Katzilla MCP

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

The annotations already provide excellent behavioral hints (readOnlyHint: true, destructiveHint: false, idempotentHint: true, openWorldHint: true). The description adds valuable context beyond these annotations: it specifies the data source (NHTSA), update frequency (daily), and describes the return format (Katzilla envelope with quality scores and citation details including SHA-256 hash). This provides important operational context that annotations alone don't convey.

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 core functionality and parameters, the second provides source metadata and output format details. Every element serves a purpose - there's no redundant information, and it's appropriately front-loaded with the primary use case.

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, comprehensive annotations (readOnly, non-destructive, idempotent, openWorld), 100% schema coverage, and the presence of an output schema, the description provides excellent contextual completeness. It covers purpose, source, update frequency, and output structure - addressing all key aspects an agent needs 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?

The input schema has 100% description coverage with clear parameter documentation (make, model, year with examples and defaults). The description mentions these parameters ('by make, model, and year') but doesn't add significant semantic value beyond what the schema already provides. It doesn't explain parameter interactions, constraints, or provide additional usage context for the parameters.

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 specific action ('Search vehicle safety complaints'), resource ('filed with the National Highway Traffic Safety Administration'), and scope ('by make, model, and year'). It distinguishes from sibling tools like 'transport__nhtsa-recalls' and 'transport__nhtsa-safety-ratings' by focusing specifically on complaints rather than recalls or ratings.

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 about when to use this tool ('Search vehicle safety complaints... by make, model, and year') and mentions the data source and update frequency. However, it doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools, though the context implies it's for complaint data rather than recalls or ratings.

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