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 · MCP Server · ★ 129
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is github-global safe to install? View the security audit →
GitHub 仓库 AI 文档翻译平台 作者：程序员鱼皮 本项目为教学项目，提供完整视频教程 + 文字教程 + 简历写法 + 面试题解 + 答疑服务，帮你提升项目能力，给简历增加亮点！ ⭐️ 加入项目系列学习：加入编程导航 一、项目介绍 这是一套以 AI 编程实战 为核心的项目教程，基于 Next.js + GitHub App + OpenRouter，用 AI 编程的方式从 0 到 1 开发一个《GitHub 仓库 AI 文档翻译 SaaS 平台》，带你亲身体验 AI Vibe Coding 的完整工作流，学会用 AI 做出真正能用、能部署、能赚钱的产品！ 📺 项目介绍视频，快速查看成品效果：https://bilibili.com/video/BV1mAAmzqEfP 输入任意一个 GitHub 仓库地址，AI 自动将文档翻译成多种语言，并在基准语言内容发生变更时，自动增量同步翻译，生成 PR 等待仓库负责人合并，全程无需人工干预。 为什么做这个项目？ 鱼皮开源了一套 AI 编程教程仓库 ai-guide，包含了上百个中文教程文档。为了让海外用户也能看到，希望把仓库翻译成多语言版本，但人工翻译成本太高，GitHub Actions 又要自己折腾配置…… 既然如此，不如做一个更通用的工具。 这就是 GitHub Global 项目的起点：输入任意一个 GitHub 仓库地址，AI 自动将文档翻译成多种语言，并在基准语言内容发生变更时，自动增量同步翻译，生成 PR 等待仓库负责人合并，全程无需人工干预。 零配置，一键翻译，让你的 GitHub 项目走向全球！ 6 大核心能力 1）用 GitHub 账号一键登录，基于 GitHub App 实现安全登录与授权。 2）导入 GitHub 仓库，输入地址即可自动拉取仓库信息。 3）配置翻译，可视化选择翻译范围和目标语言（支持 20 种主流语言）。 4）一
| Stars | 129 |
| Forks | 25 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 61.832162028052/100 |
| Open Issues | 1 |
| Last Updated | 2026-03-03 |
| Created | 2026-01-20 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~15k |
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github-global is 2026 年编程导航 AI 编程实战新项目，基于 Next.js 15 + GitHub App + OpenRouter 的 GitHub 仓库 AI 文档翻译 SaaS 平台，支持可视化翻译配置、一键多语言翻译、自动创建 PR、Webhook 增量翻译、自定义大模型等。覆盖 GitHub App OAuth 认证、GitHub REST API 对接、OpenRouter 多模型接入、Pris. It is categorized as a MCP Server with 129 GitHub stars.
github-global is primarily written in TypeScript. It covers topics such as ai, ai-agents, backend.
You can find installation instructions and usage details in the github-global GitHub repository at github.com/liyupi/github-global. The project has 129 stars and 25 forks, indicating an active community.
The top alternatives to github-global on Agent Skills Hub include weam, giselle, SimplerLLM. 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: