No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by liyupi · Codex Skill · ★ 188
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openclaw-guide safe to install? View the security audit →
OpenClaw 中文网 OpenClaw 开源 AI 智能体的中文文档与介绍站，帮助中文用户快速上手并深入使用 OpenClaw。 在线访问 · OpenClaw 主仓库 简介 OpenClaw 是一个开源、可自托管的个人 AI 智能体（AI Agent），可通过 WhatsApp、Telegram、Discord、飞书、钉钉、企业微信等 20+ 聊天平台与你交互，帮你处理清理收件箱、发送邮件、管理日历等日常任务。运行在你自己的设备上，数据完全私有。 本仓库是 OpenClaw 的 中文网站，包含： 首页（Landing Page）：产品介绍、快速安装等 文档站：350+ 篇翻译文档，涵盖安装、渠道接入、模型配置、工具技能等全部内容 文档内容 本地开发 前置要求 Node.js 18+ npm 安装与启动 bash git clone https://github.com/liyupi/openclaw-guide.git cd openclaw-gui
| Stars | 188 |
| Forks | 26 |
| Language | PowerShell |
| Category | Codex Skill |
| Quality Score | 60.4939034000842/100 |
| Last Updated | 2026-04-15 |
| Created | 2026-03-12 |
| Platforms | claude-code, cli, docker |
| Est. Tokens | ~929k |
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openclaw-guide is 开源OpenClaw中文文档站，OpenClaw中文指南，支持小龙虾 AI 智能体安装部署、消息渠道接入、Agent 架构、Skills 技能配置、模型提供商、CLI 命令参考、网关运维、安全沙箱等全方位文档。覆盖 WhatsApp、Telegram、Discord、飞书、钉钉、企业微信等 20+ 聊天平台，OpenAI、Anthropic、Ollama、通义千问等 30+ LLM 提供商，Doc. It is categorized as a Codex Skill with 188 GitHub stars.
openclaw-guide is primarily written in PowerShell. It covers topics such as agents, ai, claude.
You can find installation instructions and usage details in the openclaw-guide GitHub repository at github.com/liyupi/openclaw-guide. The project has 188 stars and 26 forks, indicating an active community.
The top alternatives to openclaw-guide on Agent Skills Hub include llmio, MCP-X-web, helix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: