first-order-odes
Assists with classifying, solving, and verifying first-order differential equations.
Install
mkdir -p .claude/skills/first-order-odes && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3470" && unzip -o skill.zip -d .claude/skills/first-order-odes && rm skill.zipInstalls to .claude/skills/first-order-odes
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Problem-solving strategies for first order odes in odes pdesKey capabilities
- →Classify ODEs into linear, separable, exact, or Bernoulli types
- →Calculate numerical IVP solutions via Scipy integration
- →Perform symbolic verification of solutions using Sympy
- →Locate equilibria and analyze stability for autonomous systems
- →Compute potential functions for exact differential equations
How it works
It maps the input ODE to a standard classification template and executes specialized Python scripts using Scipy for numerical analysis or Sympy for symbolic solving.
Inputs & outputs
When to use first-order-odes
- →Solving linear or separable ODEs
- →Numerical integration with Scipy
- →Verifying solutions with Sympy
- →Phase portrait analysis
About this skill
First Order Odes
When to Use
Use this skill when working on first-order-odes problems in odes pdes.
Decision Tree
-
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?
-
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} -
Numerical Solution (IVP)
scipy.integrate.solve_ivp(f, [t0, tf], y0, method='RK45')- For stiff systems:
method='Radau'ormethod='BDF' - Adaptive step size: specify rtol/atol, not step size
-
Verify Solution
- Substitute back into ODE
- Check initial/boundary conditions
sympy_compute.py dsolve "y' + y = x" --ics "{y(0): 1}"
-
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
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
uv run python -m runtime.harness scripts/sympy_compute.py dsolve "Derivative(y,x) + y" --ics "{y(0): 1}"
Z3_Equilibrium
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.
Cognitive Tools Reference
See .claude/skills/math-mode/SKILL.md for full tool documentation.
When not to use it
- →Solving non-first-order partial differential equations
- →High-performance computing for non-linear stiff systems requiring GPU acceleration
Prerequisites
Limitations
- →Limited to first-order ordinary differential equations
- →Relies on standard textbook methods which may not handle highly unique or non-standard ODE types
- →Requires manual interpretation of phase portrait data
How it compares
It eliminates manual decision-tree traversal by automating the selection of the mathematically appropriate solving library based on classification.
Compared to similar skills
first-order-odes side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| first-order-odes (this skill) | 1 | 7mo | Review | Intermediate |
| literature-review | 559 | 2mo | Review | Advanced |
| openalex-database | 48 | 7mo | Review | Intermediate |
| scientific-critical-thinking | 18 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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