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 states 'compute' but doesn't disclose behavioral traits like whether it's a read-only operation, if it requires specific matrix properties (e.g., square matrices), error conditions, or output format. This is inadequate for a tool with no annotation coverage.

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, efficient sentence with zero wasted words. It's appropriately sized for a simple computational tool and front-loads the core purpose immediately.

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 low complexity (single parameter, 100% schema coverage, output schema exists), the description is minimally adequate. However, with no annotations and many sibling tools, it lacks context about when to use it and behavioral details, making it incomplete for optimal agent guidance.

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 the single parameter 'matrix' well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 where the schema does the heavy lifting.

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 verb 'compute' and the resource 'matrix determinant', making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'sympy_matrix_inverse' or 'sympy_matrix_rank' that also operate on matrices, missing explicit sibling distinction.

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 matrix operations (e.g., sympy_matrix_inverse, sympy_matrix_rank), there's no indication of when determinant computation is appropriate or what prerequisites might be needed.

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