Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it specifies the data source (Swiss Public Transport API, Open Data), real-time updates, and details about the return format (Katzilla envelope with quality scores and citation). Annotations already cover read-only, non-destructive, idempotent, and open-world hints, so the description effectively supplements with operational details without contradiction.

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, followed by source and return details in a structured manner. Every sentence adds value (e.g., specifying the API, real-time updates, and return format), with no wasted words, making it efficient and easy to parse.

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 complexity (search and connection functionality), rich annotations (read-only, idempotent, etc.), and the presence of an output schema, the description is complete. It covers purpose, source, behavioral traits, and return format, providing sufficient context without needing to explain parameters or output values in detail.

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, so the schema already documents the parameters ('query', 'from', 'to'). The description does not add further meaning or syntax details for these parameters beyond what the schema provides, such as examples or constraints, meeting the baseline for high schema coverage.

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 ('search Swiss public transport stations' and 'get connections between locations'), identifies the resource (Swiss Transport API), and distinguishes it from siblings by specifying its domain (Swiss public transport) and data source (SBB, BLS, PostBus, etc.), which is unique among the listed transport tools like 'transport__bc-ferries' or 'transport__uk-transport'.

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 implies usage context by stating it's for searching stations or getting connections, but it does not explicitly mention when to use this tool versus alternatives (e.g., other transport tools like 'transport__irail' or 'transport__uk-transport') or provide exclusions. The guidance is clear but lacks explicit sibling differentiation.

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