mx-xuangu

Translate natural-language stock conditions into 东方财富妙想 API queries and return CSV results.

1|1|Updated May 5, 2026
One-click install
npx skills add https://github.com/Ewan-yu/skill-repo --skill mx-xuangu-ewan-yu
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mx-xuangu
Source: https://github.com/Ewan-yu/skill-repo/tree/main/skills/mx-xuangu
Command: npx skills add https://github.com/Ewan-yu/skill-repo --skill mx-xuangu-ewan-yu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests.

What problem does it solve?

It helps users avoid making stock-picking decisions with stale or inaccurate information by translating natural-language selection conditions into rule-based API queries and returning real results.

Core Features & Use Cases

  • Natural-language stock screening: Converts user intent (price, valuation, financial metrics, dividends, sector/board membership) into API-recognized screening rules.
  • Flexible universe selection: Screens stocks and listed companies, supports sector/industry and index/board constituents, and can rank or recommend within those scopes.
  • Deterministic output for analysis: Produces CSV results plus a human-readable description and raw JSON for secondary inspection, enabling repeatable downstream analysis.
  • Use Case: You want “ROE > 15% and net profit grows for three consecutive years” within A-shares; use this Skill to get a filtered list with structured fields you can further analyze.

Quick Start

Ask the AI to run the mx-xuangu skill with a query like: “筛选ROE大于15%且净利润连续三年增长的A股股票,并输出CSV与原始JSON”。

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 by financial metrics like ROE and consecutive net profit growth?

Stock screening by financial metrics like ROE and consecutive net profit growth is done by translating natural-language conditions into structured API rule queries, returning a filtered stock universe with matching results for downstream analysis.

Can I export stock screening results to CSV for further equity analysis?

Yes, stock screening results can be exported to CSV. The skill saves filtered stock universes as CSV files alongside descriptive text and raw JSON outputs, enabling deterministic and repeatable downstream equity analysis.

Do I need an API key to query financial metrics and dividend yield for stock screening?

Yes, an API key is required for querying financial metrics and dividend yield. You must configure the MX_APIKEY environment variable to authenticate HTTPS POST requests to the stock screening API endpoint.

What is the best way to filter sector constituents and index membership for stock recommendations?

Filtering sector constituents and index membership is best handled using rule-based API queries that accept natural-language universe selection conditions, returning structured stock lists ranked or recommended within those specific scopes.

Does natural-language stock screening work with market indicators and valuation ratios?

Natural-language stock screening works with market indicators and valuation ratios by converting user intent into API-recognized screening rules, applying to price, valuation, dividend yield, and sector or board membership conditions.

What are the limitations of using API-based stock screening for A-shares?

Limitations of API-based stock screening include dependency on the MX_APIKEY environment variable for authentication, reliance on HTTPS POST requests to a specific API endpoint, and the constraint that outputs are restricted to structured CSV and raw JSON formats.