Katzilla MCP

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

Annotations cover read-only, non-destructive, idempotent, and open-world hints, but the description adds valuable context: it specifies the data source (Smithsonian Institution, CC0), update frequency (daily), and details about the return format (Katzilla envelope with quality scores and citation info including SHA-256 hash). This enhances transparency beyond the annotations 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 a structured manner. Every sentence adds essential information (e.g., data source, update frequency, return format), with no wasted words, making it highly efficient.

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 structured returns), the description is complete: it covers purpose, source, update frequency, and detailed return format. With annotations providing safety hints and an output schema existing, no further explanation of behavior or return values is needed, making it fully adequate.

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 'query' and 'limit' parameters. The description does not add any additional meaning or syntax details for these parameters beyond what the schema provides, meeting the baseline for high 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 explicitly states the action ('Search'), the resource ('Smithsonian Institution's Open Access collection of art, artifacts, and scientific specimens'), and distinguishes it from siblings by specifying the source and data type (e.g., different from 'culture__aic-artworks' or 'culture__met-museum'). It clearly defines the tool's function beyond a tautology.

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 Smithsonian collections) and implies alternatives by mentioning the specific source and data format. However, it does not explicitly name when not to use it or list specific sibling alternatives, keeping it at a high but not perfect score.

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