by gaaiyun · Agent Tool · ★ 91
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/gaaiyun/joinquant-skill.gitTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 91 |
| Forks | 19 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 61/100 |
| Open Issues | 1 |
| Last Updated | 2026-11-02 |
| Created | 2026-04-18 |
| Platforms | claude-code, python |
| Est. Tokens | ~16k |
JoinQuant Skill 让 AI agent（Cursor / Claude Code / Codex / OpenCode 等）能正确生成符合聚宽（JoinQuant）平台的量化策略代码。 项目本身不教 AI 做策略，而是给 AI 一份结构化的 API 知识库、可粘贴运行的策略模板、静态检查工具、因子库与单因子分析工具，以及一条把券商研报变成聚宽策略代码的流水线。所有产物都被组织成一个可 install 的 skill，被 Cursor / Claude Code / MCP 客户端按需检索。 一、它解决什么具体问题 用 Claude / Cursor 写聚宽策略时反复遇到的几个坑： 模型乱编 API：让它写 DiD 它返回 ；让它写聚宽策略它返回 ——这些函数都不存在。 数据 API 与回测 API 混淆：聚宽的 在回测里和研究里行为不一样，模型常不分场景乱用。...
Looking for a joinquant-skill alternative? If you're comparing joinquant-skill with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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
宽宝 QuantBuddy： 一整套面向Agent Invesment投资研究与决策的底层设施与能力的调用skill， 覆盖A股/港股/美股/期货/宏观/ETF的量化分析与计算。支持行情、估值、财务查询、选股筛选、因子计
Quantitative factor research skills for AI coding assistants
AI Agent Team-拥有24/7专业AI开发团队：产品经理、前端开发、后端开发、测试工程师、DevOps工程师、技术负责人。一键安装，支持中英文命令，大幅提升开发效率！
A股数据分析、量化选股与模拟交易 Skill 集合，支持实时行情、历史K线、技术指标、自定义交易策略与模拟买入、卖出交易账户
An Self-Evolving Stock Strategy Research Agent 策略回测和自我进化
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: