What is a 'completion promise' in this context?

A completion promise is a specific, verifiable string or condition included in the prompt that signals to the autonomous loop that the task has been successfully finalized.

Can I manually override the task classification?

Yes, if the orchestrator's initial classification doesn't match your needs, you can explicitly specify your preferred generator (e.g., ralph-prompt-single-task) in your request.

What is the Ralph Wiggum technique?

It is an autonomous loop philosophy built on the idea that failures are deterministic data points. Prompts are designed to iterate through these failures until verifiable success criteria are met.

How does the orchestrator decide which generator to use?

It analyzes indicators such as the number of deliverables, whether you are modifying existing code or building from scratch, and if an investigation phase is required.

Ralph Prompt Builder

Name: Ralph Prompt Builder
Author: adaptationio

byadaptationio

Productivity & Workflow

Orchestrates the creation of optimized prompts for the Ralph Wiggum autonomous loop technique by classifying and routing tasks to specialized generators.

About

The Ralph Prompt Builder serves as a master orchestrator for developers looking to leverage autonomous coding cycles. It analyzes your specific task requirements—ranging from simple bug fixes to complex greenfield projects—and automatically routes them to the most appropriate specialized prompt generator. By following the 'Ralph Wiggum' philosophy that failures are deterministic and fixable through iteration, this skill helps you build robust, verifiable prompts that include success criteria, TDD patterns, and phased implementation plans for reliable AI-driven development.

Key Features

Integrated 'If Stuck' guidance and TDD-focused implementation patterns
Automatic task classification into Single, Multi-task, Project, or Research categories
0 GitHub stars
Guided input collection for technical context, success criteria, and verification commands
Recommended iteration counts based on task complexity and environmental constraints
Standardized prompt generation optimized for the Ralph Wiggum autonomous loop

Use Cases

Generating a structured prompt for fixing specific bugs or refactoring existing modules
Creating an autonomous research and audit loop for security or architectural analysis
Scaffolding a phased plan for building a new application from scratch

About

Key Features

Integrated 'If Stuck' guidance and TDD-focused implementation patterns
Automatic task classification into Single, Multi-task, Project, or Research categories
0 GitHub stars
Guided input collection for technical context, success criteria, and verification commands
Recommended iteration counts based on task complexity and environmental constraints
Standardized prompt generation optimized for the Ralph Wiggum autonomous loop

Use Cases

Generating a structured prompt for fixing specific bugs or refactoring existing modules
Creating an autonomous research and audit loop for security or architectural analysis
Scaffolding a phased plan for building a new application from scratch