Token导航 LogoToken导航TokenDH.com
待分类external-servicegithub未标认证来源可访问许可证需确认审计异常

ralph-creator拉尔夫创造者

Agent Skill

ralph-creator 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

259

周安装

11

GitHub Stars

2

下载量

91
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

2

许可证

unknown

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:ralph-creator(拉尔夫创造者)
来源仓库:https://github.com/jonmumm/skills
仓库路径:skills/ralph-creator
安装命令:
npx skills add https://github.com/jonmumm/skills --skill ralph-creator
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/jonmumm/skills --skill ralph-creator

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合围绕仓库状态、代码变更或协作事项进行整理。
  • 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,避免触发联网或命令执行。
  • ralph-creator 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Ralph Creator

Generate AFK Ralph loop scripts. Ralph runs claude -p --dangerously-skip-permissions in a loop — one task per iteration, progress tracked between iterations, stops when all tasks are done.

Output Structure

All artifacts go in .ralph/ at the project root:

.ralph/
├── ralph-<name>.sh    # Loop script (executable)
├── backlog.md         # Task checklist
├── progress.md        # Working memory (delete after run)
└── lessons.md         # Mistakes to avoid (persists)

Workflow

1. Gather Context

Ask the user (2-3 questions max, skip if obvious from context):

  • What's the task?
  • What context files should the agent read?
  • Roughly how many subtasks? (determines iteration count)

2. Create .ralph/ Directory

mkdir -p .ralph

3. Write the Backlog

Create .ralph/backlog.md. See references/backlog-format.md.

Rules:

  • Each task: - [] checkbox, bolded title, clear description
  • One task = one iteration = one context window
  • Order by dependency, then priority
  • Enough detail for a fresh Claude instance to execute without ambiguity

4. Generate the Script

Create .ralph/ralph-<name>.sh from references/script-template.md.

Customize the placeholders:

  • {{ADDITIONAL_CONTEXT_REFS}} — extra @path refs for skills, specs, style guides
  • {{ONE_SENTENCE_DIRECTIVE}} — imperative statement: what each iteration produces
  • {{EXECUTE_STEPS}} — numbered sub-steps for the domain-specific work
  • {{VERIFY_INSTRUCTION}} — how to confirm the work is correct
  • {{ADDITIONAL_RULES}} — domain-specific constraints

CRITICAL: The @ refs and prompt text MUST be in ONE quoted string passed to claude -p. The template handles this correctly — do not separate them into different variables or CLI args.

If the task needs a style guide or reference material, put it in a SEPARATE file and add it to {{ADDITIONAL_CONTEXT_REFS}} as another @ reference. Do NOT inline it in the prompt.

5. Create Tracking Files

.ralph/progress.md:

# Progress
Working memory for ralph-<name>. Delete after run.
---

.ralph/lessons.md:

# Lessons
Patterns and mistakes. Review at start of each iteration.
---

See references/tracking-format.md for entry format.

6. Make Executable and Report

chmod +x .ralph/ralph-<name>.sh

Tell the user the run command:

.ralph/ralph-<name>.sh <iterations>

Suggest iterations = task count + 2 (buffer for retries + final COMPLETE check).

Prompt Design Rules

  1. Imperative first line — The prompt MUST open with a direct command: YOUR JOB: <one sentence>. The model reads @ context files first (often 1000+ lines), so the prompt must immediately snap it into execution mode, not summary mode.
  2. Numbered steps, not section headers — Use STEPS: with numbered items (1. Do X. 2. Do Y.), NOT markdown ## Section headers. Section headers read as documentation. Numbered steps read as commands.
  3. Explicit "Do NOT" rules — End the prompt with a RULES: block that includes what the agent must NOT do (e.g., "Do NOT summarize the spec. Do NOT ask what to work on. Just execute."). Without these, the model defaults to helpful-assistant mode.
  4. Short and punchy — Prompt should be under 30 lines. The @ files provide all the context. The prompt is ONLY for instructions. If domain-specific guidance (style guides, conventions) is needed, put it in a separate @-referenced file, not inline.
  5. @ context refs — Load docs upfront, don't waste tokens exploring
  6. Verification step — Agent confirms work before marking done
  7. Quality bar — Measurable "done" criteria, no ambiguity
  8. One task per iteration — Always include: ONLY work on ONE task. Do not continue to the next.
  9. Completion sigil — Always: If all tasks are done, output <promise>COMPLETE</promise>.
  10. Tool instructions — If using MCP tools, APIs, or CLIs, include explicit how-to in the execute steps

Prompt Anti-Patterns (Avoid These)

These patterns cause the agent to summarize context instead of executing tasks:

Anti-PatternWhy It FailsFix
@ refs as separate CLI argsModel receives file contents without a directive, just summarizes them@ refs MUST be inline in the prompt string: "@file.md YOUR JOB:..."
OUTPUT=$(claude -p...) captureBuffers all output — user sees nothing for 10-20 minutesUse `\tee "$LOGFILE"` for real-time streaming + log capture
Starting with background/explanationModel treats it as conversation contextLead with YOUR JOB: imperative
## Section headers in promptReads as documentation, not commandsUse STEPS: with numbered list
Long inline style guides/conventionsBuries the actual instructionsMove to separate @-referenced file
Prompt > 40 linesModel loses the thread after heavy @ contextKeep to 15-30 lines max
No explicit "Do NOT" rulesModel defaults to helpful-assistant behaviorsAdd RULES: block with prohibitions
Sections named "Orient" / "Context"Encourages reading + summarizing, not actingName steps as actions: "Read backlog", "Write the file"

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

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

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

Codex

38.25%
按下载量换算35

Claude

32.51%
按下载量换算30

Cursor

16.79%
按下载量换算15

Gemini CLI

8.7%
按下载量换算8

安全审计

Gen Agent Trust Hub

未通过

Socket

可疑

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills