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe any behavioral traits - no information about rate limits, authentication needs, whether this is a read-only operation, what format the forecast returns, or any side effects. This is inadequate for a tool with zero annotation coverage.
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 appropriately sized with a clear purpose statement followed by parameter documentation. The two-sentence structure is efficient, though the parameter documentation could be integrated more seamlessly rather than as a separate 'Args:' section. Every sentence serves a purpose.
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 no annotations, no output schema, and a simple 2-parameter tool, the description is incomplete. It doesn't explain what the forecast returns (format, time range, metrics), any limitations (e.g., historical vs. future forecasts), or behavioral constraints. For a weather API tool, users need to know what data they'll receive.
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?
With 0% schema description coverage and 2 parameters, the description compensates well by explicitly listing both parameters ('latitude' and 'longitude') and providing basic semantic context ('Latitude of the location', 'Longitude of the location'). This adds meaningful information beyond the bare schema, though it doesn't specify format constraints or valid ranges.
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 with 'Get weather forecast for a location' - a specific verb ('Get') and resource ('weather forecast') with scope ('for a location'). However, it doesn't differentiate from sibling tools like 'get_alerts' which might also relate to weather, so it doesn't reach the highest score.
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 provides no guidance on when to use this tool versus alternatives. There's no mention of when-not scenarios, prerequisites, or comparison with sibling tools like 'get_alerts' (which might provide weather alerts instead of forecasts). The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.