mx_stocks_screener

Filter global investment assets via natural language queries and export CSV.

Updated Apr 2, 2026
One-click install
npx skills add https://github.com/ViewWay/openclaw-skills --skill mx-stocks-screener
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mx_stocks_screener
Source: https://github.com/ViewWay/openclaw-skills/tree/main/mx-stocks-screener
Command: npx skills add https://github.com/ViewWay/openclaw-skills --skill mx-stocks-screener

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires httpx, and includes scripts (resource) components.

What problem does it solve?

This skill enables users to filter global investment assets using natural language queries across A-shares, Hong Kong and US stocks, funds, ETFs, and bonds, dramatically reducing the time to identify relevant opportunities from diverse markets.

Core Features & Use Cases

  • Natural-language screening for stocks, funds, ETFs,板块 across multiple markets with multi-criteria filters including technical signals, fundamentals, and market sentiment.
  • Outputs include a CSV file with Chinese headers and a descriptive说明 to support analysis, backtesting, and portfolio construction.
  • Use Case: quickly locate semiconductor leaders across US and HK markets based on market cap, price movement, and industry exposure, then export a ready-to-analyze dataset for portfolio assembly.

Quick Start

在默认输出目录执行一个示例查询,例如筛选A股科技股市值前50并导出CSV。

Frequently Asked Questions about mx_stocks_screener

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I filter stocks across A-shares, HK, and US markets using natural language?

This stock screener supports cross-market monitoring, portfolio construction, and strategy backtesting by filtering global assets like funds, ETFs, and bonds based on your natural language criteria.

How do I screen for stocks and export the results to CSV?

You can execute a natural language query to screen assets and export the filtered dataset to a CSV file with Chinese headers and a descriptive summary for downstream analysis.

Can I use natural language queries to screen for ETFs and bonds across multiple markets?

Yes, you can use natural language queries to screen for ETFs and bonds across A-shares, Hong Kong, and US markets by specifying technical signals, fundamentals, and market sentiment filters.

Does this cross-market stock screener support strategy backtesting and portfolio construction?

Yes, the screener supports strategy backtesting and portfolio construction by outputting standardized CSV datasets with mapped data fields and descriptive summaries for analysis.

What are the limitations of using NLP search for cross-market stock screening?

While NLP search streamlines cross-market stock screening, you rely on the Python-based MCP integration's data field mapping and robust error handling to ensure reliable CSV outputs for your specific portfolio criteria.

How do I quickly locate semiconductor leaders across US and HK markets based on market cap?

You can quickly locate semiconductor leaders across US and HK markets by running a natural language query that filters by market cap, price movement, and industry exposure to export a ready-to-analyze dataset.