Katzilla MCP

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

Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds valuable context beyond annotations: it specifies the data source (openFDA, CC0 license), update frequency (daily), and the return format (Katzilla envelope with data, quality scores, and citation details including SHA-256 hash). This enhances transparency about data freshness, auditability, and output structure, though it doesn't detail rate limits or error handling.

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. Every sentence adds value: specifying the return content, data source, update frequency, and output format. It is efficient with no redundant information, making it easy 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 complexity (search functionality with two parameters), rich annotations (read-only, idempotent, etc.), and the presence of an output schema (implied by the description of the Katzilla envelope), the description is complete. It covers purpose, usage context, behavioral traits, and output details, leaving no significant gaps for an AI agent to understand and invoke the tool correctly.

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%, with clear descriptions for both parameters (limit and query). The description does not add any additional semantic details about parameters beyond what the schema provides, such as query syntax examples or how the limit interacts with pagination. Since the schema is comprehensive, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 tool's purpose: 'Search FDA drug adverse event reports (FAERS).' It specifies the resource (FDA adverse event reports), the action (search), and the data source (openFDA). It clearly distinguishes itself from siblings like 'health__fda-devices' or 'health__fda-recalls' by focusing on adverse events rather than devices or recalls.

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 FDA adverse event reports, including side effects, patient reactions, and drug info. It mentions the source (openFDA) and update frequency (daily), which helps in timing decisions. However, it does not explicitly state when not to use it or name specific alternatives among siblings, though the context implies it's for adverse events specifically.

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