Katzilla MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context beyond this: it specifies the data source (World Air Quality Index Project), update frequency (real-time), license (CC-BY-NC 4.0), and return format details (Katzilla envelope with quality scores and citation). This enhances the agent's understanding of data reliability and attribution.

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 source, and the second details the return format and metadata. Every sentence adds critical information without redundancy, making it front-loaded and concise.

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 optional parameter), rich annotations (covering safety and idempotency), and the presence of an output schema, the description is complete. It covers purpose, source, update frequency, license, and return structure, leaving no significant gaps for the agent to understand the tool's behavior and context.

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 input schema has 100% description coverage, with the 'city' parameter documented as 'City name or station identifier'. The description does not add any further parameter semantics beyond what the schema provides, such as examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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 a specific verb ('Get'), resource ('real-time Air Quality Index (AQI) data'), and scope ('for a city from the WAQI project'). It distinguishes itself from sibling tools by focusing on air quality data, unlike other environment tools that cover weather, carbon intensity, or floods.

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 retrieve real-time AQI data for a city), but it does not explicitly state when not to use it or name alternatives. It implies usage for air quality queries, but lacks explicit exclusions or comparisons with similar tools like environment__openaq or environment__openmeteo-aq.

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