mcp-sympy

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions 'evaluate expression numerically' but doesn't disclose behavioral traits such as precision handling, error conditions, or output format. For a tool with numerical evaluation, this lack of detail on behavior is a significant gap.

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 that directly states the tool's function. It's front-loaded and wastes no words, making it efficient for quick understanding 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 tool's complexity (numerical evaluation with parameters), the description is minimal. While an output schema exists (which helps), the lack of annotations and insufficient behavioral context in the description leaves gaps. It's adequate but could be more complete for effective tool 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?

Schema description coverage is 100%, so the schema already documents both parameters ('expr' and 'n') adequately. The description doesn't add any meaning beyond what the schema provides, such as examples or constraints on expression format, resulting in a baseline score of 3.

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 with a specific verb ('evaluate') and resource ('expression'), and specifies it's done 'numerically'. However, it doesn't distinguish this from sibling tools like 'sympy_evalf' or 'sympy_float' which might have similar numerical evaluation functions, missing explicit differentiation.

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 in the SymPy server, there's no indication of when 'sympy_n' is appropriate compared to other numerical or symbolic evaluation tools, leaving the agent without context for selection.

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