sympy
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and
npx skills add LeonChaoX/qinyan-academic-skills --skill sympy --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# SymPy - Symbolic Mathematics in Python ## Overview SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations. This skill provides comprehensive guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using SymPy. ## When to Use This Skill Use this skill when: - Solving equations symbolically (algebraic, differential, systems of equations) - Performing calculus operations (derivatives, integrals, limits, series) - Manipulating and simplifying algebraic expressions - Working with matrices and linear algebra symbolically - Doing physics calculations (mechanics, quantum mechanics, vector analysis) - Number theory computations (primes, factorization, modular arithmetic) - Geometric calculations (2D/3D geometry, analytic geometry) - Converting mathematical expressions to executable code (Python, C, Fortran) - Generating LaTeX or other formatted mathematical output - Needing exact mathematical results (e.g., `sqrt(2)` not `1.414...`) ## Core Capabilities ### 1. Symbolic Computation Basics **Creating symbols and expressions:** ```
- Overview
- When to Use This Skill
- Core Capabilities
- 1. Symbolic Computation Basics
- 2. Calculus
- 3. Equation Solving
- 4. Matrices and Linear Algebra
- 5. Physics and Mechanics
- 6. Advanced Mathematics
- 7. Code Generation and Output
- Working with SymPy: Best Practices
- 1. Always Define Symbols First
- 2. Use Assumptions for Better Simplification
- 3. Use Exact Arithmetic
What does the sympy skill do?
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and
How do I install it?
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill sympy --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LeonChaoX/qinyan-academic-skills, a repository with 759 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.