Weatherapi Com MCP Server

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

No annotations are provided, so the description carries full burden. It mentions the date constraint ('on or after 1st Jan, 2010') and subscription-level dependencies, but lacks critical behavioral details: it doesn't specify authentication requirements, rate limits, error handling, or the structure of the JSON response. For a data-fetching tool with no annotation coverage, this leaves significant gaps in understanding its operation.

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 a single, efficient sentence that states the core purpose upfront. It avoids redundancy and wastes no words, though it could be slightly more structured (e.g., by separating key constraints). Overall, it's appropriately concise for the tool's complexity.

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 and no output schema, the description is incomplete. It covers the basic purpose and date constraints but omits essential context: authentication needs, rate limits, error cases, and the JSON response structure. For a historical data API with multiple parameters, this leaves the agent under-informed about how to effectively invoke and interpret results.

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?

Schema description coverage is 100%, so the schema fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain 'q' formats or 'dt' constraints in more detail). Baseline 3 is appropriate as the schema handles parameter semantics adequately.

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: 'returns historical weather for a date on or after 1st Jan, 2010 as json.' It specifies the verb ('returns'), resource ('historical weather'), and temporal scope. However, it doesn't explicitly differentiate from siblings like 'realtime_weather_api' or 'forecast_weather_api' beyond the 'historical' qualifier, which is implied but not contrasted.

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. It mentions subscription-level dependencies but doesn't name or compare to sibling tools (e.g., 'realtime_weather_api' for current weather or 'forecast_weather_api' for future predictions). There's no explicit 'when-not' or alternative usage context.

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