formula-derivation

Name: formula-derivation
Availability: InStock
Author: dogekiki

Structure research notes into coherent derivation documents with assumptions and theory lines.

1|Updated Jul 21, 2026

Search Tags:#research #academic #mathematics #formula #derivation #theory

Ready to run

npx skills add https://github.com/dogekiki/SP-test --skill formula-derivation-dogekiki

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: formula-derivation
Source: https://github.com/dogekiki/SP-test/tree/main/.trae/skills/formula-derivation
Command: npx skills add https://github.com/dogekiki/SP-test --skill formula-derivation-dogekiki

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the challenge of organizing scattered research notes, assumptions, and equations into a logically sound and paper-ready derivation package.

Core Features & Use Cases

Theory Line Construction: Transforms messy notes into a coherent derivation map with explicit assumptions and invariant objects.
Logical Verification: Classifies derivation steps into identities, propositions, approximations, or interpretations to ensure mathematical honesty.
Use Case: When you have a collection of draft equations for a new model but lack a clear logical flow, use this Skill to build a formal derivation document that identifies blockers and clarifies the underlying theory.

Quick Start

Use the formula-derivation skill to structure my current research notes into a coherent derivation package for the proposed theory line.

Frequently Asked Questions about formula-derivation

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

FAQPage Schema

How do I structure scattered research notes into a coherent derivation document?▼

To structure scattered research notes into a coherent derivation document, you need to organize assumptions, theory lines, and mathematical steps into a logically sound package. This process maps complex formula chains by identifying invariant objects.

What is the best way to verify the logical flow of a theoretical physics derivation?▼

Verifying the logical flow of a theoretical physics derivation requires classifying each mathematical step into identities, propositions, approximations, or interpretations. This classification ensures mathematical honesty and clarifies the underlying theory.

Can I use this approach to build a formal derivation map from draft equations?▼

Yes, you can build a formal derivation map from draft equations by transforming messy notes into explicit assumptions and invariant objects. This clarifies the theory line and identifies blockers for quantitative research models.

When do I need to map invariant objects in a mathematical derivation?▼

You need to map invariant objects in a mathematical derivation when parsing complex formula chains for academic writing. Identifying these invariant objects helps distinguish between fundamental identities and applied approximations.

Does this method work for quantitative research theories lacking a clear logical flow?▼

Yes, this method works for quantitative research theories lacking a clear logical flow by organizing scattered equations into a paper-ready derivation package. It explicitly maps the theory line to ensure rigorous logical construction.