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 this: it specifies the data source ('Climate TRACE (CC-BY 4.0)'), update frequency ('updates daily'), and return structure ('Katzilla envelope { data, quality, citation }'), including details on quality scores and citation components, which are not covered by 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 front-loaded with the core purpose, followed by source, update frequency, and return details in a compact two-sentence format. Every sentence adds essential information without redundancy, making it highly efficient.

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 (4 parameters, 100% schema coverage, annotations, and an output schema), the description is complete. It covers purpose, source, update behavior, and return structure, compensating well for any gaps and aligning with the structured data provided.

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 all parameters. The description does not add any parameter-specific details beyond what the schema provides, such as explaining the 'sector' enum values or 'since'/'to' defaults, but it implies the tool's purpose aligns with these 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 explicitly states the action ('Get sector-level greenhouse gas emissions data'), resource ('from Climate TRACE'), and scope ('broken down by industry sectors'), clearly distinguishing it from sibling tools like 'environment__climate-trace' or 'environment__climate-trace-assets' by focusing on sector-level data.

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 ('updates daily') and implies when to use it (for sector-level emissions data), but does not explicitly state when not to use it or name specific alternatives among siblings, such as 'environment__climate-trace' for broader data.

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