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 by specifying the data source license ('CC-BY 4.0'), update frequency ('updates daily'), and details about the return structure ('quality scores freshness/uptime/confidence; citation carries the source URL, license, and a SHA-256 data hash for audit'), enhancing transparency without contradiction.

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 source, and the second details the return format and quality metrics. Every sentence adds essential information without redundancy, making it front-loaded and appropriately sized.

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 (covering safety and idempotency), and the presence of an output schema (implied by 'Has output schema: true'), the description is complete. It explains the data source, update frequency, return structure, and quality aspects, compensating adequately without needing to detail parameters or output values further.

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%, with clear descriptions for all parameters (country, since, to). The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining the implications of the 'since' and 'to' defaults or the data lag mentioned in the schema, so it meets the baseline for high schema coverage.

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 a specific verb ('Get'), resource ('country-level greenhouse gas emissions data'), and source ('Climate TRACE'), distinguishing it from siblings like environment__climate-trace-assets or environment__climate-trace-sectors by focusing on country-level data rather than assets or sectors.

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, update frequency ('updates daily'), and return format ('Katzilla envelope'), but does not explicitly state when to use this tool versus alternatives like environment__epa-ghg or environment__carbon-intensity, nor does it mention exclusions or prerequisites.

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