verify_physics

Verify dimensional consistency and numerical stability in computational physics code.

1|Updated Dec 17, 2025
One-click install
npx skills add https://github.com/tatsuki-washimi/gwexpy --skill verify-physics
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: verify_physics
Source: https://github.com/tatsuki-washimi/gwexpy/tree/main/.agent/skills/verify_physics
Command: npx skills add https://github.com/tatsuki-washimi/gwexpy --skill verify-physics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The skill helps ensure that implementations adhere to correct physics and mathematics, catching dimensional inconsistencies and calculation errors early in the development process.

Core Features & Use Cases

  • Dimensional Analysis: verifies unit handling and prevents invalid combinations (e.g., Length plus Time).
  • Mathematical Inspection: checks equations against reference literature and flags numerical instability or edge cases.
  • Sanity & Multi-Domain Checks: validates energy conservation for transforms, tests with known signals, and ensures proper behavior across all axes in multi-dimensional data.
  • Report: generates a concise, actionable summary highlighting suspect logic and confirming validity.

Quick Start

Run the verify_physics workflow on your codebase to perform dimensional analysis, mathematical inspection, and sanity checks and generate a verification report.

Frequently Asked Questions about verify_physics

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

FAQPage Schema
How do I check dimensional consistency in numerical simulation code?

Dimensional analysis validates unit handling in computational code to prevent invalid combinations, such as adding Length plus Time. It checks equations against reference literature and flags numerical instability or edge cases to ensure calculations are physically correct.

What is the best way to verify numerical stability in multi-dimensional data processing pipelines?

Numerical stability validation checks equations against reference literature and tests with known signals. It ensures proper behavior across all axes in multi-dimensional data and flags potential edge cases, generating a structured report highlighting suspect logic.

How do I validate energy conservation for mathematical transforms in my software?

Energy conservation validation performs sanity checks on mathematical transforms to ensure physical correctness. It verifies transforms using known signals and generates a concise, actionable summary confirming validity or highlighting suspect logic.

Can I use automated physics verification for multi-dimensional scientific software?

Automated physics verification applies to multi-dimensional scientific software, including numerical simulations and validation suites. It performs dimensional analysis, mathematical inspection, and sanity checks to generate a human- and machine-readable report.

Why does my computational code produce dimensional inconsistencies during calculations?

Dimensional inconsistencies occur when invalid unit combinations, such as adding Length plus Time, are present in computational code. Automated dimensional analysis verifies unit handling and equation correctness to catch these calculation errors early.

What does a physics and math verification report include for computational code?

A verification report provides a concise, actionable summary highlighting suspect logic and confirming validity. It is structured to be both human- and machine-readable, detailing the results of dimensional analysis, mathematical inspection, and sanity checks.