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 aiwenjie777 · Codex Skill · ★ 50
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is codex-skin-skill safe to install? View the security audit →
Codex Skin 中文 · English 给 Codex Desktop 换上一张真正属于你的皮肤。 用一张图片生成主页横幅与任务背景，同时保留原生侧栏、项目选择和输入框。 非官方社区项目 · 仅通过本机回环 CDP 工作 · 不修改 .app、app.asar 或代码签名。 微信交流 微信群：扫码加入交流 个人微信：添加时请备注“Codex Skin” 30 秒开始 macOS（完整版本） 在 Codex 对话中直接说： 安装 Codex Skin 之后无需打开终端或双击桌面文件，继续用自然语言操作即可： 发一张图片，说一句话，剩下的安装、保存与应用流程交给 Skill。 “用这张图片换 Codex Skin” “列出已安装皮肤” “切换到「星航员」皮肤” “验证当前皮肤并截图” “恢复 Codex 官方外观” Skill 会自动完成安装、主题保存、应用和验证；确实需要重启 Codex 时会先征得确认。桌面的 仍会随安装创建，但只是离线或手动操作的备用入口。 macOS 安装后引擎位于 ，你的图片、主题状态与日志保存在 。换肤流程不会读取或改写 Codex 的 。 Windows（同样支持 Skill） 安装仓库提供的 插件后，也可以直接在 Codex 对话中说： “安装 Codex Skin” “用这张图片创建并应用 Windows 皮肤” “列出已安装的 Windows 皮肤” “切换到「主题名」皮肤” “验
| Stars | 50 |
| Forks | 6 |
| Language | Shell |
| Category | Codex Skill |
| Quality Score | 47.1761581202817/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-23 |
| Created | 2026-07-16 |
| Platforms | cli, codex |
| Est. Tokens | ~10k |
These tools work well together with codex-skin-skill for enhanced workflows:
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A Codex/Claude skill that maintains per-repo operating theory documents.
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codex-skin-skill is codex skin 皮肤一键安装，简单操作，skill 就可以完成，随意切换，One-click Codex skin installation—simple to use and powered entirely by a skill. Switch between skins anytime.. It is categorized as a Codex Skill with 50 GitHub stars.
codex-skin-skill is primarily written in Shell.
You can find installation instructions and usage details in the codex-skin-skill GitHub repository at github.com/aiwenjie777/codex-skin-skill. The project has 50 stars and 6 forks, indicating an active community.
The top alternatives to codex-skin-skill on Agent Skills Hub include theorist. 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: