Katzilla MCP

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

Annotations cover read-only, non-destructive, idempotent, and open-world hints, but the description adds valuable context: it discloses the return format ('Katzilla envelope { data, quality, citation }'), explains quality metrics ('freshness/uptime/confidence'), and details citation components ('source URL, license, SHA-256 hash'), which are not inferable from annotations alone.

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 details and return format explanation in a compact two-sentence structure. Every sentence adds essential information without redundancy, making it highly efficient.

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 (2 parameters), rich annotations (covering safety and behavior), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It adequately explains the tool's purpose, usage context, and output without needing to detail parameters or return values further.

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 both parameters ('league', 'season') well-documented in the schema. The description does not add any parameter-specific details beyond what the schema provides, so it meets the baseline for high schema coverage without extra value.

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 action ('Get football/soccer match data'), resource ('from OpenLigaDB'), and scope ('German leagues focus'), which is specific and distinguishes it from sibling tools like 'sports__live-scores' or 'sports__team-info' that might handle different sports data or formats.

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?

It provides clear context for when to use this tool (for football/soccer match data from OpenLigaDB with a German focus) and mentions the source and update frequency ('updates monthly'), but does not explicitly state when not to use it or name alternative tools for similar data, 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.