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. It discloses that the tool returns a constant value (G ≈ 0.91597) and its mathematical definition, which is useful behavioral context. However, it does not mention any side effects, performance characteristics, or error conditions, which are typical gaps for a tool with zero annotation coverage.

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 highly concise and front-loaded: it immediately states the tool's purpose in the first phrase, followed by the constant's value and series representation, and ends with domain/category tags. Every sentence adds value without redundancy, 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 simplicity (0 parameters, no output schema, no annotations), the description is nearly complete: it explains what the tool does, provides the constant's value and mathematical definition, and includes domain/category context. The only minor gap is the lack of explicit output format details, but for a constant-retrieval tool, this is acceptable.

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 documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's output and mathematical background, which aligns with the schema's completeness.

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: 'Get Catalan's constant G ≈ 0.91597.' It specifies the exact mathematical constant being retrieved, distinguishes it from sibling tools like 'catalan_number' and 'catalan_sequence' by focusing on the constant value rather than sequences or numbers, and provides the specific alternating series representation for clarity.

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 includes context with 'Domain: arithmetic, Category: general,' which implicitly guides usage toward mathematical constant retrieval in arithmetic contexts. However, it does not explicitly state when to use this tool versus alternatives (e.g., other constant tools like 'e' or 'pi'), nor does it provide exclusions or prerequisites, leaving some ambiguity in sibling differentiation beyond the purpose statement.

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