According to AlphaMoat, as of 2026-09, joinquant聚宽平台的策略助手,DR成熟框架 has 1,969 downloads and 2 stars — ranked #4,452 of 5,078 AI skills overall, and #390 of 465 in Professional.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 26 | 969 | 1 | 1 |
| SkillHub ↗ | 236 | 2.0K | 2 | — |
Platforms count differently and update at different times.
This skill provides templates and references for writing JoinQuant (聚宽) quantitative strategies in Cursor: strategy templates cover basic, dual-strategy, and ETF rotation; code snippets cover data fetching (historical/financial), order handling (orders/cancellation), risk control (stop-loss, take-profit, position sizing), and technical analysis; API references split into core, data, and order functions; plus a full momentum-ETF example strategy. Use /template to pick a template, /snippet for snippets, and /api <function> for lookups. Code is reference-only — apply risk management, backtest validation, and platform rules.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 2.0K | — | 2 |
| 2026-08 | 1.5K | +15.0% | 2 |
| 2026-07 | 1.3K | — | 2 |
| 2026-05 | 884 | — | 2 |
| 2026-03 | 475 | — | 1 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
# joinquant-strategy Skill 帮助在Cursor中编写聚宽(JoinQuant)量化策略的工具集。 ## 主要功能 - 提供聚宽策略的标准模板 - 包含常用代码片段 - 提供API快速参考 - 集成最佳实践示例
## 目录结构
```
joinquant-strategy/
├── README.md # Skill 说明文档
├── templates/ # 策略模板目录
│ ├── basic_template.py # 基础策略模板
│ ├── dual_strategy_template.py # 双策略模板
│ └── etf_rotation_template.py # ETF轮动策略模板
├── snippets/ # 代码片段目录
│ ├── data_fetching.md # 数据获取常用代码
│ ├── order_handling.md # 下单处理代码
│ ├── risk_control.md # 风险控制代码
│ └── technical_analysis.md # 技术分析代码
├── api_reference/ # API参考文档
│ ├── core_functions.md # 核心函数说明
│ ├── data_functions.md # 数据获取函数说明
│ └── order_functions.md # 下单函数说明
└── examples/ # 示例策略
└── momentum_etf_strategy.py # 动量ETF策略
```
## 功能说明
### 策略模板
- **basic_template.py**: 基础策略模板,包含完整的策略结构和基本逻辑
- **dual_strategy_template.py**: 双策略模板,基于示例实现的双策略框架
- **etf_rotation_template.py**: ETF轮动策略模板,用于实现ETF轮动交易策略
### 代码片段
- **data_fetching.md**: 数据获取常用代码,包括历史数据、财务数据等获取方法
- **order_handling.md**: 下单处理代码,包括委托下单、撤单等操作
- **risk_control.md**: 风险控制代码,包括止损、止盈、仓位管理等
- **technical_analysis.md**: 技术分析代码,包括常用技术指标计算
### API参考文档
- **core_functions.md**: 核心函数说明,包括策略初始化、运行等核心功能
- **data_functions.md**: 数据获取函数说明,详细介绍数据API的使用方法
- **order_functions.md**: 下单函数说明,详细介绍下单API的使用方法
### 示例策略
- **momentum_etf_strategy.py**: 动量ETF策略,基于示例整理的完整策略实现
## 使用方法
在Cursor中使用此skill时,可以:
1. **快速开始**:使用`/template`命令选择策略模板
2. **代码补全**:输入`/snippet`查看常用代码片段
3. **API查询**:输入`/api 函数名`快速查看API用法
4. **最佳实践**:参考`examples/`目录学习复杂策略的编写
## 注意事项
- 本工具包提供的代码和模板仅供参考,实际使用时需要根据具体情况进行调整
- 策略开发过程中,应注意风险管理和回测验证
- 请遵守 JoinQuant 平台的相关规定和限制
## 版本信息
- 版本: 1.0.0
- 最后更新: 2026-03-10
A data-interface skill that pulls A-share quotes, financials, and sector data through the AkShare library.
Query Eastmoney financial data in natural language and get Excel plus Markdown tables back.
Help organize China-patent materials, search questions, and technical-disclosure drafts.
Financial data skill: query structured market data via the westock CLI.
A local-first market research skill that reads Yahoo Finance data for quotes and fundamentals and renders charts with technical panels.
A valuation analysis skill for A-share and Hong Kong stocks built on a value investing framework.
A script for A-share quotes, intraday volume breakdowns, and portfolio tracking.
Watch watchlist quotes and technical indicators, then push alerts ranked by severity when conditions fire.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.