A central tool that routes complex mathematical tasks to specialized solvers like SymPy or Z3.
Install
mkdir -p .claude/skills/math && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1086" && unzip -o skill.zip -d .claude/skills/math && rm skill.zipInstalls to .claude/skills/math
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Unified math capabilities - computation, solving, and explanation. I route to the right tool.Key capabilities
- →Solve algebraic equations
- →Compute derivatives and integrals
- →Perform matrix operations
- →Verify logical propositions
- →Convert units
How it works
It routes requests to specialized Python scripts using SymPy for symbolic math, Z3 for constraint solving, or Pint for unit conversion.
Inputs & outputs
When to use math
- →Solving algebraic equations
- →Calculating derivatives or integrals
- →Performing matrix operations
- →Verifying logical propositions
- →Converting units
About this skill
/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.
When not to use it
- →Machine-verified formal proofs
- →Category theory proofs
Prerequisites
Limitations
- →Limited to supported libraries
- →Requires specific command syntax for complex operations
How it compares
It automates the selection of the correct mathematical engine based on the input query instead of requiring manual tool selection.
Compared to similar skills
math side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| math (this skill) | 10 | 7mo | Review | Beginner |
| quant-analyst | 103 | 2mo | No flags | Advanced |
| umap-learn | 6 | 2mo | Review | Intermediate |
| embedding-strategies | 8 | 2mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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