Weather MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves alerts but doesn't describe what the alerts contain, their format, whether the data is real-time or historical, any rate limits, authentication needs, or error conditions. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 efficiently structured and front-loaded: the first sentence states the purpose, followed by a clear 'Args:' section with parameter details. Every sentence earns its place, with no redundant or verbose language. It's appropriately sized for a single-parameter tool.

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 low complexity (one parameter) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the purpose and parameter semantics adequately. However, the lack of behavioral details (e.g., data freshness, error handling) and usage guidelines relative to siblings prevents a perfect score.

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 description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains that 'state' is a 'Two-letter US state code' and provides examples ('e.g. CA, NY'), clarifying the parameter's format and expected values. This fully compensates for the schema's lack of documentation, making the parameter semantics clear.

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 weather alerts for a US state.' It specifies the verb ('Get'), resource ('weather alerts'), and geographic scope ('US state'), making the function unambiguous. However, it doesn't explicitly differentiate from its sibling 'get_forecast' (which presumably provides forecasts rather than alerts), preventing a perfect 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 like 'get_forecast'. It doesn't mention any prerequisites, exclusions, or contextual cues for choosing between siblings. The only implicit usage hint is the geographic limitation to US states, but this is part of the purpose rather than comparative guidance.

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