MCP Math Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description states that the tool 'Get NaN,' implying it returns a value, but does not specify what type of value (e.g., a float constant), any side effects, or error conditions. It lacks details on how NaN is represented or any limitations, which is insufficient for a tool with no 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 concise and well-structured in a single sentence: 'Get NaN (Not a Number). Represents undefined or invalid mathematical operations. (Domain: arithmetic, Category: general).' It front-loads the core purpose and efficiently adds context without unnecessary details. However, the parenthetical domain and category could be integrated more smoothly.

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, no output schema, no annotations), the description is adequate but has gaps. It explains what NaN is and its domain, but does not cover behavioral aspects like return format or usage context relative to siblings. For a tool in a server with many mathematical functions, more guidance on when to use it would improve completeness.

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 0 parameters with 100% coverage, so no parameter information is needed. The description does not mention parameters, which is appropriate. It adds value by explaining what NaN represents, but since there are no parameters, a baseline score of 4 is applied as it meets the requirement without redundancy.

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 NaN (Not a Number).' It specifies the verb ('Get') and the resource ('NaN'), and explains what NaN represents ('undefined or invalid mathematical operations'). However, it does not explicitly differentiate this tool from sibling tools like 'is_nan', which likely checks if a value is NaN rather than retrieving NaN itself.

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 minimal guidance on when to use this tool. It mentions the domain ('arithmetic') and category ('general'), but does not specify scenarios or alternatives. For example, it does not clarify when to use this tool versus a constant like 'infinity' or other mathematical operations, nor does it explain its role among sibling tools such as 'is_nan'.

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