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 ardeyouxipianyi · Codex Skill · ★ 208
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is workbuddy2api-hub safe to install? View the security audit →
WorkBuddy2API-Hub — 国际版、国内版多账号网关中枢 本项目为 WorkBuddy2API-Hub,将腾讯 www.workbuddy.ai (国际版) 与 codebuddy.cn (国内版) 原生服务封装为标准 OpenAI 兼容接口,支持 Chat Completions 与 Responses API。具备多账号负载轮询、稳定物理设备指纹隔离、OAuth 一键免客户端登录、国内版每日签到与实时积分查询、国内成长任务全自动完成与国内版积分任务、后台常驻定时调度器、Web 监控看板等全套能力。 开箱即用:绿色包自带精简 Python ,双击批处理脚本即启。 双区域独立路由:支持 🌐 国际版 与 🇨🇳 国内版独立配置与管理,严格隔离串号,看板一键切换且状态落盘持久化。 模型列表严格按照桌面应用 1:1 对齐:按官方桌面端主界面清洗收敛,彻底剔除内部代码补全通道与底层专线变体。 稳定物理设备指纹隔离 ():国际版与国内版统一方案,以账号自身 UID 稳定哈希派生专属机器特征与会话标识,同一账号长期固定在一台虚拟物理设备上,天然防多号关联风控。 OAuth 一键免客户端登录:无需在本地安装桌面客户端,点击看板链接在浏览器完成授权即可自动入库;亦支持扫描本地客户端两步确认导入。 国内版签到与实时积分查询:支持国内版每日签到领积分,实时聚合账户资源包用量与余额。 国内成长任务与积分任务全自动完成:全自动接取任务、构造行为事件上报点亮并自动领取奖励,支持猫猫日常旅行与连续打卡。
| Stars | 208 |
| Forks | 41 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 64.9068810788052/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-22 |
| Created | 2026-09-12 |
| Platforms | browser, claude-code, codex, python |
| Est. Tokens | ~15k |
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workbuddy2api-hub is WorkBuddy 国际国内多账号反代网关 — 双域独立路由与切换、稳定设备指纹防风控、国内成长任务全自动完成、后台定时调度器、Web监控看板,支持 Codex / Claude Code / DSH与标准 OpenAI 客户端。. It is categorized as a Codex Skill with 208 GitHub stars.
workbuddy2api-hub is primarily written in Python. It covers topics such as api-gateway, claude-code, codebuddy.
You can find installation instructions and usage details in the workbuddy2api-hub GitHub repository at github.com/ardeyouxipianyi/workbuddy2api-hub. The project has 208 stars and 41 forks, indicating an active community.
workbuddy2api-hub is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to workbuddy2api-hub on Agent Skills Hub include codebuddy2openai, ccLoad, Clipal. 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: