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mx-xuangu

Translate natural-language stock conditions into 东方财富妙想 API rules and output CSV.

Updated May 19, 2026
Search Tags:#API integration#financial metrics#equity research#stock screening#sector/industry filter#index constituents
One-click install
npx skills add https://github.com/swf2020/hello-agents --skill mx-xuangu-swf2020
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mx-xuangu
Source: https://github.com/swf2020/hello-agents/tree/main/Co-creation-projects/lcyting-StockSage-agent/skills/%E6%99%BA%E8%83%BD%E9%80%89%E8%82%A1/mx-xuangu
Command: npx skills add https://github.com/swf2020/hello-agents --skill mx-xuangu-swf2020

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you screen A-share stocks using stock and financial conditions, avoiding stale or hallucinated market information by relying on the official 东方财富妙想 API instead of an LLM’s memory.

Core Features & Use Cases

  • Natural-language stock screening: Parses user queries (e.g., price/volume/valuation/financial metrics) into API-recognizable screening rules and returns matching stocks.
  • Sector/industry and index constituent support: Retrieves stocks within a specified industry/sector, listed companies, and constituent stocks of a board/index to support targeted research.
  • Structured outputs for downstream use: Exports results to CSV (with Chinese column mapping) and saves raw JSON for further analysis or iteration.

Quick Start

Set your 东方财富妙想 API Key as the environment variable MX_APIKEY, then run the Python command with your natural-language query to generate a CSV of the screened stocks.

Frequently Asked Questions about mx-xuangu

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

FAQPage Schema
How do I screen A-share stocks using natural language financial metrics?▼

Screen A-share stocks by translating natural-language equity and financial conditions into official 东方财富妙想 API rules, returning real-time matched stock lists without relying on LLM memory.

Can I retrieve index constituent stocks and sector constituents for equity research?▼

Yes, retrieve index constituent stocks, sector constituents, and listed company lists by translating queries into official 东方财富妙想 API rules for targeted equity research.

Do I need an API key to run natural-language stock screening queries?▼

Yes, you must set the 东方财富妙想 API Key as the environment variable MX_APIKEY to authenticate API calls to mkapi2.dfcfs.com before running stock screening queries.

What is the best way to avoid stale market data when screening stocks?▼

Avoid stale market data by using official 东方财富妙想 API integration for stock screening, which fetches real-time results instead of relying on LLM memory or outdated datasets.

How do I export screened stock lists for downstream analysis?▼

Export screened stock lists to CSV with Chinese column mapping and save raw JSON files for auditing or further downstream analysis after running natural-language screening queries.

What are the limitations of using LLM memory for stock screening?▼

LLM memory risks hallucinating market information and providing stale data; using official 东方财富妙想 API rules for stock screening ensures real-time, accurate financial metric filtering.

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