Is Ralph Wiggum compatible with the ai-eng-system?

Yes, it is designed to integrate directly with the ai-eng-system as an execution pattern for /work commands and multi-agent workflows.

Can I use this for Test-Driven Development (TDD)?

Absolutely. It is highly optimized for TDD, allowing the agent to write failing tests and iterate on the implementation until the test suite is green.

How does this skill prevent infinite loops and token waste?

It implements required safety parameters including a Max Iterations Cap (typically 10-50) and specific completion promises that must be matched exactly.

What is the Ralph Wiggum iteration pattern?

It is a systematic while-loop methodology that directs AI agents to work on a task until an objective completion signal or promise is detected.

When should I avoid using the Ralph Wiggum skill?

Avoid using it for tasks requiring subjective human judgment, UX design choices, or ambiguous goals like 'improve performance' without specific metrics.

Ralph Wiggum Continuous Iteration

Name: Ralph Wiggum Continuous Iteration
Author: v1truv1us

byv1truv1us

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생산성 및 워크플로

Automates repetitive development tasks through a continuous iteration loop with clear, verifiable completion criteria.

소개

Ralph Wiggum is a specialized execution pattern for Claude Code designed to handle well-defined tasks autonomously using a while-loop methodology. It enables AI agents to persist through TDD cycles, complex bug fixes, and feature implementations by iterating until specific success signals—or 'completion promises'—are met. Built for the ai-eng-system, it includes critical safety measures such as iteration caps and stuck-state detection, making it an ideal tool for overnight automation and frictionless, test-driven development.

주요 기능

Safety caps and iteration limits to prevent token waste
2 GitHub stars
Integrated prompt templates for TDD, refactoring, and feature builds
Configurable completion promises for objective task verification
Autonomous TDD and bug-fixing iteration loops
Stuck-state detection and progress monitoring logic

사용 사례

Autonomous overnight development of features with automated test suites
Continuous TDD cycles where the agent iterates until all unit tests pass
Systematic bug fixing that requires repeated debugging and verification steps

소개

주요 기능

Safety caps and iteration limits to prevent token waste
2 GitHub stars
Integrated prompt templates for TDD, refactoring, and feature builds
Configurable completion promises for objective task verification
Autonomous TDD and bug-fixing iteration loops
Stuck-state detection and progress monitoring logic

사용 사례

Autonomous overnight development of features with automated test suites
Continuous TDD cycles where the agent iterates until all unit tests pass
Systematic bug fixing that requires repeated debugging and verification steps