Civic Data MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that it returns 'List of active weather alerts,' which indicates a read-only operation, but lacks details on permissions, rate limits, error handling, or data freshness. For a tool with no annotation coverage, this is a significant gap in transparency.

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 the core purpose in the first sentence, followed by structured sections for 'Args' and 'Returns' that are efficient and waste-free. Every sentence earns its place by providing essential information without redundancy, making it highly concise and well-structured.

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 mostly complete. It covers the purpose, parameter semantics, and return type adequately. However, it lacks behavioral details like error cases or usage constraints, which slightly reduces completeness for a tool with no annotations.

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, the description compensates by explaining the 'state' parameter as 'Two-letter state code (e.g., 'CA', 'TX', 'NY'),' adding crucial semantic context beyond the schema's basic type. Since there is only one parameter, this is sufficient to achieve a high score, though not perfect due to lack of further details like validation or examples beyond the few given.

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 specific action ('Get active weather alerts') and resource ('for a US state'), distinguishing it from sibling tools like 'get_weather_forecast' or 'get_global_weather' which serve different weather-related purposes. It precisely defines the tool's function without being vague or tautological.

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 specifying 'for a US state,' which provides some context, but it does not explicitly state when to use this tool versus alternatives like 'get_weather_forecast' or 'get_global_weather.' No exclusions or prerequisites are mentioned, leaving the agent to infer appropriate scenarios.

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