Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it discloses the data source (Squiggle API), update frequency (monthly), return format (Katzilla envelope with quality scores and citation details), and audit features (SHA-256 hash). While annotations cover read-only, non-destructive, idempotent, and open-world hints, the description enriches this with practical implementation details that help the agent understand what to expect from the tool's behavior.

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 source, the second details the return format and its components. Every sentence adds value without redundancy, and key information (data source, return format) is front-loaded appropriately.

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 low complexity (1 parameter, 100% schema coverage), rich annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), and the presence of an output schema (implied by context signals), the description is complete. It covers purpose, source, update frequency, and return format, providing sufficient context for the agent to use the tool effectively without needing to explain parameters or output details that are already documented elsewhere.

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 with a clear enum for the 'query' parameter. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain what 'teams', 'games', or 'tips' data types entail). 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 clearly states the tool's purpose with specific verbs ('Get AFL data from Squiggle') and resource ('Australian Football League data'), and distinguishes it from siblings by specifying the data source (Squiggle API) and return format (Katzilla envelope). It goes beyond the title/name to explain what data is retrieved and from where.

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 mentioning the data source (Squiggle) and update frequency (monthly), but does not explicitly state when to use this tool versus alternatives or provide any exclusions. It lacks guidance on when this specific AFL data tool should be chosen over other sports or data tools in the sibling list.

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