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. 'Binomial coefficient' implies a mathematical computation but does not specify whether it's read-only, if it handles symbolic inputs, error conditions (e.g., invalid n/k values), or output format. This is inadequate for a tool with no annotation coverage, as it misses key behavioral traits.

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 phrase, which is efficient and front-loaded. However, it is under-specified rather than appropriately detailed, as it lacks necessary context. While not wasteful, it fails to provide sufficient information, slightly reducing the score.

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 mathematical nature, 2 parameters, 100% schema coverage, and an output schema (implied by context signals), the description is minimally adequate. However, it lacks details on usage, behavioral traits, and differentiation from siblings, making it incomplete for optimal agent guidance. The presence of an output schema mitigates some gaps.

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 descriptions for 'n' and 'k' as non-negative integers. The description adds no parameter semantics beyond what the schema provides, but since the schema is comprehensive, the baseline score of 3 is appropriate. No additional value is contributed by the description.

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 'Binomial coefficient' is a tautology that merely restates the tool name without specifying the action. It does not clarify what the tool does (e.g., compute, evaluate, or calculate the binomial coefficient), nor does it differentiate from sibling tools like 'sympy_factorial' or 'sympy_gcd', which are also mathematical functions. This lacks a clear verb and resource specification.

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. It does not mention context, prerequisites, or comparisons with sibling tools (e.g., for combinatorial calculations or symbolic math operations). The description offers no usage instructions, leaving the agent without direction.

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