sympy

8.1

100

362

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 parameters.

symbolic math

8.1

Rating

Installs

Data & Analytics

Quick Review

Exceptional skill for symbolic mathematics with SymPy. The SKILL.md provides comprehensive coverage with clear invocation guidance (extensive 'When to Use' section, common patterns, and quick reference). Task knowledge is excellent with concrete code examples for all major operations, best practices, troubleshooting, and references to supplementary files for deep topics. Structure is exemplary: concise overview in SKILL.md with well-organized sections and modular reference files for advanced content. Novelty is strong—symbolic computation requires domain expertise and many API details that would consume significant tokens in a CLI-only approach. Minor deduction on novelty only because some basic symbolic math could be handled directly, but the comprehensive coverage of advanced topics (physics, code generation, matrices) and integration patterns clearly justify the skill. This is a well-crafted, production-ready skill that meaningfully reduces token cost for mathematical workflows.