gpd-derive-equation

Derive physics equations with explicit assumptions, dimensional checks, and stepwise verification.

1|Updated Mar 29, 2026
One-click install
npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-derive-equation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gpd-derive-equation
Source: https://github.com/CharlieGreenman/roomtemp-superconductor-gpd/tree/main/.agents/skills/gpd-derive-equation
Command: npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-derive-equation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a rigorous, end-to-end derivation workflow that ensures every assumption, notation, and step is explicit, verifiable, and well-documented so derived results are trustworthy.

Core Features & Use Cases

  • Explicit assumptions and notation lock to prevent drift.
  • Step-by-step derivation with explicit operations, dimensional checks, and symmetry verifications.
  • Automatic generation of a self-contained derivation document suitable for publication or peer review.
  • Supported by an end-to-end workflow that records conventions, checks limits, and produces a final boxed result.

Quick Start

Provide the target equation as input to the derivation workflow to begin an end-to-end, verifiable derivation with explicit assumptions, notation, steps, and documentation.

Frequently Asked Questions about gpd-derive-equation

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

FAQPage Schema
How do I derive a physics equation with verifiable steps and explicit assumptions?

To derive a physics equation with verifiable steps, you provide the target formulation as input to trigger a stepwise workflow that locks notation, checks dimensions, and outputs a complete derivation document with a boxed result.

What is the best way to verify a Hamiltonian derivation for theoretical physics?

Verifying a Hamiltonian derivation requires a workflow that enforces notation lock, performs dimensional analysis, and checks symmetry limits to ensure every step is explicit and mathematically sound.

Can I use this derivation workflow for perturbation theory equations?

Yes, you can use this derivation workflow for perturbation theory equations because it applies to theoretical physics derivations requiring explicit assumptions and stepwise verification.

Does this physics derivation tool provide error bounds in the final result?

Yes, this physics derivation tool provides explicit error bounds in the final result by recording conventions, checking limits, and producing a boxed outcome suitable for peer review.

How do I document notation and conventions for a particle physics derivation?

Documenting notation and conventions for a particle physics derivation happens automatically by applying notation lock to prevent drift and generating a self-contained document with explicit assumptions.

When should I not use an automated physics equation derivation workflow?

You should not use an automated physics equation derivation workflow when your formulation lacks defined starting assumptions or when your problem does not require explicit dimensional analysis and stepwise verification.