One entry point for all computation and explanation. I route to the right tool based on your request.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmathExecute the skills CLI command in your project's root directory to begin installation:
Fetches math from parcadei/continuous-claude-v3 and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate math. Access via /math in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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One entry point for all computation and explanation. I route to the right tool based on your request.
For formal proofs, use /prove instead.
| 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 |
uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" <command> <args>
| Command | Description | Example |
|---|---|---|
solve |
Solve equations | solve "x**2 - 4" --var x |
integrate |
Definite/indefinite integral | integrate "sin(x)" --var x --lower 0 --upper pi |
diff |
Derivative | diff "x**3" --var x |
simplify |
Simplify expression | simplify "sin(x)**2 + cos(x)**2" |
limit |
Compute limit | limit "sin(x)/x" --var x --point 0 |
series |
Taylor expansion | series "exp(x)" --var x --point 0 --n 5 |
dsolve |
Solve ODE | dsolve "f''(x) + f(x)" --func f --var x |
laplace |
Laplace transform | laplace "sin(t)" --var t |
Matrix Operations:
| Command | Description |
|---|---|
det |
Determinant |
eigenvalues |
Eigenvalues |
eigenvectors |
Eigenvectors with multiplicities |
inverse |
Matrix inverse |
transpose |
Transpose |
rref |
Row echelon form |
rank |
Matrix rank |
nullspace |
Null space basis |
linsolve |
Linear system Ax=b |
charpoly |
Characteristic polynomial |
Number Theory:
| Command | Description |
|---|---|
factor |
Factor polynomial |
factorint |
Prime factorization |
isprime |
Primality test |
gcd |
Greatest common divisor |
lcm |
Least common multiple |
modinverse |
Modular inverse |
Combinatorics:
| Command | Description |
|---|---|
binomial |
C(n,k) |
factorial |
n! |
permutation |
P(n,k) |
partition |
Integer partitions p(n) |
catalan |
Catalan numbers |
bell |
Bell numbers |
uv run python "$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 |
uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/pint_compute.py" convert <value> <from_unit> <to_unit>
Example: convert 5 miles kilometers
uv run python "$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.
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 |
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
User: Solve x² - 5x + 6 = 0
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/sympy_compute.py" solve "x**2 - 5*x + 6" --var x
Result: x = 2 or x = 3
User: Find eigenvalues of [[2, 1], [1, 2]]
Claude: uv run python "$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)
User: Is x² + y² ≥ 2xy always true?
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/z3_solve.py" prove "x**2 + y**2 >= 2*x*y"
Result: PROVED (equivalent to (x-y)² ≥ 0)
User: How many kilometers in 26.2 miles?
Claude: uv run python "$CLAUDE_PROJECT_DIR/.claude/scripts/cc_math/pint_compute.py" convert 26.2 miles kilometers
Result: 42.16 km
Use /prove when you need:
/math is for computation. /prove is for verification.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
parcadei/continuous-claude-v3
mattpocock/skills
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
Registry listing for math matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
Keeps context tight: math is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
We added math from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
math has been reliable in day-to-day use. Documentation quality is above average for community skills.
math is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added math from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: math is focused, and the summary matches what you get after install.
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