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 dfkai · Codex Skill · ★ 156
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is xtquantai safe to install? View the security audit →
xtquantai — 迅投 QMT 量化 AI 技能集 面向迅投 QMT / 投研终端的 Agent Skills 仓库：把量化策略开发的领域知识（因子回测、信号生成、实盘模板等）封装为标准 SKILL.md 技能，安装后可在 Claude Code、Cursor、Codex、Gemini CLI、Kimi Code 等 70+ AI 编程工具中直接使用。 本仓库曾是 xtquant 的 MCP 服务器实现，现已全面转型为 skill 仓库。旧 MCP 代码保留在 分支（tag ），不再维护。 技能列表 参与社区 这个项目靠社区需求驱动——你在 QMT 量化中遇到的重复劳动，都可能值得做成一个技能： 💡 想要新技能 → 提交技能需求，一句话的想法也欢迎 🐛 技能出问题 → 反馈 Bug 💬 使用咨询 / 量化思路交流 → Discussions 🔧 自己动手 → 阅读 贡献指南 后提 PR 所有技能在 CI 中自动按 Agent Skills 标准 校验。维护流程公开在 [维护手册](docs/maintena
| Stars | 156 |
| Forks | 38 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 64.9888859971536/100 |
| Open Issues | 9 |
| Last Updated | 2026-06-11 |
| Created | 2025-03-11 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~6k |
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xtquantai is 迅投 QMT 量化 AI 技能集（Agent Skills）：研报因子回测脚本生成等，适用于 Claude Code / Cursor / Codex / Kimi 等 70+ AI 编程工具. It is categorized as a Codex Skill with 156 GitHub stars.
xtquantai is primarily written in Python. It covers topics such as agent-skills, claude-code, cursor.
You can find installation instructions and usage details in the xtquantai GitHub repository at github.com/dfkai/xtquantai. The project has 156 stars and 38 forks, indicating an active community.
xtquantai is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to xtquantai on Agent Skills Hub include joinquant-skill, quant-buddy-skills, ai-skills. 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: