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 source (GovData.de), update frequency (daily), and details the return format (Katzilla envelope with data, quality scores, and citation including SHA-256 hash). Annotations already indicate read-only, non-destructive, idempotent, and open-world hints, so the description complements these with operational details 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 front-loaded with the core purpose, followed by source and return details in two efficient sentences. Every sentence adds value: the first defines the search scope, and the second explains the output structure and quality metrics, with no wasted words.

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 (search with parameters), rich annotations (read-only, idempotent, etc.), and the presence of an output schema (implied by the description of the Katzilla envelope), the description is complete. It covers purpose, source, update frequency, and return format, adequately supplementing the structured data without needing to explain return values in detail.

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 schema description coverage is 100%, so the input schema already documents the parameters (query, groups, limit) with descriptions and examples. The description does not add further meaning or syntax details for the parameters, such as explaining 'groups' categories beyond the schema's example. Baseline 3 is appropriate as the schema handles the heavy lifting.

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 searches the German government open data portal (GovData) for datasets from federal, state, and municipal authorities, covering specific domains like statistics, geospatial data, environment, transport, and public services. It distinguishes itself from siblings by specifying the German focus and GovData source, unlike other government data tools (e.g., data-australia, data-canada).

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 searching German open data across various categories, but does not explicitly state when to use this tool versus alternatives or provide exclusions. It mentions the source (GovData.de) and daily updates, which gives context, but lacks direct comparison to sibling tools like data-france or data-uk for guidance on regional selection.

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