ph-civic-data-mcp

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 adds valuable context by explaining the API fallback mechanism (PAGASA TenDay API when token is set, otherwise Open-Meteo), which informs the agent about data source dependencies and potential variations in behavior. However, it lacks details on rate limits, error handling, or response formats, leaving some behavioral aspects unclear.

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 and front-loaded, with the first sentence stating the core purpose and the second adding crucial behavioral context about API fallback. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse.

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 moderate complexity (2 parameters, 100% schema coverage, and an output schema exists), the description is reasonably complete. It covers the purpose, geographic scope, and API behavior, and since an output schema is present, it need not explain return values. However, it could benefit from more explicit usage guidelines relative to siblings to enhance completeness.

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 description coverage is 100%, meaning the input schema already documents both parameters (location and days) with descriptions. The description does not add any additional meaning or semantics beyond what the schema provides, such as examples or constraints not covered in the schema. Thus, it meets the baseline for high schema coverage without compensating with extra param info.

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 as 'Get weather forecast for a Philippine location,' which specifies the verb (get), resource (weather forecast), and geographic scope (Philippine location). However, it does not explicitly differentiate from sibling tools like 'get_weather_alerts,' which might cover similar weather-related data but for alerts rather than forecasts.

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 the geographic scope (Philippine location) and mentions API fallback behavior (PAGASA vs. Open-Meteo), which provides some context. However, it does not explicitly state when to use this tool versus alternatives like 'get_weather_alerts' or other weather-related siblings, nor does it provide exclusions or clear prerequisites for usage.

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