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 (BC Ferries API), update frequency (daily), and details about the return format (Katzilla envelope with quality scores and citation info). Annotations already cover read-only, non-destructive, idempotent, and open-world hints, so the description complements these by explaining freshness and auditability 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 highly concise and well-structured: it front-loads the core purpose, adds source and update details, and explains the return format in a single, efficient sentence. Every part adds value without redundancy, 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 simplicity (no parameters, annotations covering safety and idempotency, and an output schema implied by the return format description), the description is complete. It covers purpose, source, update frequency, and output structure, leaving no gaps for an agent to understand and invoke the tool correctly.

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 zero parameters, with 100% schema description coverage. The description does not need to explain parameters, but it implicitly confirms there are no required inputs by focusing on data retrieval without mentioning any filters or options. This is sufficient, though a perfect score is reserved for cases where parameter semantics are explicitly addressed when relevant.

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 ('Get current BC Ferries schedule and capacity data') and resources ('for British Columbia ferry routes'), distinguishing it from sibling tools like transport__bts-stats or transport__uk-transport by focusing on BC Ferries specifically. It explicitly mentions the data source (BC Ferries API) and update frequency (daily), which further clarifies its scope.

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: for accessing current schedule and capacity data from BC Ferries, sourced from a public API with daily updates. However, it does not explicitly state when not to use it or name alternatives among sibling tools (e.g., for historical data or other transport modes), 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.