Katzilla MCP

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

Annotations cover read-only, non-destructive, idempotent, and open-world hints, but the description adds valuable behavioral context beyond this: it specifies the data source ('Carbon Intensity API (National Grid ESO)'), update frequency ('updates daily'), and return structure ('Katzilla envelope { data, quality, citation }') with details on quality scoring and citation content. 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 front-loaded with the core purpose in the first sentence, followed by essential details in a structured manner (source, update frequency, return format). Every sentence adds value without redundancy, making it efficient and easy to parse.

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 simplicity (0 parameters, annotations provided, output schema exists), the description is complete. It covers purpose, source, update frequency, and return structure, compensating for any gaps. With an output schema, it need not explain return values in detail, making this description sufficient for the agent's needs.

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 0 parameters and 100% schema description coverage, the schema fully documents the inputs. The description adds no parameter-specific information, which is appropriate, but it does imply the tool requires no inputs for its operation, aligning with the schema. Baseline is 4 for zero parameters, as no additional semantics are needed.

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 specific verbs ('Get the current carbon intensity') and resources ('UK electricity generation from the National Grid ESO'), clearly distinguishing it from sibling tools like environment__climate-trace or environment__openaq by focusing on UK electricity carbon intensity from a specific source.

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 ('Get the current carbon intensity of UK electricity generation'), implying it's for real-time or daily-updated UK-specific data. However, it does not explicitly state when not to use it or name alternatives among siblings, such as environment__climate-trace for broader climate data.

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