Katzilla MCP

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the data source (NHTSA, Public Domain), update frequency (daily), and details about the return structure (quality scores for freshness/uptime/confidence, citation with URL, license, SHA-256 hash). This enhances transparency 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 scope, and the second details the return format and source metadata. Every sentence adds essential information (e.g., rating types, update frequency, return structure) without redundancy, making it front-loaded and concise.

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 (3 parameters, read-only operation), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It covers purpose, source, update frequency, and return format, leaving no significant gaps for agent understanding.

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 defaults and examples for make, model, and year. The description does not add any parameter-specific semantics beyond what the schema provides, such as validation rules or usage tips. With high schema coverage, the baseline score of 3 is appropriate as the schema carries the full burden.

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 with a specific verb ('Get') and resource ('NHTSA NCAP safety ratings for vehicles'), detailing the rating types included (overall, frontal crash, side crash, rollover). It clearly distinguishes from sibling tools like 'transport__nhtsa-complaints' and 'transport__nhtsa-recalls' by focusing on safety ratings rather than complaints 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 usage by specifying the data source (NHTSA), update frequency (daily), and return format (Katzilla envelope). However, it does not explicitly state when to use this tool versus alternatives (e.g., other vehicle data tools) or any prerequisites, leaving some guidance implicit rather than explicit.

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