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 bytedoger · Codex Skill · ★ 875
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-OpenPrice safe to install? View the security audit →
OpenPrice 💖 如果这个项目对您有帮助，请在右上角帮我们点个 Star ⭐！ 您的支持是我们持续开源更新的最大动力！请关注项目后续的新功能发布，接下来我们将接入更多类型的渠道 ，敬请期待！ open price,就是开放价格的意思。所以这是一个开源的收录全网卡网渠道各种AI订阅价格的项目。项目的目的只有一个，打破信息茧房，让友友们能方便挑选价格更低、更更低的 AI 订阅服务。本项目不提供 AI 服务，只是 AI 订阅产品的搬运工。 🔗 快速访问 (Quick Links) 🛒 查看全网 AI 订阅最新底价 🏪 卡网商家一键免费收录 🚀 快速开始部署指南 ⚠️ 免责声明 📊 汇聚全网海量渠道底价 💡 项目初衷与解决的痛点 如今大家对 AI 订阅如 Claude、chatgpt 有着很大的需求，虽然市面上有着非常多高性价比的产品，但它们往往分散在各个不同的渠道中，例如链动小铺、独角卡网、二次元发卡、微信群、QQ群、闲鱼、淘宝等。这种信息不对称导致了两个主要问题： 对于买家（普通用户）：很难找到靠谱、便宜的购买渠道，往往需
| Stars | 875 |
| Forks | 47 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 63.1966195654585/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-27 |
| Created | 2026-07-16 |
| Platforms | claude-code, codex, gemini, node |
| Est. Tokens | ~15k |
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awesome-OpenPrice is 开源的 AI 订阅价格聚合与比价平台，收录 ChatGPT、Claude、Gemini、Grok、Cursor 等产品的官方订阅价格和卡网渠道报价，帮助用户快速查询并比较不同购买渠道。. It is categorized as a Codex Skill with 875 GitHub stars.
awesome-OpenPrice is primarily written in TypeScript. It covers topics such as ai, ai-subscription, chatgpt.
You can find installation instructions and usage details in the awesome-OpenPrice GitHub repository at github.com/bytedoger/awesome-OpenPrice. The project has 875 stars and 47 forks, indicating an active community.
The top alternatives to awesome-OpenPrice on Agent Skills Hub include agtx, chat-js, ctxport. 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: