formula-derivation

Construct a structured derivation package from scattered notes and assumptions.

Updated Apr 29, 2026
One-click install
npx skills add https://github.com/jkfee/Auto-Research --skill formula-derivation-jkfee
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: formula-derivation
Source: https://github.com/jkfee/Auto-Research/tree/main/skills/formula-derivation
Command: npx skills add https://github.com/jkfee/Auto-Research --skill formula-derivation-jkfee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps researchers transform scattered notes, assumptions, and informal derivations into a coherent derivation package, clarifying objectives and keeping the target objective stable throughout the development process.

Core Features & Use Cases

  • Target selection and scoping: Define the derivation target and the main invariant object, while separating general and special-case regimes.
  • Assumptions normalization: Capture and standardize notation, definitions, and assumptions to prevent ambiguity.
  • Derivation mapping and tracking: Build a map of steps, lemmas, and dependencies to guide the end-to-end derivation workflow.
  • Use Case: When notes are fragmented across drafts, generate a structured Derivation Package to support reproducible reasoning and review.

Quick Start

Specify your derivation target and attach the current notes to generate the Derivation Package.

Frequently Asked Questions about formula-derivation

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

FAQPage Schema
How do I turn scattered research notes into a coherent derivation?

To turn scattered notes into a coherent derivation, you specify your derivation target and attach your informal drafts. The process normalizes assumptions and notation, then maps lemmas and steps into a fixed structure for reproducible reasoning.

What is the best way to structure mathematical assumptions and notation for a research document?

The best way to structure assumptions and notation is through standardization during derivation mapping. Capturing definitions and separating general from special-case regimes prevents ambiguity and keeps the target objective stable throughout the document.

How do I track derivation steps and lemmas from fragmented drafts?

You track derivation steps and lemmas by building a dependency map from your fragmented drafts. This mapping guides the end-to-end workflow, resolving the invariant object and linking steps to generate a structured derivation package.

When do I need a fixed structure for theory derivation and documentation?

You need a fixed structure for theory derivation when notes are fragmented across drafts and require reproducible reasoning. Defining the target, invariant object, assumptions, notation, strategy, map, steps, and interpretations ensures coherent review.

Does this derivation mapping approach support special-case regimes and general assumptions?

Yes, derivation mapping explicitly supports special-case regimes and general assumptions. Target selection and scoping separate these regimes during the process, ensuring the invariant object remains resolved while standardizing notation.

Why does my informal derivation lose track of the original target objective?

Your informal derivation loses track of the target objective because scattered notes lack enforced structure. Stating the target object upfront and resolving the invariant during mapping keeps the objective stable throughout the reasoning workflow.