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 ZhiweiChen-coder · Codex Skill · ★ 68
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is OpenAshare safe to install? View the security audit →
OpenAshare 中文 · English 面向中国与香港股票的 AI 研究工作台。 从行情、新闻和技术面，到带上下文的 Agent 研究，一处完成。 云端 Beta 正在开放。 想先体验云端工作台？访问产品首页并登录后申请 Beta 访问；想自己掌控数据与模型？直接在本地运行本仓库。 OpenAshare 不是另一个只展示行情的面板。它将个股技术分析、市场消息、热点主题、持仓复盘、策略观察和 Agent 对话连接成一条研究链路：从一个代码开始，看到数据、指标、新闻与 AI 的可追问解读；从一个市场热点出发，回到关联标的与自己的持仓语境。 项目以本地优先和可自托管为基础，也在建设面向海外华人与国际研究者的中英文产品体验，帮助更多人更方便地理解中国与香港股票市场。 重要提示：本项目仅用于研究、学习和工具搭建，不构成投资建议。市场有风险，所有决策请自行负责。
| Stars | 68 |
| Forks | 18 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.9564548897685/100 |
| Last Updated | 2026-09-07 |
| Created | 2025-07-20 |
| Platforms | python |
| Est. Tokens | ~14k |
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OpenAshare is 🤖 A 股与港股 AI 研究智能体：行情、技术分析、新闻热点、交易信号、持仓管理与 Agent 问答一站式完成。. It is categorized as a Codex Skill with 68 GitHub stars.
OpenAshare is primarily written in Python. It covers topics such as agent, ashare, finance.
You can find installation instructions and usage details in the OpenAshare GitHub repository at github.com/ZhiweiChen-coder/OpenAshare. The project has 68 stars and 18 forks, indicating an active community.
OpenAshare is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to OpenAshare on Agent Skills Hub include hhxg-top-hhxg-python, alphaevo, JoySafeter. 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: