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ralph-method

Decompose complex features into atomic user stories with dependency ordering.

12|4|Updated Dec 2, 2025
Search Tags:#planning#decomposition#user-story#ralph#coding-loop#autonomous-ai
One-click install
npx skills add https://github.com/dariuszparys/claude-code-toolkit --skill ralph-method
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ralph-method
Source: https://github.com/dariuszparys/claude-code-toolkit/tree/main/plugins/ralph-prep/skills
Command: npx skills add https://github.com/dariuszparys/claude-code-toolkit --skill ralph-method

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Ralph Wiggum Method provides a structured approach to break complex tasks into small, independently verifiable user stories, enabling autonomous AI coding loops to ship features predictably.

Core Features & Use Cases

  • Atomic story generation: convert features into minimal, testable stories.
  • Dependency-first decomposition: order work to satisfy prerequisites before dependent tasks.
  • PRD/json artifact support: produce prd.json style artifacts and story breakdowns for documentation.
  • Validation and audit: ensure each story is self-contained, testable, and deliverable within a single iteration.
  • Use cases: planning for AI-driven code generation, sprint planning, and feature decomposition for large initiatives.

Quick Start

Describe a feature you want decomposed, and the Ralph Wiggum Method will generate atomic user stories ready for implementation.

Frequently Asked Questions about ralph-method

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

FAQPage Schema
How do I decompose complex features into atomic user stories?▼

Feature decomposition breaks complex tasks into minimal, independently verifiable atomic user stories. It applies pattern-based story templates, dependency ordering, and verification checks to ensure each story is testable and deliverable within a single iteration.

What is the best way to plan tasks for autonomous AI coding loops?▼

Planning for autonomous AI coding loops requires structured task decomposition to ship features predictably. You convert features into small, self-contained user stories ordered to satisfy prerequisites before dependent tasks.

How do I generate a PRD JSON artifact for sprint planning?▼

Generating a PRD JSON artifact involves producing structured story breakdowns from feature descriptions. This outputs dependency-ordered, self-contained stories suitable for documentation and stepwise implementation.

Can I use atomic user stories for stepwise implementation across software projects?▼

Atomic user stories support stepwise implementation across software projects by ensuring each task is self-contained and testable. This validation and audit process verifies deliverability within a single iteration before moving forward.

Does dependency-first decomposition work for large initiative feature planning?▼

Dependency-first decomposition orders work to satisfy prerequisites before dependent tasks, making it effective for large initiative feature planning. It ensures complex features are broken down into predictable, verifiable iterations.

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