Katzilla MCP

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds valuable context beyond this: it discloses the real-time update nature, the source (Digitraffic with Creative Commons license), and details about the return structure (Katzilla envelope with quality scores and citation data including a SHA-256 hash for audit). This enriches the agent's understanding of data freshness, licensing, and output format.

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 purpose and usage, and the second details the return format and source information. Every sentence adds critical value—no wasted words—and it's front-loaded with the core functionality.

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 (real-time data lookup with quality metrics), rich annotations (read-only, idempotent, etc.), and the presence of an output schema, the description is complete. It covers purpose, source, licensing, update frequency, and return structure, providing all necessary context for an agent to use the tool effectively without needing to explain return values (handled by the output schema).

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 fully documents the parameters (mmsi, shipName, limit). The description mentions looking up by MMSI or name, which aligns with the schema but doesn't add significant semantic details beyond what's already in the schema descriptions. It does not explain parameter interactions or constraints, so it meets 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 explicitly states the tool's purpose: 'Vessel metadata and registration data from Digitraffic maritime AIS. Look up vessels by MMSI or name.' It specifies the verb ('look up'), resource ('vessel metadata and registration data'), and source ('Digitraffic maritime AIS'), clearly distinguishing it from sibling tools that cover different domains like agriculture, consumer, or crypto.

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: for real-time maritime vessel lookups by MMSI or name, with a specified data source. It does not explicitly mention when not to use it or name alternative tools for similar purposes, but the domain-specific context (maritime vs. other sibling domains) offers implicit guidance.

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