ODE Solver Library

SkillDev tools

Numerical methods for ordinary differential equations

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the ODE Solver Library skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/mathematics/skills/ode-solver-library/SKILL.md and read by ahel’s review.

Purpose

Provides numerical methods and solvers for ordinary differential equations in mathematical modeling and dynamical systems analysis.

Capabilities

  • Runge-Kutta methods (explicit and implicit)
  • Multistep methods (Adams-Bashforth, BDF)
  • Stiff equation handling
  • Adaptive step size control
  • Event detection and root finding
  • Sensitivity analysis

Usage Guidelines

  1. Stiffness Assessment: Determine if problem is stiff
  2. Method Selection: Choose explicit or implicit methods accordingly
  3. Tolerance Setting: Set appropriate error tolerances
  4. Event Handling: Configure event detection for discontinuities

Tools/Libraries

  • SUNDIALS
  • scipy.integrate
  • DifferentialEquations.jl

Signals

GitHub stars
2k
Forks
112
Last commit
Sep 2026
Advanced
Item type
skill
Key
ode-solver-library
Source
github.com/a5c-ai/babysitter