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. It states the tool converts an expression to Python code, but doesn't clarify what the output looks like (e.g., a string of Python code, an executable function), whether it handles errors or invalid input, or any performance considerations. This leaves significant gaps in understanding the tool's 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 a single, clear sentence with no wasted words. It is front-loaded and efficiently communicates the core function without unnecessary elaboration, making it easy to parse quickly.

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 has a simple single parameter with full schema coverage and an output schema exists (though not detailed here), the description is minimally adequate. However, it lacks context about the output format, error handling, or how it differs from sibling tools, which reduces completeness for effective agent use.

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 single parameter 'expr' documented as 'SymPy expression string'. The description adds no additional semantic context beyond this, such as examples of valid expressions or formatting requirements. With high schema coverage, the baseline score of 3 is appropriate as the schema adequately defines the parameter.

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 'Convert expression to Python code' clearly states the verb ('Convert') and resource ('expression to Python code'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like sympy_latex (converts to LaTeX) or sympy_str (converts to string), which perform similar conversion operations but to different formats.

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 that also process SymPy expressions (e.g., sympy_latex for LaTeX output, sympy_simplify for simplification), there is no indication of this tool's specific role in converting to executable Python code rather than other representations or transformations.

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