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Setup Ralph

CommunityPopular
glittercowboy
setup-ralph

Set up and configure Geoffrey Huntley's original Ralph Wiggum autonomous coding loop in any directory with proper structure, prompts, and backpressure.

Overview

Publisherglittercowboy
Repositorytaches-cc-resources
Skill namesetup-ralph
Stars
2K
Forks
411
Bundled files
14
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 14 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by glittercowboy on GitHub. Read the source before you install it.

Installation

Install the Setup Ralph AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/glittercowboy/taches-cc-resources.git /tmp/taches-cc-resources
mkdir -p .claude/skills
cp -r /tmp/taches-cc-resources/skills/setup-ralph .claude/skills/setup-ralph
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Setup Ralph in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Setup Ralph on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Setup Ralph is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

<essential_principles>

What is Ralph?

Ralph is Geoffrey Huntley's autonomous AI coding methodology that uses iterative loops with task selection, execution, and validation. In its purest form, it's a Bash loop:

bash
while :; do cat PROMPT.md | claude ; done

The loop feeds a prompt file to Claude, the agent completes one task, updates the implementation plan, commits changes, then exits. The loop restarts immediately with fresh context.

Core Philosophy

The Ralph Wiggum Technique is deterministically bad in an undeterministic world. Ralph solves context accumulation by starting each iteration with fresh context—the core insight behind Geoffrey's approach.

Three Phases, Two Prompts, One Loop

  1. Planning Phase: Gap analysis (specs vs code) outputs prioritized TODO list—no implementation, no commits
  2. Building Phase: Picks tasks from plan, implements, runs tests (backpressure), commits
  3. Observation Phase: You sit on the loop, not in it—engineer the setup and environment that allows Ralph to succeed

Key Principles

Your Role: Ralph does all the work, including deciding which planned work to implement next and how to implement it. Your job is to engineer the environment.

Backpressure: Create backpressure via tests, typechecks, lints, builds that reject invalid/unacceptable work.

Observation: Watch, especially early on. Prompts evolve through observed failure patterns.

Context Efficiency: With ~176K usable tokens from 200K window, allocating 40-60% to "smart zone" means tight tasks with one task per loop achieves maximum context utilization.

File I/O as State: The plan file persists between isolated loop executions, serving as deterministic shared state—no sophisticated orchestration needed.

Remote Backup: The loop automatically creates a private GitHub repo and pushes after each commit. This protects against accidental data loss from autonomous operations. Requires gh CLI authenticated. Disable with RALPH_BACKUP=false.

Safety Rules: PROMPT_build.md includes critical safety rules prohibiting dangerous operations like rm -rf on project directories. Tests must run in isolated temp directories. </essential_principles>

  1. Set up a new Ralph loop - Initialize Ralph structure in a directory
  2. Understand Ralph concepts - Learn about the technique and how it works
  3. Customize existing loop - Modify prompts or configuration
  4. Troubleshoot Ralph - Debug loop issues or improve performance

Wait for response before proceeding.

After reading the workflow, follow it exactly.

<reference_index>

Domain Knowledge

All in references/:

Core Concepts: ralph-fundamentals.md - Three phases, two prompts, one loop Structure: project-structure.md - Required files and directory layout Prompts: prompt-design.md - Planning vs building mode instructions Backpressure: validation-strategy.md - Tests, lints, builds as steering Best Practices: operational-learnings.md - AGENTS.md guidance and evolution </reference_index>

<workflows_index>

WorkflowPurpose
setup-new-loop.mdInitialize Ralph structure in a directory
understand-ralph.mdLearn Ralph concepts and philosophy
customize-loop.mdModify prompts or loop configuration
troubleshoot-loop.mdDebug loop issues and improve performance
</workflows_index>

<success_criteria> Skill is successful when:

  • User understands which workflow they need
  • Appropriate workflow loaded based on intent
  • All required references loaded by workflow
  • User can set up and run Ralph loops independently </success_criteria>

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Setup Ralph AI skill do?

Set up and configure Geoffrey Huntley's original Ralph Wiggum autonomous coding loop in any directory with proper structure, prompts, and backpressure.

Why use Setup Ralph on TypingMind?

Because you install it once and use it with any model. Setup Ralph is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Setup Ralph in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/glittercowboy/taches-cc-resources/tree/main/skills/setup-ralph. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Setup Ralph?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Setup Ralph?

As many as you like. As long as a model supports skills, you can use Setup Ralph with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Setup Ralph AI skill free?

Yes. It is published on GitHub by glittercowboy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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