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setup-ralph设置拉尔夫

Agent Skill

setup-ralph 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,879

周安装

76

GitHub Stars

1,914

下载量

590
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:setup-ralph(设置拉尔夫)
来源仓库:https://github.com/glittercowboy/taches-cc-resources
仓库路径:skills/setup-ralph
安装命令:
npx skills add https://github.com/glittercowboy/taches-cc-resources --skill setup-ralph
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/glittercowboy/taches-cc-resources --skill setup-ralph

简介

集成 Ralph AI 助手相关配置与上下文工程支持。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中需要增强推理能力的场景。
  • 通过 npx skills add 命令从 taches-cc-resources 仓库安装。
  • 可能加载自定义提示词或知识库,需审核内容安全性和准确性。
  • 注意模型微调数据的版权与使用许可限制。

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:

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>

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Antigravity

31.73%
按下载量换算187

OpenCode

22.28%
按下载量换算131

Claude Code

18.44%
按下载量换算109

windsurf

13.04%
按下载量换算77

Codex

7.41%
按下载量换算44

Gemini CLI

3.85%
按下载量换算23

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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