first-order-odes

first-order-odes is a skill for Claude Code from parcadei/Continuous-Claude-v3. It costs 18 tokens per session (976 once invoked), scanned A, original, MIT.

A guide to solving first-order ordinary differential equations, which contain a function and its first derivative. It covers common equation types, numerical solutions, and checks for correctness.

In plain words
What is it for?
Use it to solve separable, linear, exact, and Bernoulli equations, including initial-value problems. It also supports numerical solutions and basic stability analysis of autonomous equations.
Why use it?
It helps choose a suitable solution method instead of trying techniques at random. It also helps verify the result and handle equations that are difficult to solve exactly.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: reads .claude/ paths.

Good fit Use it to solve separable, linear, exact, and Bernoulli equations, including initial-value problems. It also supports numerical solutions and basic stability analysis of autonomous equations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/parcadei/continuous-claude-v3/first-order-odes
About the project

Continuous-Claude-v3 is a Claude Code development environment that preserves working context between sessions, coordinates specialized agents, and stores project knowledge through ledgers, handoffs, and analysis tools. It is for people using Claude Code on ongoing or complex software work. Its catalogue entries are the skills, agents, hooks, plugin, and setting that provide its workflows and orchestration.

parcadei/Continuous-Claude-v3 · 3,938 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add parcadei/Continuous-Claude-v3 --skill first-order-odes
Clone the repo
git clone --depth 1 https://github.com/parcadei/Continuous-Claude-v3

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for first-order-odes

README.md
[![agentmods](https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/first-order-odes/github.svg)](https://agentmods.dev/skills/parcadei/continuous-claude-v3/first-order-odes)
Your own site
<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/first-order-odes"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/first-order-odes/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for first-order-odes

Your own site · 80×15
<a href="https://agentmods.dev/skills/parcadei/continuous-claude-v3/first-order-odes"><img src="https://agentmods.dev/badge/skills/parcadei/continuous-claude-v3/first-order-odes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 976 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Agent Snooping · line 75
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.00976
Opus 5 $0.00009 $0.00488
Sonnet 5 $0.00004 $0.00195
Haiku 4.5 $0.00002 $0.00098

Measured 9d ago against content hash 7b137b7f9778, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

first-order-odes scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/math/odes-pdes/first-order-odes/SKILL.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

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.

Read the full file on GitHub · 76 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 76 lines · 18 tokens per session scan A 7b137b7f9778

Subscribe to this mod's changes

first-order-odes is a skill published in the GitHub repository parcadei/Continuous-Claude-v3 (3,938 stars, last pushed 7mo ago), licensed MIT. It adds 18 tokens to every session and 976 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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