
setup-ralph
Set up and configure Geoffrey Huntley's original Ralph Wiggum autonomous coding loop in any directory with proper structure, prompts, and backpressure.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/glittercowboy/taches-cc-resources --skill setup-ralph- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads setup-ralph automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
<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:
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
- Planning Phase: Gap analysis (specs vs code) outputs prioritized TODO list—no implementation, no commits
- Building Phase: Picks tasks from plan, implements, runs tests (backpressure), commits
- 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>
- Set up a new Ralph loop - Initialize Ralph structure in a directory
- Understand Ralph concepts - Learn about the technique and how it works
- Customize existing loop - Modify prompts or configuration
- Troubleshoot Ralph - Debug loop issues or improve performance
Wait for response before proceeding. </intake>
<routing> | Response | Workflow | |----------|----------| | 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` | | Other | Clarify 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>
| Workflow | Purpose |
|---|---|
| setup-new-loop.md | Initialize Ralph structure in a directory |
| understand-ralph.md | Learn Ralph concepts and philosophy |
| customize-loop.md | Modify prompts or loop configuration |
| troubleshoot-loop.md | Debug 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>
FAQ
What does the setup-ralph skill do?
Set up and configure Geoffrey Huntley's original Ralph Wiggum autonomous coding loop in any directory with proper structure, prompts, and backpressure.
How do I install setup-ralph?
Run npx skills add https://github.com/glittercowboy/taches-cc-resources --skill setup-ralph in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/setup-ralph/ (personal) or .claude/skills/setup-ralph/ (project).
Which AI agents can use setup-ralph?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is setup-ralph safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains setup-ralph?
It is published by glittercowboy in glittercowboy/taches-cc-resources. It has 124 recorded installs.
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