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, covering safety and idempotency. The description adds valuable context beyond this: it specifies the data source (NOAA CO-OPS, Public Domain), update frequency (daily), and details about the return structure (Katzilla envelope with quality scores and citation info), which helps the agent understand data freshness and auditability.

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 details about the source, updates, and return format. Every sentence adds value without redundancy, making it efficient and well-structured for quick comprehension by an AI agent.

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 (environmental data retrieval), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It adds necessary context like data source, update frequency, and return structure details, ensuring the agent has enough information to use the tool effectively without needing to rely solely on structured fields.

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%, with clear descriptions for both parameters (station ID and product enum). The description adds no additional parameter semantics beyond what the schema provides, such as examples or constraints. Since the schema is comprehensive, a baseline score of 3 is appropriate, as the description does not compensate but also does not 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 clearly states the tool's purpose with specific verbs ('Get latest tidal, water level, temperature, and wind data') and resources ('from a NOAA CO-OPS station'), and it distinguishes itself from siblings by specifying the NOAA CO-OPS data source and the Katzilla envelope return format, which is unique among the listed environment tools.

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 for retrieving environmental data from NOAA stations, but it does not explicitly state when to use this tool versus alternatives like other environment tools (e.g., environment__canada-weather, environment__openaq). No exclusions or prerequisites are mentioned, leaving the agent to infer context from the tool's name and data source.

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