first-order-odes

Solve first-order ordinary differential equations using SciPy and SymPy.

3.9k|296|Updated Dec 23, 2025
One-click install
npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill first-order-odes-parcadei
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: first-order-odes
Source: https://github.com/parcadei/Continuous-Claude-v3/tree/main/.claude/skills/math/odes-pdes/first-order-odes
Command: npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill first-order-odes-parcadei

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires scipy, sympy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides strategies and tools for solving first-order ordinary differential equations (ODEs), a fundamental task in many scientific and engineering disciplines.

Core Features & Use Cases

  • ODE Classification: Helps identify the type of first-order ODE (linear, separable, exact, Bernoulli).
  • Solution Method Selection: Recommends appropriate analytical or numerical methods based on ODE classification.
  • Numerical Solvers: Integrates with SciPy for solving initial value problems (IVPs).
  • Symbolic Solvers: Leverages SymPy for analytical solutions and verification.
  • Phase Portraits: Aids in visualizing autonomous ODE behavior and stability analysis.
  • Use Case: When faced with a differential equation like y' + 2y = x, this skill can guide you to classify it as linear, apply the integrating factor method, or use SymPy to find the exact solution and check initial conditions.

Quick Start

Use the first-order-odes skill to solve the differential equation y' + y = x with the initial condition y(0) = 1.

Frequently Asked Questions about first-order-odes

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I solve first-order ODEs using Python and SciPy?

You solve first-order ODEs numerically by applying SciPy's integration functions to initial value problems, which computes the trajectory of the differential equation. This skill provides the setup logic to execute that numerical integration accurately.

Can I find analytical solutions for differential equations with SymPy?

Yes, you can find analytical solutions for differential equations with SymPy. This skill leverages symbolic computation to derive exact mathematical formulas and verify them against your initial conditions.

What is the best way to classify a first-order differential equation before solving?

The best way to classify a first-order differential equation is to identify its mathematical structure as linear, separable, exact, or Bernoulli. This skill evaluates the equation form to recommend the appropriate analytical or numerical solution method.

Does this approach support phase portrait analysis for autonomous systems?

Yes, this approach supports phase portrait analysis for autonomous ODEs. It aids in visualizing system behavior and performing stability analysis to understand the long-term dynamics of the differential equation.

When should I choose numerical integration over symbolic computation for ODEs?

You should choose numerical integration over symbolic computation when an exact analytical formula is difficult or impossible to derive. This skill uses SciPy for numerical approximations of complex initial value problems and SymPy for exact symbolic forms.