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 (Hipolabs Free API), update frequency (monthly), and detailed return format (Katzilla envelope with quality scores and citation details). Annotations cover read-only, non-destructive, idempotent, and open-world hints, so the description complements them without contradiction, enhancing transparency.

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 essential operational details (source, updates, return format). Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.

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 filtering), rich annotations (read-only, idempotent, etc.), and the presence of an output schema, the description is complete. It covers purpose, usage context, behavioral traits, and return format, leaving no significant gaps for the agent to operate 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?

The input schema has 100% description coverage, with clear parameter descriptions ('Country name', 'University name'). The description adds no additional parameter semantics beyond implying filtering by country/name, which is already evident from the schema. This meets the baseline of 3 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 clearly states the tool's purpose with a specific verb ('Search'), resource ('universities worldwide'), and scope ('by country and/or name'). It distinguishes itself from sibling tools like 'education__hipolabs-universities' by specifying the international focus and data source (Hipolabs API), avoiding redundancy.

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 usage ('Search universities worldwide by country and/or name') and mentions the data source and update frequency, which helps set expectations. However, it does not explicitly state when not to use this tool or name specific alternatives among the many sibling tools, which would be needed for a score of 5.

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