Katzilla MCP

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

The description adds valuable behavioral context beyond what annotations provide: it discloses the data source (openFDA), licensing (CC0), update frequency (daily), and the specific return format ('Katzilla envelope { data, quality, citation }') with details about quality scoring and citation contents. While annotations cover read-only, non-destructive, idempotent, and open-world hints, the description enriches this with practical implementation details.

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 purpose, scope, source, and update frequency; the second details the return format and its components. Every element serves a clear purpose with zero wasted words, making it easy to parse while being information-dense.

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 moderate complexity (2 parameters, search functionality), rich annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), and the existence of an output schema, the description is complete. It covers purpose, data source, update frequency, return format structure, and quality metrics - providing all necessary context for an agent to understand when and how to use this 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?

With 100% schema description coverage, the input schema already fully documents both parameters ('limit' and 'query'). The description doesn't add any parameter-specific semantics beyond what's in the schema - it mentions 'search query to filter recalls' which merely restates the schema's description for the query parameter. Baseline score of 3 is appropriate when schema does the heavy lifting.

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 with specific verbs ('Search FDA drug enforcement/recall reports') and resources ('FDA drug enforcement/recall reports'), distinguishing it from sibling tools like 'health__fda-adverse-events' or 'health__fda-devices' by focusing specifically on recalls. It also specifies the data source (openFDA) and update frequency (daily).

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 ('Search FDA drug enforcement/recall reports'), but doesn't explicitly state when not to use it or name specific alternatives among the many sibling tools. It implies usage for recall data needs without contrasting with other FDA or recall-related tools like 'consumer__cpsc-recalls' or 'transport__nhtsa-recalls'.

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