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. It states the tool solves Diophantine equations but does not disclose behavioral traits like what types of equations are supported, whether it returns all solutions or a subset, error handling, or performance considerations. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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: 'Solve a Diophantine equation.' It is front-loaded and wastes no words, making it easy to parse quickly. Every word earns its place by directly stating the tool's core function without unnecessary elaboration.

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 complexity of solving Diophantine equations, the description is minimal. It lacks details on equation types, solution formats, or error cases. However, with an output schema present, it doesn't need to explain return values, and the input schema is well-covered. The description is adequate as a starting point but incomplete for full understanding without relying on external knowledge or trial.

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, with the 'expr' parameter well-documented in the schema (e.g., format as a SymPy expression equal to zero). The description does not add any additional meaning beyond the schema, such as examples of Diophantine equations or constraints on the expression. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't need to heavily.

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: 'Solve a Diophantine equation.' It specifies the verb ('solve') and the resource ('a Diophantine equation'), making it unambiguous. However, it does not explicitly differentiate from siblings like 'sympy_solve' or 'sympy_solveset', which might also solve equations, leaving some ambiguity about when to use this specific tool.

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 for solving equations (e.g., 'sympy_solve', 'sympy_solveset'), it lacks explicit instructions on when this Diophantine-specific solver is appropriate, such as for integer solutions or polynomial equations, leaving usage context implied at best.

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