Can I use Ralph Plan for large-scale projects?

Absolutely. If a goal is too large, Ralph Plan will suggest breaking it down into multiple, focused ralph-loop commands to ensure high-quality results.

Why does Ralph Plan avoid using double quotes in output?

It uses single quotes or rephrases content to ensure the generated command can be copied and executed in CLI environments without formatting interference.

What is a ralph-loop command?

A ralph-loop command is a structured XML instruction set that provides an AI agent with context, setup requirements, a task list, and testing steps to ensure a task is completed correctly.

Does Ralph Plan understand my specific codebase?

Yes, the skill is designed to proactively search your local files to find implementation patterns, which it then uses to suggest specific file paths and function names.

How does Ralph Plan improve AI task execution?

By forcing a structured planning phase and asking clarifying questions, it eliminates ambiguity and identifies technical dependencies before the AI starts writing code.

Ralph Plan

Name: Ralph Plan
Author: mastra-ai

bymastra-ai

•

20,654

Productivity & Workflow

Guides users through creating structured, actionable ralph-loop commands via collaborative planning and proactive codebase research.

About

Ralph Plan is an interactive assistant designed to help developers architect precise and effective ralph-loop commands. It moves beyond simple prompts by engaging in a step-by-step dialogue to define project background, environment setup, verifiable tasks, and testing protocols. By proactively exploring the codebase, Ralph Plan identifies existing patterns and dependencies, ensuring that the final execution plan is technically sound and follows established conventions. It is an essential tool for breaking down complex requirements into manageable, focused units of work for AI agents.

Key Features

Interactive conversational workflow for building complex task plans
Gap analysis to identify missing requirements or edge cases during planning
Automatic generation of structured XML ralph-loop commands
Logic-based task sequencing to ensure dependencies are handled first
20,654 GitHub stars
Proactive codebase research to identify relevant patterns and file paths

Use Cases

Breaking down complex feature requests into actionable AI execution steps
Standardizing team-wide workflows for consistent AI agent task execution
Architecting refactoring plans for legacy components within a repository

About

Key Features

Interactive conversational workflow for building complex task plans
Gap analysis to identify missing requirements or edge cases during planning
Automatic generation of structured XML ralph-loop commands
Logic-based task sequencing to ensure dependencies are handled first
20,654 GitHub stars
Proactive codebase research to identify relevant patterns and file paths

Use Cases

Breaking down complex feature requests into actionable AI execution steps
Standardizing team-wide workflows for consistent AI agent task execution
Architecting refactoring plans for legacy components within a repository