Katzilla MCP

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

Annotations already cover key behavioral traits (readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true). The description adds valuable context beyond annotations: it specifies the data source (Art Institute of Chicago), update frequency ('updates daily'), licensing (CC0 1.0 for metadata), and details about the return envelope structure ('Katzilla envelope { data, quality, citation }') with quality scoring and citation components. 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 in two sentences: the first covers the tool's purpose and return data, and the second adds source, licensing, update frequency, and envelope details. Every sentence provides essential information with zero waste, making it highly concise and well-organized.

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 metadata returns), the description is complete. It explains what the tool does, the data source, licensing, update frequency, and the structure of the return envelope. With annotations covering safety and idempotency, and an output schema presumably detailing the envelope structure, no critical information is missing for effective agent use.

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 documentation for both parameters ('query' and 'limit'). The description does not add any parameter-specific semantics beyond what the schema already provides (e.g., it doesn't clarify search syntax or result ordering). Given the high schema coverage, a baseline score of 3 is appropriate.

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 ('Search'), the resource ('Art Institute of Chicago's collection of over 300,000 artworks'), and the return content ('artwork metadata including artist, date, medium, and image links'). It clearly distinguishes this from sibling tools by specifying the unique cultural dataset (AIC artworks), unlike other culture tools like 'culture__met-museum' or 'culture__smithsonian'.

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: for searching AIC's artwork collection. However, it does not explicitly state when not to use it or name specific alternatives among the many sibling tools (e.g., 'culture__met-museum' for another museum's collection), 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.