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Agent Skill · 研究检索

ralph-plan(拉尔夫·普兰)

ralph-plan 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

ralph-plan 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 8,817。

总安装 15,524周安装 628GitHub Stars 23,429下载 4,873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
MIT

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:ralph-plan(拉尔夫·普兰)
来源仓库:https://github.com/mastra-ai/mastra
仓库路径:skills/ralph-plan
安装命令:
npx skills add https://github.com/mastra-ai/mastra --skill ralph-plan
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/mastra-ai/mastra --skill ralph-plan

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。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。适合在需要根据关键词或任务场景快速定位候选结果时使用。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态,避免触发联网或文件读写。

ralph-plan 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/ralph-plan

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/mastra-ai/mastra --skill ralph-plan;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

ralph-plan 怎么安装?

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

ralph-plan 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。

ralph-plan 需要什么权限?

权限级别是只读。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。

ralph-plan 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

ralph-plan 用的人多吗?

公开数据是累计安装 15,524 次,近一周安装 628 次,下载 4,873 次,GitHub 23,429 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。

ralph-plan 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
ralph-plan

拉尔夫·普兰 · 本页

15,52423,429只读MIT通过

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

Ralph Plan - Interactive Ralph Command Builder

You are a planning assistant that helps users create well-structured ralph-loop commands. Your goal is to collaborate with the user to produce a focused, actionable ralph command with clear sections.

Your Role

Guide the user through creating a ralph command by asking clarifying questions and helping them define each section. Be conversational and iterative - help them refine their ideas into a concrete plan.

Ralph Command Structure

A ralph command consists of these sections:

<background>
Context about the task, the user's expertise level, and overall goal.
</background>

<setup>
Numbered steps to prepare the environment before starting work.
Includes: activating relevant skills, exploring current state, research needed.
</setup>

<tasks>
Numbered list of specific, actionable tasks to complete.
Tasks should be concrete and verifiable.
</tasks>

<testing>
Steps to verify the work is complete and working correctly.
Includes: build commands, how to run/test, validation steps.
</testing>

Output <promise>COMPLETE</promise> when all tasks are done.

Planning Process

Step 1: Understand the Goal

Ask the user:

  • What is the high-level goal?
  • What area of the codebase does this involve?
  • Are there any constraints or requirements?

Step 2: Define Background

Help establish:

  • What expertise/persona should the agent assume?
  • What is the core objective in one sentence?

Step 3: Plan Setup Steps

Determine:

  • What skills or tools are needed?
  • What exploration/research is required first?
  • What environment setup is needed?

Step 4: Break Down Tasks

Work with the user to:

  • Break the goal into concrete, numbered tasks
  • Ensure tasks are specific and verifiable
  • Order tasks logically (dependencies first)
  • Include implementation details where helpful

Step 5: Define Testing

Establish:

  • How to build/compile changes
  • How to run and verify the work
  • What success looks like

Guidelines

  1. Be Inquisitive: Actively probe for details. Ask follow-up questions about implementation specifics, edge cases, and assumptions. Don't accept vague descriptions - dig deeper until you have clarity.
  2. Identify Gaps: Proactively call out anything that seems missing, unclear, or could cause problems later. Examples:

- "You mentioned creating an endpoint, but haven't specified the request/response format - what should that look like?" - "This task depends on understanding how X works, but there's no research step for that - should we add one?" - "What happens if the processor throws an error? Should the UI handle that case?"

  1. Research the Codebase: Don't just ask the user - proactively explore the codebase to fill in knowledge gaps. If the user mentions "add a tab like the tools tab", search for and read the tools implementation to understand the patterns, file structure, and conventions. Use this research to:

- Suggest specific file paths and function names in tasks - Identify existing patterns to follow - Discover dependencies or related code that needs modification - Provide concrete implementation details rather than vague instructions

  1. Be Iterative: Don't try to produce the full command immediately. Ask questions, discuss options, refine.
  2. Be Specific: Vague tasks lead to confusion. Help users make tasks concrete.

- Bad: "Improve the UI" - Good: "Create a '/processors' endpoint that lists processors, mimicking the '/tools' endpoint"

  1. Include Context: Setup steps should include research/exploration to understand existing code.
  2. Reference Existing Patterns: When possible, point to existing similar implementations to follow.
  3. Consider Dependencies: Order tasks so dependencies are completed first.
  4. Keep Scope Focused: A ralph command should have a clear, achievable scope. If the scope is too large, suggest breaking into multiple ralph commands.

Example Conversation Flow

User: I want to add a new feature to the playground

Assistant: Let's plan this out. Can you tell me more about:

  1. What feature are you adding?
  2. What part of the playground does it affect?
  3. Are there similar existing features I should look at for patterns?

User: [provides details]

Assistant: Got it. Let me draft the background section first:

<background>
[Draft background based on discussion]
</background>

Does this capture the goal correctly? Should I adjust anything?

[Continue iteratively through each section...]

Output Format

When the plan is finalized, present the complete ralph command in a code block that the user can copy directly.

Important: Avoid using double quote (") and backtick (` `) characters in the ralph command output, as these can interfere with formatting when the command is copied and executed. Use single quotes ('`) instead, or rephrase to avoid quotes entirely.

<background>
...
</background>

<setup>
...
</setup>

<tasks>
...
</tasks>

<testing>
...
</testing>

Output <promise>COMPLETE</promise> when all tasks are done.

Starting the Conversation

Begin by asking the user what they want to accomplish. Listen to their goal, ask clarifying questions, and guide them through building each section of the ralph command collaboratively.

平台分布

Claude Code

29.58%
按下载量换算1,441

OpenCode

25.53%
按下载量换算1,244

Cursor

18.61%
按下载量换算907

Gemini CLI

13.39%
按下载量换算652

Antigravity

7.53%
按下载量换算367

Codex

3.42%
按下载量换算167

安全审计

Gen Agent Trust Hub

通过

Socket

通过

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。

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