mcp-sympy

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. While 'Check' implies a read-only operation, the description doesn't specify any behavioral traits such as performance characteristics, input constraints beyond being an integer, error handling, or output format. This leaves significant gaps for a tool with no 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 extremely concise with a single sentence 'Check if n is prime.' that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it highly efficient for quick understanding.

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 (one parameter, 100% schema coverage, output schema exists), the description is minimally adequate. However, with no annotations and many sibling tools, it lacks context on usage distinctions and behavioral details. The existence of an output schema means return values are documented elsewhere, but the description doesn't fully compensate for the missing annotation context.

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 schema description coverage is 100%, with the parameter 'n' documented as 'Integer' in the schema. The description adds no additional semantic information beyond what the schema provides (e.g., no details on valid ranges, special cases like negative numbers, or format requirements). This meets the baseline score when the schema does 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 'Check if n is prime' clearly states the tool's purpose with a specific verb ('Check') and resource ('n'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'sympy_is_square' or 'sympy_perfect_power', which also perform mathematical property checks, so it doesn't reach the highest 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 no guidance on when to use this tool versus alternatives. With many sibling tools performing similar mathematical checks (e.g., 'sympy_is_square', 'sympy_perfect_power'), there's no indication of when this specific prime-checking tool is appropriate or what distinguishes it from other verification functions.

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