smithery.ai

math

Unified math capabilities - computation, solving, and explanation. I route to the right tool.

First seen Mar 19, 2026

Installation

$ npx skills add https://smithery.ai

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
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Codex Not declared
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Windsurf Not declared
Gemini CLI Not declared
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Skill metadata

Parsed from SKILL.md frontmatter.

Allowed toolsBash, Read, Write
Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 6,251 B
  • docs SUMMARY.md 105 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 5 installs

SKILL.md

/math - Unified Math Capabilities

One entry point for all computation and explanation. I route to the right tool based on your request.

For formal proofs, use /prove instead.


Quick Examples

You Say I Use
"Solve x² - 4 = 0" SymPy solve
"Integrate sin(x) from 0 to π" SymPy integrate
"Eigenvalues of [[1,2],[3,4]]" SymPy eigenvalues
"Is x² + 1 > 0 for all x?" Z3 prove
"Convert 5 miles to km" Pint
"Explain what a functor is" Category theory skill

Computation Scripts

SymPy (Symbolic Math)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" <command> <args>
Command Description Example
solve Solve equations solve "x**2 - 4" --var x
integrate Definite/indefinite integral integrate "sin(x)" --var x --lower 0 --upper pi
diff Derivative diff "x**3" --var x
simplify Simplify expression simplify "sin(x)2 + cos(x)2"
limit Compute limit limit "sin(x)/x" --var x --point 0
series Taylor expansion series "exp(x)" --var x --point 0 --n 5
dsolve Solve ODE dsolve "f''(x) + f(x)" --func f --var x
laplace Laplace transform laplace "sin(t)" --var t

Matrix Operations:

Command Description
det Determinant
eigenvalues Eigenvalues
eigenvectors Eigenvectors with multiplicities
inverse Matrix inverse
transpose Transpose
rref Row echelon form
rank Matrix rank
nullspace Null space basis
linsolve Linear system Ax=b
charpoly Characteristic polynomial

Number Theory:

Command Description
factor Factor polynomial
factorint Prime factorization
isprime Primality test
gcd Greatest common divisor
lcm Least common multiple
modinverse Modular inverse

Combinatorics:

Command Description
binomial C(n,k)
factorial n!
permutation P(n,k)
partition Integer partitions p(n)
catalan Catalan numbers
bell Bell numbers

Z3 (Constraint Solving)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/z3_solve.py" <command> <args>
Command Use Case
sat Is this satisfiable?
prove Is this always true?
optimize Find min/max subject to constraints

Pint (Units)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/pint_compute.py" convert <value> <from_unit> <to_unit>

Example: convert 5 miles kilometers


Math Router (Auto-Route)

uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/math_router.py" route "<natural language request>"

Returns the exact command to run. Use when unsure which script.


Topic Skills (For Explanation)

When the request is "explain X" or "what is X", I reference these:

Topic Skill Location Key Concepts
Abstract Algebra math/abstract-algebra/ Groups, rings, fields, homomorphisms
Category Theory math/category-theory/ Functors, natural transformations, limits
Complex Analysis math/complex-analysis/ Analytic functions, residues, contour integrals
Functional Analysis math/functional-analysis/ Banach spaces, operators, spectra
Linear Algebra math/linear-algebra/ Matrices, eigenspaces, decompositions
Mathematical Logic math/mathematical-logic/ Propositional, predicate, proof theory
Measure Theory math/measure-theory/ Lebesgue, σ-algebras, integration
Real Analysis math/real-analysis/ Limits, continuity, convergence
Topology math/topology/ Open sets, compactness, connectedness
ODEs/PDEs math/odes-pdes/ Differential equations, boundary problems
Optimization math/optimization/ Convex, LP, gradient methods
Numerical Methods math/numerical-methods/ Approximation, error analysis
Graph/Number Theory math/graph-number-theory/ Graphs, primes, modular arithmetic
Information Theory math/information-theory/ Entropy, coding, channels

Routing Logic

I decide based on your request:

"solve/calculate/compute" → SymPy (exact symbolic)
"is X always true?" → Z3 (constraint proving)
"convert units" → Pint
"explain/what is" → Topic skill for context
"prove formally" → Redirect to /prove

Examples

Solve Equation

User: Solve x² - 5x + 6 = 0
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" solve "x**2 - 5*x + 6" --var x
Result: x = 2 or x = 3

Compute Eigenvalues

User: Find eigenvalues of [[2, 1], [1, 2]]
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" eigenvalues "[[2,1],[1,2]]"
Result: {1: 1, 3: 1}  (eigenvalue 1 with multiplicity 1, eigenvalue 3 with multiplicity 1)

Prove Inequality

User: Is x² + y² ≥ 2xy always true?
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/z3_solve.py" prove "x**2 + y**2 >= 2*x*y"
Result: PROVED (equivalent to (x-y)² ≥ 0)

Convert Units

User: How many kilometers in 26.2 miles?
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/pint_compute.py" convert 26.2 miles kilometers
Result: 42.16 km

When to Use /prove Instead

Use /prove when you need:

  • Machine-verified formal proof (Lean 4)
  • Category theory proofs (functors, Yoneda, etc.)
  • Publication-quality verification
  • Abstract algebra proofs

/math is for computation. /prove is for verification.