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. 'Random matrix' does not reveal any behavioral traits such as whether the matrix entries are integers or floats, the distribution used (e.g., uniform, normal), the range of values, if the matrix is square or rectangular, or any side effects. This is inadequate for a tool that generates random data.

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 just two words, which is appropriately sized for such a minimal statement. It is front-loaded and wastes no words, though this brevity contributes to its inadequacy in other dimensions.

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 generating random matrices, the lack of annotations, low schema coverage, and no output schema explanation in the description, this description is incomplete. It does not provide enough context for an agent to understand the tool's behavior, parameters, or output, making it insufficient for effective 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 one parameter 'n' with 0% description coverage, and the tool description adds no information about parameters. It does not explain what 'n' represents (e.g., matrix dimension, size, or other property), its constraints, or how it influences the output. With low schema coverage, the description fails to compensate, leaving the parameter undocumented.

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 'Random matrix' is a tautology that essentially restates the tool name 'sympy_randMatrix'. It does not specify what the tool actually does (e.g., generates a random matrix of given dimensions with optional properties like integer entries, specific range, or symmetry). While it mentions the resource ('matrix'), it lacks a clear verb and does not distinguish it from sibling tools like sympy_zeros or sympy_ones that also create matrices.

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. It does not mention any context, prerequisites, or comparisons to sibling tools (e.g., sympy_zeros for zero matrices, sympy_ones for ones matrices, or sympy_matrix for creating custom matrices). This leaves the agent without direction on appropriate usage scenarios.

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