glittercowboy/taches-cc-resources/setup-ralph

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

Install

npx vskill@latest install glittercowboy/taches-cc-resources/setup-ralph

SKILL.md

<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>

<intake> What would you like to do?

  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. </intake>

<routing>

ResponseWorkflow
1, "set up", "setup", "new", "initialize", "create"workflows/setup-new-loop.md
2, "understand", "learn", "concepts", "explain", "how"workflows/understand-ralph.md
3, "customize", "modify", "change", "update", "edit"workflows/customize-loop.md
4, "troubleshoot", "debug", "fix", "problem", "issue"workflows/troubleshoot-loop.md
OtherClarify intent, then select appropriate workflow

After reading the workflow, follow it exactly. </routing>

<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>

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
1,982
Repository forks
410
7-day trend score
38

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 18 Mar 2026, 7 months ago.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

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  • Windsurf
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  • Gemini CLI
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  • Amp
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  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
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