Katzilla MCP

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

The description adds valuable behavioral context beyond annotations: it discloses the data source ('FIPE / Parallelum API (Public)'), update frequency ('updates daily'), and return format ('Katzilla envelope { data, quality, citation }') with details on quality scoring and citation contents. Annotations already cover read-only, non-destructive, idempotent, and open-world hints, so the description appropriately supplements with operational details without contradicting them.

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 source, update frequency, and return format. 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 moderate complexity, rich annotations (read-only, non-destructive, idempotent, open-world), and the presence of an output schema, the description is complete. It covers purpose, source, update frequency, and return structure, compensating well for any gaps. With an output schema handling return values, the description need not explain them further, making it sufficiently comprehensive.

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%, so the schema fully documents the two parameters (type with enum and default, brandId with its purpose). The description adds no additional parameter semantics beyond what the schema provides, such as examples or edge cases, but this is acceptable given the high schema coverage, resulting in a baseline score of 3.

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 ('Get Brazilian vehicle pricing data', 'List brands or get model details') and resources ('from FIPE', 'for cars, motorcycles, and trucks'). It distinguishes itself from sibling tools by focusing on Brazilian vehicle pricing data, unlike other transport tools that cover different regions or data types (e.g., transport__bc-ferries, transport__bts-stats).

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 the tool ('Get Brazilian vehicle pricing data from FIPE'), but does not explicitly state when not to use it or name specific alternatives. It implies usage for vehicle pricing queries in Brazil, but lacks explicit exclusions or comparisons to other tools that might handle similar data (e.g., consumer or economic tools).

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