ralph-zero

Translate PRDs into atomic stories and execute autonomous multi-agent iterations.

11|2|Updated Jan 18, 2026
One-click install
npx skills add https://github.com/davidkimai/ralph-zero --skill ralph-zero
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ralph-zero
Source: https://github.com/davidkimai/ralph-zero/tree/main
Command: npx skills add https://github.com/davidkimai/ralph-zero --skill ralph-zero

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires docopt, rich, GitPython, jsonschema, tiktoken, anthropic, and includes scripts (resource) and assets (resource) components.

What problem does it solve?

Automates the orchestration of multi-story feature development by turning PRDs into executable iterations using AI agents, enabling cognitive feedback loops and quality-driven execution.

Core Features & Use Cases

  • Universal agent compatibility and stateless iterations
  • Context synthesis and memory injection across tasks to maintain continuity
  • Built-in quality gates and cognitive feedback to surface patterns and improve over time

Quick Start

Run the Ralph Zero workflow against a PRD to automatically generate stories, convert them to prd.json, and execute the autonomous loop.

Frequently Asked Questions about ralph-zero

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

FAQPage Schema
How do I translate PRDs into executable stories for AI agents?

To translate PRDs into executable stories, you run an autonomous orchestration workflow that parses requirements and converts them into atomic, verifiable stories formatted as prd.json for AI agent execution.

What is autonomous development orchestration for multi-story features?

Autonomous development orchestration coordinates multi-story feature development by turning PRDs into executable iterations using AI agents, enabling cognitive feedback loops and quality-driven execution across iterations.

How do I maintain context continuity across multiple AI agent iterations?

To maintain context continuity across multiple AI agent iterations, the orchestration workflow uses context synthesis and memory injection across tasks to preserve execution continuity.

Can I use GitPython with autonomous orchestration workflows for quality gates?

Yes, GitPython is included as a dependency to support autonomous orchestration workflows, enabling version control integrations alongside built-in quality gates and strict validations during execution.

What are the limitations of using AI agents for autonomous story execution?

AI agents executing autonomous stories require strict validations and cognitive feedback to surface patterns, but limitations include dependency on structured PRD inputs and the need for continuous memory injection to prevent context loss.