Katzilla MCP

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

Annotations already cover key behavioral traits (readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true), so the bar is lower. The description adds valuable context beyond annotations: it specifies the data source ('Pinball Map (Free API)'), update frequency ('updates daily'), and details about the return format ('Katzilla envelope { data, quality, citation }') with explanations of quality scores and citation contents. This enriches the agent's understanding without contradicting annotations.

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 front-loaded with the core purpose in the first sentence, followed by essential contextual details (source, updates, return format). Every sentence adds value: the second sentence provides metadata, and the third explains the output structure. It is efficiently structured with zero wasted words, making it easy for an agent to parse quickly.

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 (3 optional parameters), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Has output schema: true'), the description is complete. It covers purpose, source, update frequency, and return format details, which complements the structured data well without needing to explain parameters or output values redundantly.

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 already fully documents the three parameters (lat, lon, distance). The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it mentions 'near coordinates' but doesn't clarify parameter interactions or defaults). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 explicitly states the tool's purpose with specific verbs ('Find pinball machine locations near coordinates, or list all regions') and resources ('pinball machine locations', 'regions'). It clearly distinguishes this geography-focused tool from its many siblings across diverse domains like agriculture, consumer, crypto, etc., by specifying its unique geolocation function and data source (Pinball Map).

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 the tool ('Find pinball machine locations near coordinates, or list all regions'), implying usage for location-based queries. However, it does not explicitly state when not to use it or name alternatives among siblings (e.g., other geo__ tools like geo__census-geocoder or geo__nominatim), which prevents a perfect score.

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