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 successfully describes key behavioral traits: it retrieves active warnings (not historical), returns JSON format, and specifies the content structure (alert levels, affected regions, hazard descriptions, validity periods). It doesn't mention rate limits, authentication needs, or potential errors, but provides substantial 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 efficiently structured in two sentences: the first states the core purpose and return format, the second explains the parameter options with concrete examples. Every sentence adds value with zero wasted words, and key information is front-loaded.

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 1 parameter with full schema coverage, no annotations, and no output schema, the description provides strong context about what the tool does, when to use it, and what it returns. It could be slightly more complete by mentioning the data source URL (danepubliczne.imgw.pl) earlier or potential limitations, but it covers the essential operational aspects well for this complexity level.

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 has 100% description coverage, so the baseline is 3. The description adds meaningful semantic context beyond the schema by explaining what 'meteo' and 'hydro' warnings specifically include (e.g., 'storms, frost, heat, wind' for meteo, 'flood and hydrological' for hydro), and clarifies that 'all' is the default behavior. This enhances understanding of parameter choices.

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 ('retrieve active meteorological and/or hydrological warnings'), the resource ('issued by IMGW-PIB'), and distinguishes it from sibling tools like imgw_hydro and imgw_meteo by explaining it can fetch both types or either individually. It goes beyond just restating the name to explain the actual function.

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 explicitly provides when-to-use guidance by explaining the three type options: 'meteo' for weather warnings, 'hydro' for flood/hydrological warnings, or 'all' for both (default). This gives clear context for selecting between this tool and its specialized siblings (imgw_hydro, imgw_meteo).

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