Best use case
first-order-odes is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Problem-solving strategies for first order odes in odes pdes
Teams using first-order-odes should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/first-order-odes/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How first-order-odes Compares
| Feature / Agent | first-order-odes | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Problem-solving strategies for first order odes in odes pdes
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# First Order Odes
## When to Use
Use this skill when working on first-order-odes problems in odes pdes.
## Decision Tree
1. **Classify the ODE**
- Linear: y' + P(x)y = Q(x)?
- Separable: y' = f(x)g(y)?
- Exact: M(x,y)dx + N(x,y)dy = 0 with dM/dy = dN/dx?
- Bernoulli: y' + P(x)y = Q(x)y^n?
2. **Select Solution Method**
| Type | Method |
|------|--------|
| Separable | Separate and integrate |
| Linear | Integrating factor e^{int P dx} |
| Exact | Find potential function |
| Bernoulli | Substitute v = y^{1-n} |
3. **Numerical Solution (IVP)**
- `scipy.integrate.solve_ivp(f, [t0, tf], y0, method='RK45')`
- For stiff systems: `method='Radau'` or `method='BDF'`
- Adaptive step size: specify rtol/atol, not step size
4. **Verify Solution**
- Substitute back into ODE
- Check initial/boundary conditions
- `sympy_compute.py dsolve "y' + y = x" --ics "{y(0): 1}"`
5. **Phase Portrait (Autonomous)**
- Find equilibria: f(y*) = 0
- Analyze stability: sign of f'(y*)
- `z3_solve.py solve "dy/dt == 0"`
## Tool Commands
### Scipy_Solve_Ivp
```bash
uv run python -c "from scipy.integrate import solve_ivp; sol = solve_ivp(lambda t, y: -y, [0, 5], [1]); print('y(5) =', sol.y[0][-1])"
```
### Sympy_Dsolve
```bash
uv run python -m runtime.harness scripts/sympy_compute.py dsolve "Derivative(y,x) + y" --ics "{y(0): 1}"
```
### Z3_Equilibrium
```bash
uv run python -m runtime.harness scripts/z3_solve.py solve "f(y_star) == 0"
```
## Key Techniques
*From indexed textbooks:*
- [Elementary Differential Equations and... (Z-Library)] Solving ODEs with MATLAB (New York: Cambridge REFERENCES cyan black NJ: Prentice-Hall, 1971). Mattheij, Robert, and Molenaar, Jaap, Ordinary Differential Equations in Theory and Practice Shampine, Lawrence F. Numerical Solution of Ordinary Differential Equations (New York: Chapman and Shampine, L.
- [Elementary Differential Equations and... (Z-Library)] Differential Equations: An Introduction to Modern Methods and Applications (2nd ed. Use the Laplace transform to solve the system 2e−t 3t α1 α2 , where α1 and α2 are arbitrary. How must α1 and α2 be chosen so that the solution is identical to Eq.
- [An Introduction to Numerical Analysis... (Z-Library)] Modern Numerical Methods for Ordinary Wiley, New York. User's guide for DVERK: A subroutine for solving non-stiff ODEs. Keller (1966), Analysis of Numerical Methods.
- [Elementary Differential Equations and... (Z-Library)] Show that the rst order Adams–Bashforth method is the Euler method and that the rst order Adams–Moulton method is the backward Euler method. Show that the third order Adams–Moulton formula is yn+1 = yn + (h/12)(5fn+1 + 8fn − fn−1). Derive the second order backward differentiation formula given by Eq.
- [An Introduction to Numerical Analysis... (Z-Library)] Test results on initial value methods for non-stiff ordinary differential equations, SIAM J. Comparing numerical methods for Fehlberg, E. Klassische Runge-Kutta-Formeln vierter und niedrigerer Ordnumg mit Schrittweiten-Kontrolle und ihre Anwendung auf Warme leitungsprobleme, Computing 6, 61-71.
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