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daffamumtaz2361

safe-mathjs-mcp

Evaluate Expression

evaluate

Evaluate mathematical expressions in one call, supporting variables, functions, and array operations for statistics and linear algebra.

Instructions

Evaluate a mathematical expression in one call. Supports + - * / ^ % ! and parentheses; array literals like [1,2,3] for statistics and [[1,2],[3,4]] for linear algebra. Functions: sqrt, cbrt, abs, pow, exp, log, ln, log10, log2, nthRoot, gcd, lcm, factorial, sign, hypot, mod, sin, cos, tan, asin, acos, atan, atan2, sinh, cosh, tanh, floor, ceil, round, min, max, isPrime, combinations, permutations, mean, median, std, sum, prod, variance, mode, det, inv, transpose, norm, dot, cross. Constants: pi, e, tau. Pass named values via 'variables' (e.g. { x: 2 }) to reference them in the expression. Example: '2 * (12 + sqrt(255))^2'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
precisionNoSignificant digits for the result (default: 10)
variablesNoNamed values to substitute into the expression, e.g. { x: 2, y: 255 }. Keys must be valid variable names.
expressionYesA mathematical expression, e.g. '2 * (12 + sqrt(255))^2'. Use * for multiplication and ^ for exponentiation.
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals supported operations, array literals, and variable-passing mechanics, but omits the return format (e.g., number vs array), error behavior for invalid expressions, and how precision affects the result.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single dense paragraph with no wasted words; the first sentence states purpose, followed by operators, functions, constants, variables, and an example. While the long function list could be better structured with bullet points, it is still efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with three parameters and no output schema, the description thoroughly covers input syntax and capabilities. However, it does not explain the return value shape (especially for array operations) or edge-case behavior, leaving some gaps for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for all three parameters, providing a baseline of 3. The description adds meaningful semantics by explaining how to use the 'variables' parameter (e.g., { x: 2 }) and by detailing valid expression syntax with an example, exceeding the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States 'Evaluate a mathematical expression in one call' with a clear verb and resource. The extensive list of operators, functions, and constants further clarifies the tool's exact scope. However, it does not explicitly differentiate from sibling tools simplify and derivative, so it stops short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides rich 'how-to' guidance (supported operators, functions, variables, and an example) but no 'when-to-use' guidance. It does not mention alternatives like simplify or derivative or indicate scenarios where evaluation is preferred over them.

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

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