Katzilla MCP

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

Annotations already cover read-only, non-destructive, idempotent, and open-world hints. The description adds valuable behavioral context beyond annotations by specifying the update frequency ('updates daily'), describing the return format ('Katzilla envelope { data, quality, citation }'), and detailing quality metrics ('freshness/uptime/confidence') and citation components ('source URL, license, SHA-256 hash'). This enriches the agent's understanding without contradicting annotations.

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 into two sentences: one stating the tool's purpose and source, and another detailing the return format and its components. Every sentence adds essential information without redundancy, making it front-loaded and appropriately sized for quick comprehension.

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 functionality with quality metrics), rich annotations, 100% schema coverage, and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It covers purpose, source, update frequency, and return structure, leaving no significant gaps for the agent to understand and use the tool effectively.

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 ('query' and 'limit'). The description does not add any parameter-specific semantics beyond what the schema provides, such as query syntax examples or limit usage guidance. With high schema coverage, the baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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 specific action ('Search the Istanbul Metropolitan Municipality (IBB) open data portal for public datasets'), identifies the resource ('public datasets'), and distinguishes it from siblings by specifying the source ('Istanbul Metropolitan Municipality (Open Data)'). It avoids tautology and provides a precise verb+resource combination.

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 implicitly provides usage context by stating the source and update frequency ('updates daily'), which helps determine when to use it. However, it does not explicitly mention when not to use it or name alternatives among the many sibling tools, such as other government data tools like 'government__data-uk' or 'government__datagov'.

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