What is the Ralph Wiggum technique for AI coding?

It is a deterministic methodology that uses iterative loops and strict verification commands to ensure AI-generated code meets specific, measurable requirements.

What is a 'completion promise' in this context?

A completion promise is a unique string enclosed in specific tags that the AI is instructed to output only after all tests pass and all criteria are met.

Does this generator handle Test-Driven Development?

Yes, it specifically builds a TDD workflow into the prompt, requiring the AI to identify failing tests before implementing the solution.

How does this skill improve Claude Code's output?

By structuring prompts with binary success criteria and clear verification steps, it reduces ambiguity and helps the AI self-correct until the task is truly complete.

Can I use this for complex, multi-file features?

This skill is optimized for single implementation tasks. For larger, multi-stage projects, consider using the ralph-prompt-multi-task or ralph-prompt-project skills.

Ralph Prompt Generator (Single Task)

Name: Ralph Prompt Generator (Single Task)
Author: adaptationio

byadaptationio

Productivity & Workflow

Generates optimized, verification-driven prompts for the Ralph Wiggum coding technique to handle focused development tasks.

About

This skill automates the creation of high-quality, Ralph-compatible prompts designed for single-session implementation tasks like bug fixes, refactors, and small feature additions. It enforces a rigorous Test-Driven Development (TDD) approach by embedding clear completion criteria, automated verification scripts, and deterministic success loops within every generated prompt. By leveraging the Ralph philosophy—which treats failures as data for improvement—this tool ensures Claude Code iterations are measurable, self-correcting, and highly reliable.

Key Features

TDD-focused workflow integration for robust self-correction loops
Standardized Ralph-compliant prompt templates for single tasks
Automatic generation of binary success checklists and verification steps
Structured 'If Stuck' guidance to prevent hallucination cycles
Pre-defined completion promise tags for reliable loop termination
0 GitHub stars

Use Cases

Resolving specific bugs with verifiable success criteria and unit tests
Implementing single API endpoints or features with clearly defined parameters
Refactoring legacy code modules into modern patterns like async/await

About

Key Features

TDD-focused workflow integration for robust self-correction loops
Standardized Ralph-compliant prompt templates for single tasks
Automatic generation of binary success checklists and verification steps
Structured 'If Stuck' guidance to prevent hallucination cycles
Pre-defined completion promise tags for reliable loop termination
0 GitHub stars

Use Cases

Resolving specific bugs with verifiable success criteria and unit tests
Implementing single API endpoints or features with clearly defined parameters
Refactoring legacy code modules into modern patterns like async/await