Katzilla MCP

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

Annotations already indicate this is a read-only, non-destructive, idempotent, and open-world operation. The description adds valuable context beyond this: it specifies the return format ('Katzilla envelope { data, quality, citation }'), explains quality metrics ('freshness/uptime/confidence'), and details citation components ('source URL, license, SHA-256 data hash'). This enriches the agent's understanding of 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 covers purpose and source, the second details the return format and its components. Every phrase adds necessary information without redundancy, making it easy for an agent to parse quickly.

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 moderate complexity (search with two parameters), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It explains the tool's purpose, usage context, return structure, and data quality aspects, leaving no significant gaps for the agent.

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%, so the schema fully documents the two parameters ('query' and 'limit'). The description adds minimal semantic value beyond the schema: it notes that omitting 'query' returns recent datasets, which is implied but not explicit in the schema's 'optional' note. This meets the baseline 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 specific action ('Search openAFRICA'), resource ('dataset metadata from governments, NGOs, and researchers'), and scope ('largest independent open data portal on the African continent'). It distinguishes itself from sibling tools by focusing on African open data, unlike other culture tools like 'culture__met-museum' or 'culture__open-library'.

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 when to use this tool: searching for African open data datasets. It implies usage by mentioning the source and update frequency ('updates daily'), but does not explicitly state when not to use it or name alternative tools for similar data from other regions, 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.