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. It states the tool finds numbers 'up to limit,' implying a search operation, but does not describe output format (e.g., list structure), performance characteristics (e.g., computational complexity for large limits), or error handling. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 front-loaded, with the core purpose stated first: 'Find all vampire numbers up to limit.' The additional domain/category tags are brief and relevant. There is no unnecessary verbosity, and every sentence contributes to understanding, though the structure could be slightly improved by integrating the tags more seamlessly.

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 complexity (finding special numbers), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It does not explain what vampire numbers are, how they are returned, or any algorithmic details. While the domain/category tags help, they are insufficient for an agent to fully understand the tool's operation and results without external knowledge.

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 one parameter ('limit') with 0% description coverage, so the schema provides no semantic context. The description adds value by clarifying that 'limit' defines the upper bound for finding vampire numbers, but it does not specify constraints (e.g., must be positive integer) or units. This partial compensation aligns with the baseline for low schema coverage, but more detail would improve usability.

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: 'Find all vampire numbers up to limit.' It specifies the verb ('Find'), resource ('vampire numbers'), and scope ('up to limit'), making the action unambiguous. However, it does not differentiate from sibling tools like 'is_vampire_number' (which tests individual numbers) or other number-finding tools (e.g., 'armstrong_numbers'), so it falls short of a perfect score.

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 usage guidance. It includes domain/category tags ('Domain: arithmetic, Category: special_numbers'), which imply context but do not explicitly state when to use this tool versus alternatives like 'is_vampire_number' or other number generators. There is no mention of prerequisites, limitations, or comparisons to sibling tools, leaving the agent with insufficient direction.

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