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, so the description does not need to repeat these. It adds valuable context beyond annotations by specifying the data source (disease.sh), update frequency (daily), and the structure of the return value ('Katzilla envelope { data, quality, citation }') with details on quality scores and citation contents. This enhances transparency about data freshness, auditability, and output format.

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 supporting details in subsequent sentences. Each sentence adds value: the first states what the tool does, the second specifies source and update frequency, and the third explains the return structure. There is no wasted text, making it efficient and well-structured.

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 low complexity (one optional parameter), rich annotations (read-only, idempotent, etc.), and the presence of an output schema (implied by 'Has output schema: true'), the description is complete. It covers purpose, source, update frequency, and return format, providing sufficient context for an agent to understand and use the tool effectively without needing to explain parameters or output details that are already documented elsewhere.

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, fully documenting the 'days' parameter with type, constraints, and default. The description adds no additional parameter semantics beyond what the schema provides, as it only mentions 'over a number of recent days' without further details. With high schema coverage, the baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

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 a specific verb ('Get'), resource ('global COVID-19 vaccine coverage data'), and scope ('over a number of recent days'). It clearly distinguishes itself from siblings by specifying the data source (disease.sh) and type (vaccine coverage), which is unique among the health-related tools listed (e.g., CDC data, FDA recalls, NIH trials).

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 global COVID-19 vaccine coverage data over a number of recent days') and mentions the data source and update frequency ('Source: disease.sh (Open Data), updates daily'), which helps guide usage. However, it does not explicitly state when not to use it or name alternatives (e.g., other health data tools for non-vaccine or non-COVID-19 data), which prevents a perfect score.

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