math-tools

Math Tools

Deterministic mathematical computation engine using SymPy. All calculations use symbolic math - no LLM estimation.

When to Use

Use this skill whenever mathematical accuracy matters:

• Arithmetic involving fractions, roots, or large numbers
• Algebraic simplification, expansion, factoring
• Solving equations (polynomial, transcendental, systems)
• Calculus (derivatives, integrals, limits, series)
• Linear algebra (matrices, eigenvalues, determinants)
• Number theory (primes, factorization, GCD/LCM)
• Statistical calculations

Quick Start

Run the calculator script with operation and arguments:

python scripts/math_calculator.py <operation> <args...>

All results return JSON with result, latex, and numeric fields.

Core Operations

Arithmetic

python scripts/math_calculator.py add 5 3 2          # 10
python scripts/math_calculator.py multiply 2 3 4    # 24
python scripts/math_calculator.py divide 10 4       # 5/2 (exact)
python scripts/math_calculator.py sqrt 8            # 2*sqrt(2)
python scripts/math_calculator.py factorial 10      # 3628800

Algebra

# Simplify
python scripts/math_calculator.py simplify "(x**2 - 1)/(x - 1)"
# → x + 1

# Expand
python scripts/math_calculator.py expand "(x + 1)**3"
# → x**3 + 3*x**2 + 3*x + 1

# Factor
python scripts/math_calculator.py factor "x**3 - 8"
# → (x - 2)*(x**2 + 2*x + 4)

# Solve equations
python scripts/math_calculator.py solve "x**2 - 5*x + 6" x
# → [2, 3]

python scripts/math_calculator.py solve "2*x + 3 = 7" x
# → [2]

Calculus

# Derivative
python scripts/math_calculator.py derivative "x**3 + sin(x)" x
# → 3*x**2 + cos(x)

# Second derivative
python scripts/math_calculator.py derivative "x**4" x 2
# → 12*x**2

# Indefinite integral
python scripts/math_calculator.py integrate "x**2" x
# → x**3/3

# Definite integral
python scripts/math_calculator.py integrate "x**2" x 0 1
# → 1/3

# Limit
python scripts/math_calculator.py limit "sin(x)/x" x 0
# → 1

# Limit at infinity
python scripts/math_calculator.py limit "(x**2 + 1)/(x**2 - 1)" x oo
# → 1

# Taylor series
python scripts/math_calculator.py series "exp(x)" x 0 5
# → 1 + x + x**2/2 + x**3/6 + x**4/24 + O(x**5)

Linear Algebra

# Determinant
python scripts/math_calculator.py det '[[1,2],[3,4]]'
# → -2

# Inverse
python scripts/math_calculator.py inverse '[[1,2],[3,4]]'

# Eigenvalues
python scripts/math_calculator.py eigenvalues '[[4,2],[1,3]]'
# → {5: 1, 2: 1}

# RREF
python scripts/math_calculator.py rref '[[1,2,3],[4,5,6]]'

Number Theory

python scripts/math_calculator.py gcd 24 36 48       # 12
python scripts/math_calculator.py lcm 4 6 8         # 24
python scripts/math_calculator.py prime_factors 360  # 2^3 × 3^2 × 5
python scripts/math_calculator.py is_prime 17       # true
python scripts/math_calculator.py nth_prime 100     # 541
python scripts/math_calculator.py binomial 10 3     # 120

Statistics

python scripts/math_calculator.py mean '[1,2,3,4,5]'      # 3
python scripts/math_calculator.py variance '[1,2,3,4,5]'  # 2
python scripts/math_calculator.py std_dev '[1,2,3,4,5]'   # sqrt(2)

Utilities

# Numerical evaluation with precision
python scripts/math_calculator.py evaluate "pi" 50

# LaTeX output
python scripts/math_calculator.py latex "x**2 + 1/x"
# → x^{2} + \frac{1}{x}

# Compare expressions
python scripts/math_calculator.py compare "(x+1)**2" "x**2 + 2*x + 1"
# → equal: true

Expression Syntax

• Powers: x**2 or x^2
• Multiplication: 2*x or 2x (implicit)
• Functions: sin(x), cos(x), exp(x), log(x), sqrt(x)
• Constants: pi, E, I (imaginary), oo (infinity)

Complex Operations (JSON Input)

For operations requiring structured input:

# Solve system of equations
python scripts/math_calculator.py solve_system \
  '{"equations": ["x + y = 10", "x - y = 2"], "variables": ["x", "y"]}'

# Substitute values
python scripts/math_calculator.py substitute \
  '{"expr_str": "x**2 + y", "substitutions": {"x": 3, "y": 2}}'

# Matrix multiplication
python scripts/math_calculator.py matrix_mult \
  '{"matrix_a": [[1,2],[3,4]], "matrix_b": [[5,6],[7,8]]}'

Full API Reference

See references/api_reference.md for complete documentation of all operations, including:

• All operation names and aliases
• Detailed parameter descriptions
• Output format specifications
• Additional examples

Dependencies

Requires SymPy:

pip install sympy