formula-derivation

Structure research formulas into a coherent derivation package with labeled steps.

2|1|Updated Apr 19, 2026
One-click install
npx skills add https://github.com/raja21068/AutoResearch --skill formula-derivation-raja21068
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: formula-derivation
Source: https://github.com/raja21068/AutoResearch/tree/main/skills/aris/formula-derivation
Command: npx skills add https://github.com/raja21068/AutoResearch --skill formula-derivation-raja21068

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you structure and derive research formulas when your notes are scattered or the target object and assumptions are still unclear, so the result becomes a coherent derivation package instead of a polished but unfounded theorem story.

Core Features & Use Cases

  • Derivation Package Builder: Chooses a target file (explicitly specified, referenced, or defaults to DERIVATION_PACKAGE.md) and writes a theory-line derivation document with clear structure.
  • Invariant Object + Assumption Normalization: Freezes the target and selects a single organizing “invariant object” so special cases don’t quietly change the underlying meaning.
  • Honest Coherence Checking: Classifies output status as coherent as stated, coherent after reframing/extra assumptions, or not yet coherent with a blocker report and explicit missing pieces.

Quick Start

Ask the AI to use formula-derivation to build a paper-ready derivation package into DERIVATION_PACKAGE.md for your current 推导公式 goal, using your provided equations and assumptions, and to output either a coherent derivation or a blocker report if the object or assumptions remain inconsistent.

Frequently Asked Questions about formula-derivation

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

FAQPage Schema
How do I structure messy equations into a coherent derivation for a research paper?

You can format scattered research notes by freezing a clear target, selecting a stable invariant object, and normalizing notation to produce a coherent derivation package with labeled nontrivial steps.

What is an invariant object in formula derivation and why does it matter for research writing?

An invariant object in formula derivation is a single organizing target that prevents special cases from quietly changing the underlying meaning, ensuring the theory line remains consistent throughout the research writing process.

How do I label nontrivial steps when deriving formulas for academic papers?

When deriving formulas for academic papers, label each nontrivial step as an identity, proposition, approximation, or interpretation to maintain an evidence-aligned theory line and clear structural coherence.

Can I check if my mathematical assumptions are consistent before finalizing a derivation?

You can check assumption consistency by normalizing notation and evaluating the derivation against the invariant object, which outputs a status of coherent, coherent after reframing, or a blocker report with missing pieces.

What happens when my equation structuring fails due to inconsistent assumptions?

When equation structuring fails due to inconsistent assumptions, the process outputs a blocker report identifying explicit missing pieces and returning a status indicating the derivation is not yet coherent.

Does this approach work for organizing scattered notes into a paper-ready derivation document?

Yes, this approach works for organizing scattered notes by writing a target derivation file, applying assumption normalization, and producing a paper-ready document with a status-consistent output.