Katzilla MCP

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable context beyond this: it specifies the data source (Fruityvice Free API), update frequency (monthly), and details about the return format (Katzilla envelope with quality scores and citation info including SHA-256 hash). This enhances transparency about data freshness, reliability, and auditability.

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 in the first sentence, followed by additional context in a structured manner. It efficiently conveys source, update frequency, and return format without unnecessary words, making every sentence contribute essential information.

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 (simple read operation with one optional parameter), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It adds necessary context about data source, update frequency, and return structure, compensating for any gaps and ensuring the agent has sufficient information to 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?

The input schema has 100% description coverage, with the parameter 'name' documented as 'Fruit name (omit for all fruits)'. The description does not add further details about parameter usage or semantics beyond what the schema provides. With high schema coverage, the baseline score of 3 is appropriate, as the description relies on the schema for parameter information.

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 ('Get nutritional data about fruits') and the resource ('from Fruityvice'), making the purpose clear. It distinguishes itself from sibling tools by specifying the data domain (fruits/nutrition) and source (Fruityvice API), unlike other tools in the list that cover agriculture, consumer data, crypto, etc.

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 obtaining nutritional data about fruits from the Fruityvice API. It mentions the source and update frequency (monthly), which helps set expectations. However, it does not explicitly state when not to use it or name specific alternatives among the sibling tools, such as agriculture__usda-fooddata for broader food data.

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