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Ralph Loop (Agent Mode)

作者 Addo.Zhang · GitHub ↗ · v1.1.0
cross-platform ⚠ suspicious
2892
总下载
0
收藏
12
当前安装
1
版本数
在 OpenClaw 中安装
/install ralph-loop-agent
功能描述
Guide OpenClaw agents to execute Ralph Wiggum loops using exec and process tools. Agent orchestrates coding agents (Codex, Claude Code, OpenCode, Goose) with proper TTY support via pty:true. Plans/builds code via PROMPT.md + AGENTS.md, SPECS and IMPLEMENTATION_PLAN.md. Includes PLANNING vs BUILDING modes, backpressure, sandboxing, and completion conditions. Users request loops, agents execute using tools.
安全使用建议
This skill appears to do what it says — it teaches an OpenClaw agent how to launch and monitor interactive coding CLIs using exec + process — but there are several things to consider before installing or running it: 1. Metadata mismatch: The package/README explicitly require CLIs like opencode/codex/claude/goose, but the registry metadata you were shown said 'none' for required binaries. Confirm which CLIs are actually required and present on the host before use. 2. Review auto-approval flags: The SKILL.md references risky flags (e.g. --yolo, --dangerously-skip-permissions, --full-auto). Avoid enabling those unless you run the skill in a fully isolated sandbox and understand the consequences. 3. Sandbox and least privilege: Run initial tests in an isolated environment (container/VM) with limited network and credentials. Prefer sandboxed execution (docker/e2b/fly) as the README recommends. 4. Inspect generated prompts and files: The agent will create and cat PROMPT.md and other files into CLI commands. Prompt injection or crafted prompts could cause the coding CLI to run unintended actions. Review PROMPT.md, AGENTS.md, and command strings before allowing execution. 5. Monitor runtime and logs: Use the platform's process/exec monitoring controls and be prepared to kill sessions if behavior is unexpected. Do not give the agent access to sensitive cloud credentials or wide git permissions when testing. 6. What would change this assessment: If there were an install script that downloaded code from an untrusted host, or the skill requested unrelated credentials (AWS/GCP tokens) in its declared requirements, or the registry metadata intentionally omitted required exec/process permissions — the verdict would be higher-severity suspicious or worse. Providing explicit, consistent required-tools metadata and removing or clearly warning about permission-bypassing flags would increase my confidence to 'benign'.
功能分析
Type: OpenClaw Skill Name: ralph-loop-agent Version: 1.1.0 This skill is classified as suspicious due to several high-risk capabilities. The primary concern is a clear command injection vulnerability where the content of `PROMPT.md` is directly executed as part of shell commands via `exec tool ... "$(cat PROMPT.md)"` (seen in SKILL.md and README.md). This allows a malicious user or agent to inject arbitrary commands. Additionally, the skill explicitly documents and instructs the agent to accept and use highly risky flags like `--yolo` (no sandbox) and `--dangerously-skip-permissions` (seen in SKILL.md and README.md), which can bypass critical safety mechanisms. The skill also requires broad `exec`, `process`, `file-read`, and `file-write` permissions (package.json), granting extensive control over the system.
能力评估
Purpose & Capability
The skill's README and package.json clearly describe launching interactive coding CLIs (opencode, codex, claude, goose, pi) and requiring exec/process/file-read/file-write permissions — which fits the stated purpose. However the registry metadata shown to you earlier lists no required binaries or env vars, which contradicts the package.json and SKILL.md. That mismatch (no declared required CLIs in the registry view vs. explicit tool requirements in the files) should be resolved before trusting the skill.
Instruction Scope
The SKILL.md instructs agents to construct and exec arbitrary CLI command strings built from PROMPT.md and project files and to run background interactive sessions with pty:true. This is functionally coherent for an orchestrator, but the instructions also promote using auto-approval flags (e.g. --yolo, --dangerously-skip-permissions) and running arbitrary tests/commits. Those bits broaden the agent's runtime discretion and enable bypassing sandbox/permission checks — a real risk if misused or combined with malicious prompts or untrusted repos.
Install Mechanism
This is instruction-only (no install spec and no code files to execute on install), which is the lowest install risk. Nothing in the bundle downloads or writes code at install time.
Credentials
The skill doesn't request environment variables or credentials from the registry metadata, and package.json lists only tool and permission requirements (exec/process/file-read/file-write), which are consistent with running CLIs and manipulating project files. However the skill will read and write workspace files (PROMPT.md, AGENTS.md, IMPLEMENTATION_PLAN.md, project files) and will execute arbitrary CLI commands which can access network services or local credentials. The absence of declared required credentials is not an assurance that sensitive data won't be accessed during runs — the agent's runtime commands could touch cloud CLIs or git remotes.
Persistence & Privilege
always:false and no install-time persistence are set; the skill is user-invocable and relies on agent tools at runtime. It does not request force-inclusion or system-wide configuration changes in the provided materials.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ralph-loop-agent
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ralph-loop-agent 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.0
Version 1.1.0 summary: Expanded documentation and feature guidance for Ralph Loop agent orchestration. - Added comprehensive SKILL.md detailing agent workflows, tool usage, prompts, and best practices. - Documented support for interactive CLIs with proper TTY and background process management. - Outlined PLANNING vs BUILDING loop modes, completion condition detection, and sandboxing safeguards. - Included explicit input requirements, command templates for major AI coding agents, and troubleshooting guidance. - Emphasized use of exec+process tools for robust automation and session control.
元数据
Slug ralph-loop-agent
版本 1.1.0
许可证
累计安装 12
当前安装数 12
历史版本数 1
常见问题

Ralph Loop (Agent Mode) 是什么?

Guide OpenClaw agents to execute Ralph Wiggum loops using exec and process tools. Agent orchestrates coding agents (Codex, Claude Code, OpenCode, Goose) with proper TTY support via pty:true. Plans/builds code via PROMPT.md + AGENTS.md, SPECS and IMPLEMENTATION_PLAN.md. Includes PLANNING vs BUILDING modes, backpressure, sandboxing, and completion conditions. Users request loops, agents execute using tools. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 2892 次。

如何安装 Ralph Loop (Agent Mode)?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ralph-loop-agent」即可一键安装,无需额外配置。

Ralph Loop (Agent Mode) 是免费的吗?

是的,Ralph Loop (Agent Mode) 完全免费(开源免费),可自由下载、安装和使用。

Ralph Loop (Agent Mode) 支持哪些平台?

Ralph Loop (Agent Mode) 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ralph Loop (Agent Mode)?

由 Addo.Zhang(@addozhang)开发并维护,当前版本 v1.1.0。

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