Katzilla MCP

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

The description adds valuable behavioral context beyond the annotations: it discloses the data source ('disease.sh (Open Data)'), update frequency ('updates daily'), and output structure ('Katzilla envelope { data, quality, citation }'). The annotations already indicate it's read-only, non-destructive, idempotent, and open-world, so the description complements this with practical details 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 explains the output format and additional metadata. 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 simplicity (1 optional parameter, 100% schema coverage, annotations, and an output schema), the description is complete. It covers purpose, source, update frequency, and output structure, which, combined with the structured fields, provides all necessary context for an agent to use the tool effectively.

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 the parameter 'country' documented as 'Country name or ISO code; omit for global stats.' The description does not add further parameter details beyond what the schema provides, such as examples or constraints, so it meets the baseline of 3 where the schema handles the heavy lifting.

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: 'Get global or country-level COVID-19 statistics from the disease.sh API.' It specifies the verb ('Get'), resource ('COVID-19 statistics'), and scope ('global or country-level'), and distinguishes itself from siblings by focusing on COVID-19 data from a specific source, unlike other health tools that cover different datasets (e.g., CDC data, FDA 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: it specifies the data source (disease.sh API), update frequency (daily), and scope (global or country-level). However, it does not explicitly state when to use this tool versus alternatives (e.g., other health tools like 'health__cdc-data' or 'health__who-gho'), nor does it mention any exclusions or prerequisites for use.

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