ralph-method
CommunityDecompose tasks into atomic user stories.
Authordariuszparys
Version1.0.0
Installs0
System Documentation
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.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: ralph-method Download link: https://github.com/dariuszparys/claude-code-toolkit/archive/main.zip#ralph-method Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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