Katzilla MCP

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

Annotations indicate read-only, non-destructive, idempotent, and open-world operations. The description adds valuable context beyond annotations: it specifies the return format ('Returns the Katzilla envelope { data, quality, citation }'), explains quality metrics ('freshness/uptime/confidence'), and details citation components ('source URL, license, SHA-256 data hash'). This enriches behavioral 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 states the purpose and key details, and the second explains the return format and its components. Every sentence adds essential information without redundancy, making it front-loaded and appropriately sized for the tool's complexity.

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 simplicity (one parameter, high schema coverage, annotations provided, and an output schema), the description is complete. It covers purpose, usage context, behavioral traits, and return format, leaving no gaps. The presence of an output schema means the description does not need to detail return values, and it adequately supplements the structured data.

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 'din' fully documented. The description adds minimal semantics beyond the schema, only implying the DIN is used for lookup. Since the schema carries the burden, the baseline score of 3 is appropriate, as the description does not significantly enhance parameter understanding.

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: 'Look up drugs in Health Canada's Drug Product Database (DPD) by Drug Identification Number (DIN).' It specifies the verb ('look up'), resource ('drugs'), and scope ('Health Canada's Drug Product Database'), distinguishing it from sibling tools that focus on other domains like agriculture, consumer, or economic data.

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: 'by Drug Identification Number (DIN)' and mentions the source and update frequency ('Source: Health Canada, updates daily'). However, it does not explicitly state when not to use this tool or name alternatives among siblings, such as other health-related tools like 'health__cdc-data' or 'health__fda-recalls', which serve different purposes.

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