by daxiondi · Codex Skill · ★ 75
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openclaw-desktop 默认中文文档。English docs: README.en.md 是面向普通用户的 OpenClaw 桌面版,目标是「安装即用、零门槛」。 这个项目的好处 零依赖体感:用户安装一个桌面包即可,不需要先手动装一堆 CLI 和环境。 离线友好:安装包内置 OpenClaw 离线载荷,弱网/无外网场景也能完成初始化。 登录更顺滑:支持 OAuth 登录流程,并可复用本机已有的登录状态(如 Codex)。 国内可用:同时支持 OAuth 路线和 API Key 路线(可接入国内模型/网关)。 官方能力不丢:可直接打开 OpenClaw 官方本地页面使用聊天与配置能力。 跨平台交付:统一产出 macOS / Windows / Linux 安装包。 用户快速开始 打开 Releases 页面下载对应系统安装包。 安装并启动 。 在引导页选择登录方式: OAuth(如 Codex / Claude / Gemini / Qwen Portal) API Key(可对接国内兼容端点) 本地 Ollama 登录完成后即可进入聊天和模型配置。 Windows 离线安装说明 目标:弱网/离线用户只需一次安装,尽量不依赖复杂外网步骤。 当前 Windows 提供两条路径: 自动路径(推荐) 正常安装并启动 。 首次引导时,程序会优先尝试安装包内离线载荷。 如果安装包内离线载荷缺失或不完整,会自动下载并提取 后继续安装。 手动路径(兜底) 在引导页点击 。 选择你已经下载好的 。 程序会自动提取并安装离线载荷,然后继续初始化。 为什么 Windows 还会出现“安装包内离线载荷不可用”: Windows 的打包链路里,资源注入偶发失败/路径不稳定(表现为构建产物里缺少 )。 为避免用户被阻塞,我们增加了运行时自动下载兜底 + 手动选择 portable 兜底,两条路径都不要求用户手动配环境。 验证 Windows portable 安装(dev/CI) 该脚本用于验证 Windows portable zip 是否能完成离线自举:下载/解压载荷 → 离线安装 → 启动 gateway → 验证本地页面可访问。 沟通交流群 扫码加入 交流群: 在线更新(自动检测 + 一键更新) 应用顶部已内置在线更新入口: 启动后自动静默检测新版本。 检
| Stars | 75 |
| Forks | 18 |
| Language | Rust |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.2775840348901/100 |
| Open Issues | 13 |
| Last Updated | 2026-04-23 |
| Created | 2026-02-18 |
| Platforms | cli, rust |
| Est. Tokens | ~839k |
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openclaw-desktop is 零依赖体感:用户安装一个桌面包即可,不需要先手动装一堆 CLI 和环境。 离线友好:安装包内置 OpenClaw 离线载荷,弱网/无外网场景也能完成初始化。 跨平台交付:统一产出 macOS / Windows / Linux 安装包。. It is categorized as a Codex Skill with 75 GitHub stars.
openclaw-desktop is primarily written in Rust. It covers topics such as opeclaw-desktop, openclaw.
You can find installation instructions and usage details in the openclaw-desktop GitHub repository at github.com/daxiondi/openclaw-desktop. The project has 75 stars and 18 forks, indicating an active community.
openclaw-desktop is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openclaw-desktop on Agent Skills Hub include pinion-os, kindly-web-search-mcp-server, JoySafeter. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.