mcp-sympy

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

No annotations are provided, so the description must fully disclose behavioral traits, but it fails to do so. 'Get coefficient' implies a read-only operation, but it doesn't clarify if this is a pure computation, whether it has side effects, error handling, or performance characteristics. The description adds no behavioral context beyond the minimal implication of retrieval.

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?

While concise with two words, the description is under-specified rather than efficiently structured. It lacks front-loaded essential information and fails to earn its place by providing insufficient detail for a tool with three parameters and complex sibling context, making it ineffective despite brevity.

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 symbolic mathematics tools and the presence of an output schema, the description is incomplete. It doesn't explain what a 'coefficient' means in this context, how results are returned, or tie into the broader SymPy ecosystem. With no annotations and minimal description, it leaves significant gaps for agent understanding.

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%, with clear parameter descriptions ('Expression', 'Variable', 'Power of x'), so the schema does the heavy lifting. The description adds no additional meaning beyond what the schema provides, such as examples or constraints on input formats, but the high coverage justifies 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 'Get coefficient' is a tautology that essentially restates the tool name 'sympy_coeff' without providing meaningful context. It doesn't specify what type of coefficient (e.g., polynomial coefficient, series coefficient) or from what mathematical expression, nor does it distinguish this tool from sibling tools like 'sympy_degree' or 'sympy_poly' which might also relate to polynomial analysis.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools for symbolic mathematics (e.g., 'sympy_degree', 'sympy_poly', 'sympy_expand'), the description offers no context about specific use cases, prerequisites, or comparisons, leaving the agent to guess based on parameter names alone.

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