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Ralph Wiggum

fstandhartinger/ralph-wiggum

This implements Geoffrey Huntley's iterative bash loop methodology where each coding task runs in a fresh AI agent process to avoid context window bloat. You write specs with clear acceptance criteria, run the loop, and it works through them autonomously until each outputs a DONE signal. The clever bit is that state lives on disk between iterations (specs, history logs, plans) while the agent itself stays fresh. Best for multi-feature work where you want the AI grinding through tasks unattended. Requires YOLO mode and solid acceptance criteria or it'll spin. The setup includes a project interview that focuses on vision over tech stack, which is a nice touch.

skills.sh installs
1.4K
GitHub stars
312
last updated
Aug 21, 2026
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Install

$ npx -y skills add fstandhartinger/ralph-wiggum --skill ralph-wiggum --agent claude-code

Installs into .claude/skills of the current project.

Files

Ralph Wiggum

Autonomous AI coding with spec-driven development

What is Ralph Wiggum?

Ralph Wiggum combines Geoffrey Huntley's iterative bash loop with spec-driven development for fully autonomous AI-assisted software development.

The key insight: Fresh context each iteration. Each loop starts a new agent process with a clean context window, preventing context overflow and degradation.

When to Use This Skill

Use Ralph Wiggum when:

  • You have multiple specifications/features to implement
  • You want the AI to work autonomously through tasks
  • You need consistent, verifiable completion of acceptance criteria
  • You want to avoid context window problems in long sessions

How It Works

SKILL.md on GitHub

Sponsors

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Details

Repository
github.com/fstandhartinger/ralph-wiggum
Category
CLI & Terminal

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