mcpField
R
ralph-loop

ralph-loop

github.com/andrelandgrafAgent workflows233.5k installsUpdated 20w ago
Repository

About ralph-loop

ralph-loop is a recipe sequence for setting up automated agent-driven development. Teams define features as user stories with testable acceptance criteria, then run agents in a loop to implement and verify them.

Key features

  1. 01Set up code health checks
  2. 02Configure coding agents
  3. 03Define stories with acceptance criteria
  4. 04Track implementation progress
  5. 05Run agents in an implementation loop

Use cases

  1. 01Preparing a project for agent-driven development
  2. 02Breaking features into verifiable stories
  3. 03Automating implementation and acceptance checks

MCP support

The setup recipe includes configuring MCP servers for consistent AI-assisted development.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/andrelandgraf/fullstackrecipes --skill ralph-loop

After installing, type/ralph-loopin Claude Code to confirm it loaded.

Details

From the project README

Ralph Loop

Complete setup for automated agent-driven development. Define features as user stories with testable acceptance criteria, then run AI agents in a loop until all stories pass.

Prerequisites

Complete these recipes first (in order):

Code Health, Linting & Formatting

Configure Prettier for formatting, TypeScript for typechecking, and Fallow for code health (dead code, duplication, complexity, architecture drift). Skips ESLint/Biome to avoid config complexity.

curl -H "Accept: text/markdown" https://fullstackrecipes.com/api/recipes/code-health-setup
AI Coding Agent Configuration

Configure AI coding agents like Cursor, GitHub Copilot, or Claude Code with project-specific patterns, coding guidelines, and MCP servers for consistent AI-assisted development.

curl -H "Accept: text/markdown" https://fullstackrecipes.com/api/recipes/agent-setup

Cookbook - Complete These Recipes in Order

User Stories Setup

Create a structured format for documenting feature requirements as user stories. JSON files with testable acceptance criteria that AI agents can verify and track.

curl -H "Accept: text/markdown" https://fullstackrecipes.com/api/recipes/user-stories-setup
Working with User Stories

Document and track feature implementation with user stories. Workflow for authoring stories, building features, and marking acceptance criteria as passing.

curl -H "Accept: text/markdown" https://fullstackrecipes.com/api/recipes/using-user-stories
Ralph Agent Loop

Set up automated agent-driven development with Ralph. Run AI agents in a loop to implement features from user stories, verify acceptance criteria, and log progress for the next agent.

curl -H "Accept: text/markdown" https://fullstackrecipes.com/api/recipes/ralph-setup

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