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Agent Skill · 开发

ralphmode(ralphmode 命令行)

ralphmode 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。

ralphmode 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 20,588。

总安装 218周安装 9GitHub Stars 8下载 71核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:ralphmode(ralphmode 命令行)
来源仓库:https://github.com/jeo-tech-ai/oh-my-unity3d
仓库路径:skills/ralphmode
安装命令:
npx skills add https://github.com/jeo-tech-ai/oh-my-unity3d --skill ralphmode
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/jeo-tech-ai/oh-my-unity3d --skill ralphmode

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

命令行模式助手,处理 GitHub 协作事务与仓库状态查询。适用于批量处理 Issue 标签或里程碑更新等操作。从 GitHub 安装,需授权相应 API 权限并遵守安全策略。操作前建议预览变更影响,防止误改重要数据。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。ralphmode 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ralphmode

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jeo-tech-ai/oh-my-unity3d --skill ralphmode;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

ralphmode 怎么安装?

在终端执行 npx skills add https://github.com/jeo-tech-ai/oh-my-unity3d --skill ralphmode。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ralphmode 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

ralphmode 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/jeo-tech-ai/oh-my-unity3d --skill ralphmode 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

ralphmode 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

ralphmode 用的人多吗?

公开数据是累计安装 218 次,近一周安装 9 次,下载 71 次,GitHub 8 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

ralphmode 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
ralphmode

ralphmode 命令行 · 本页

2188执行命令未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Ralphmode

Ralphmode is a cross-platform permission profile for long-running ralph or omu workflows. It reduces approval friction, but it is not "allow everything everywhere." The core rule is simple: widen automation only inside a bounded project or disposable sandbox, and keep secrets plus destructive commands explicitly blocked.

When to use this skill

  • You want ralph to iterate without repeated approval popups.
  • You are setting up the same repo for Claude Code, Codex CLI, and Gemini CLI.
  • You need a shared safety model: repo-only writes, no secrets reads, no destructive shell by default.
  • You want a stronger separation between day-to-day automation and true YOLO mode.

Instructions

Step 1: Define the automation boundary first

Before changing any permission mode:

  • Pick one project root and keep automation scoped there.
  • List files and commands that must stay blocked: .env*, secrets/**, production credentials, rm -rf, sudo, unchecked curl | sh.
  • Decide whether this is a normal repo or a disposable sandbox.

If the answer is "disposable sandbox," you may use the platform's highest-autonomy mode. If not, use the repo-scoped preset instead.

Step 2: Choose one preset per platform

Use only the section that matches the current tool:

  • Claude Code: everyday preset first, bypassPermissions only for isolated sandboxes.
  • Codex CLI: use the current official approval and sandbox model first; treat older permissions.allow and permissions.deny snippets as compatibility-only.
  • Gemini CLI: trust only the project root; there is no true global YOLO mode.

Detailed templates live in references/permission-profiles.md.

Step 3: Apply the profile locally, not globally, unless the workspace is disposable

Prefer project-local configuration over user-global defaults.

  • Claude Code: start with project .claude/settings.json.
  • Codex CLI: start with project config and repo instructions or rules files.
  • Gemini CLI: trust the current folder, not ~/ or broad parent directories.

If you must use a user-global default, pair it with a stricter denylist and a sandbox boundary.

Step 4: Run Ralph with an explicit verification loop

After permissions are configured:

  1. Confirm the task and acceptance criteria.
  2. Run ralph or the omu plan-execute-verify loop.
  3. Verify outputs before claiming completion.
  4. If the automation profile was temporary, revert it after the run.

Recommended execution contract:

boundary check -> permission profile -> ralph run -> verify -> cleanup or revert

Step 5: Keep "skip" and "safe" separate

Treat these as different modes:

  • Repo automation: minimal prompts inside a bounded workspace.
  • Sandbox YOLO: promptless execution in a disposable environment only.

Do not collapse them into one shared team default.

Step 6: Configure Mid-Execution Approval Checkpoints

Static permission profiles (Steps 2–3) reduce friction before a run starts, but they do not stop dangerous operations that arise during execution. Add dynamic checkpoints so that Tier 1 actions are blocked or flagged at the moment they are attempted.

Dangerous operation tiers
TierActionPlatform response
Tier 1 (always block)rm -rf, git reset --hard, git push --force, DROP TABLE, sudo, .env*/secrets/** access, production environment changesBlock immediately, require explicit user approval
Tier 2 (warn)npm publish, docker push, git push (non-force), DB migrationsOutput warning, continue only with confirmation
Tier 3 (allow)File reads/edits, tests, local builds, lintAllow automatically
Platform checkpoint mechanisms
PlatformHookBlockingRecommended pattern
Claude CodePreToolUse (Bash)Yes — exit 2Shell script pattern-matches command; blocks Tier 1
Gemini CLIBeforeToolYes — non-zero exitShell script blocks tool; stderr fed to next turn
Codex CLInotify (post-turn)Noapproval_policy="unless-allow-listed" + prompt contract
OpenCodeNoneNoPrompt contract in opencode.json instructions

Principle: Combine static profiles (Steps 2–3) with dynamic checkpoints (this step).

  • Platforms with pre-tool hooks (Claude Code, Gemini): use the hook script.
  • Platforms without (Codex, OpenCode): rely on approval_policy and explicit prompt contracts that instruct the agent to output CHECKPOINT_NEEDED: <reason> and wait before proceeding with Tier 1 actions.

See references/permission-profiles.md for full hook script templates per platform.

Examples

Example 1: Claude Code sandbox run

Use the Claude sandbox preset from references/permission-profiles.md, then run Ralph only inside that isolated repo:

/ralph "fix all failing tests" --max-iterations=10

Example 2: Codex CLI repo-scoped Ralph run

Apply the Codex repo preset from references/permission-profiles.md, then run the task. The current official model uses config file settings, not CLI flag overrides:

approval_policy = "never"
sandbox_mode = "workspace-write"

Place this in ~/.codex/config.toml (or a project-local override) and restart Codex before running Ralph.

Example 3: Gemini CLI trust-only setup

Trust the current project folder, keep explicit file selection, then run the Ralph workflow for that repo only.

Best practices

  • Default to the least-permissive preset that still lets Ralph finish end-to-end.
  • Keep secret denylists and destructive command denylists even when approvals are reduced.
  • Use full bypass only in disposable environments with a clear project boundary.
  • Record which preset was applied so teammates can reproduce or revert it.
  • Re-check platform docs when upgrading CLI versions because permission models change faster than skill content.

References

平台分布

Claude

31.92%
按下载量换算23

Codex

31.61%
按下载量换算22

Cursor

16.97%
按下载量换算12

Gemini CLI

9.52%
按下载量换算7

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/jeo-tech-ai/oh-my-unity3d --skill ralphmode 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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