mx_stocks_screener

基于东方财富数据库,支持通过自然语言输入筛选A港美股、基金、债券等多种资产,支持多元指标筛选,含技术面、消息面、基本面及市场情绪等,可用于全球资产速筛、跨市场监控、投资组合构建、策略回测等场景。返回结果包含数据说明及 csv 文件。Natural language screener for investment assets across global markets, including A-shares, ETFs, bonds, HK and US stocks, and funds. It enables multi-dimensional filtering via technical, fundamental, sentiment and news indicators. Ideal for global asset selection, cross-market monitoring, portfolio construction and strategy backtesting.

3,891 stars

Best use case

mx_stocks_screener is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

基于东方财富数据库,支持通过自然语言输入筛选A港美股、基金、债券等多种资产,支持多元指标筛选,含技术面、消息面、基本面及市场情绪等,可用于全球资产速筛、跨市场监控、投资组合构建、策略回测等场景。返回结果包含数据说明及 csv 文件。Natural language screener for investment assets across global markets, including A-shares, ETFs, bonds, HK and US stocks, and funds. It enables multi-dimensional filtering via technical, fundamental, sentiment and news indicators. Ideal for global asset selection, cross-market monitoring, portfolio construction and strategy backtesting.

Teams using mx_stocks_screener should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/mx-mx-stocks-screener/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/akiry09/mx-mx-stocks-screener/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/mx-mx-stocks-screener/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How mx_stocks_screener Compares

Feature / Agentmx_stocks_screenerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

基于东方财富数据库,支持通过自然语言输入筛选A港美股、基金、债券等多种资产,支持多元指标筛选,含技术面、消息面、基本面及市场情绪等,可用于全球资产速筛、跨市场监控、投资组合构建、策略回测等场景。返回结果包含数据说明及 csv 文件。Natural language screener for investment assets across global markets, including A-shares, ETFs, bonds, HK and US stocks, and funds. It enables multi-dimensional filtering via technical, fundamental, sentiment and news indicators. Ideal for global asset selection, cross-market monitoring, portfolio construction and strategy backtesting.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 选股 / 选板块 / 选基金

通过**自然语言查询**进行选股,数据来自于妙想大模型服务,支持以下类型:
- **A股**、**港股**、**美股**
- **基金**、**ETF**、**可转债**、**板块**

## 密钥来源与安全说明

- 本技能仅使用一个环境变量:`EM_API_KEY`。
- `EM_API_KEY` 由东方财富妙想服务(`https://ai.eastmoney.com/mxClaw`)签发,用于其接口鉴权。
- 在提供密钥前,请先确认密钥来源、可用范围、有效期及是否支持重置/撤销。
- 禁止在代码、提示词、日志或输出文件中硬编码/明文暴露密钥。

## 功能范围

### 基础选股能力
- 按股价、市值、涨跌幅、市盈率等**财务/行情指标**筛选
- 按**技术信号**筛选(如连续上涨、突破均线等)
- 按**主营业务、主要产品**筛选
- 按**行业/概念板块**筛选成分股
- 获取**指数成分股**
- **推荐**股票、基金、板块
- 按多种**复合条件**(如且、或、非、排序等)的逻辑组合筛选

### A股进阶查询(部分场景)
除基础选股外,还支持A股上市公司的以下查询场景:
- 高管信息、股东信息
- 龙虎榜数据
- 分红、并购、增发、回购
- 主营区域
- 券商金股

> **注意**:上述仅为部分示例,实际支持的条件远多于列举内容

### **查询示例**

| 类型     | query                    | select-type |
|----------|--------------------------|----------|
| 选A股   | 股价大于500元的股票、创业板市盈率最低的50只 | A股 |
| 选港股   | 港股的科技龙头                  | 港股 |
| 选美股   | 纳斯达克市值前30、苹果产业链美股   | 美股 |
| 选板块   | 今天涨幅最大板块                 | 板块 |
| 选基金   | 白酒主题基金、新能源混合基金近一年收益排名 | 基金 |
| 选ETF   | 规模超2亿的电力ETF              | ETF |
| 选可转债 | 价格低于110元、溢价率超5个点的可转债 | 可转债 |

## 前提条件

### 1. 注册东方财富妙想账号

访问 https://ai.eastmoney.com/mxClaw 注册账号并获取API_KEY。

### 2. 配置 Token

```bash
# macOS 添加到 ~/.zshrc,Linux 添加到 ~/.bashrc
export EM_API_KEY="your_api_key_here"
```

然后根据系统执行对应的命令:

**macOS:**
```bash
source ~/.zshrc
```

**Linux:**
```bash
source ~/.bashrc
```

### 3. 安装依赖


```bash
pip3 install httpx --user
```

## 快速开始

### 1. 命令行调用

```bash
python3 {baseDir}/scripts/get_data.py --query 股价大于100元,主力流入,成交额排名前50 --select-type A股
```

**输出示例**
```
CSV: /path/to/miaoxiang/mx_stocks_screener/mx_stocks_screener_9535fe18.csv
描述: /path/to/miaoxiang/mx_stocks_screener/mx_stocks_screener_9535fe18_description.txt
行数: 42
```

**参数说明:**

| 参数 | 说明 | 必填 |
|------|------|------|
| `--query` | 自然语言查询条件 | ✅ |
| `--select-type` | 查询领域 | ✅ |

### 2. 代码调用

```python
import asyncio
from pathlib import Path
from scripts.get_data import query_mx_stocks_screener

async def main():
    result = await query_mx_stocks_screener(
        query="A股半导体板块市值前20",
        selectType="A股",
        output_dir=Path("miaoxiang/mx_stocks_screener"),
    )
    if "error" in result:
        print(result["error"])
    else:
        print(result["csv_path"], result["row_count"])

asyncio.run(main())
```

## 输出文件说明

| 文件 | 说明 |
|------|------|
| `mx_stocks_screener_<查询ID>.csv` | 全量数据表,列名为**中文**(由返回的 columns 映射),UTF-8 编码,可用 Excel 或 pandas 打开 |
| `mx_stocks_screener_<查询ID>_description.txt` | 数据说明:查询内容、行数、列名说明等 |

## 环境变量

| 变量                        | 说明                    | 默认 |
|---------------------------|-----------------------|------|
| `MX_STOCKS_SCREENER_OUTPUT_DIR` | CSV 与描述文件的输出目录(可选)    | `miaoxiang/mx_stocks_screener` |
| `EM_API_KEY` | 妙想智能选股工具 API 密钥(必备) | 无 |

## 常见问题

**错误:请设置 EM_API_KEY 环境变量**

- 请访问 https://ai.eastmoney.com/mxClaw 获取`API_KEY`。
- 配置`EM_API_KEY`环境变量


**如何指定输出目录?**
```bash
export MX_STOCKS_SCREENER_OUTPUT_DIR="/path/to/output"
python3 {baseDir}/scripts/get_data.py --query "查询内容" --select-type "查询领域"
```

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