Polish Academic 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 effectively describes key behavioral traits: the data source (danepubliczne.imgw.pl), return format (JSON with specific measurement types), scope (all active meteorological stations in Poland), and refresh rate (roughly every hour). It doesn't mention error handling or authentication needs, but covers the essential operational context.

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 perfectly concise and front-loaded: the first sentence states the core purpose, the second adds details about return format and scope, and the third provides refresh information. Every sentence earns its place with no wasted words.

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 simplicity (0 parameters, no annotations, no output schema), the description is nearly complete. It explains what data is returned, from where, for what geographic scope, and how frequently it's updated. The only minor gap is the lack of output schema, but the description adequately describes the return content (JSON with specific measurements).

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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on what the tool does without inputs.

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 specific verbs ('retrieve', 'returns') and resources ('current meteorological station readings from IMGW-PIB', 'JSON with temperature, precipitation, snow cover, wind, and related measurements'). It distinguishes itself from siblings like imgw_hydro, imgw_synop, and imgw_warnings by specifying it provides station readings rather than hydrological data, synoptic data, or warnings.

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 clear context for when to use this tool: to get current meteorological station readings for Poland, refreshed roughly every hour. It doesn't explicitly state when not to use it or name alternatives, but the specificity of the data (station readings vs. hydro/synop/warnings) implies differentiation from sibling tools.

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