AI Agent Hub
Back to skills
ETF Screener icon

ETF Screener

Professional Updated 2026.08.30

Paste the following prompt into your AI chat to install this skill:

Please follow https://skillhub.cn/install/skillhub.md to install @org-mijzrode/gfetfsearch.

About this skill

Problem

When tracking ETFs, analysts or research scripts often need to narrow down a large product list to ETFs in a specific sector whose one-month return exceeds a threshold, then sort the results by return. ETF Screener turns that query into a reusable skill by calling the Guangfa Securities ETF list API instead of manually assembling endpoint parameters.

How it works

The skill relies on the API key environment variable GF_SKILLS_APIKEY. If the key is missing, it stops the call and points to http://hd.gf.com.cn/skills-market for configuration. It sends a POST request to https://mcp-api.gf.com.cn/gf-skills/skills/mcp/call with:
- service_name: etf_search
- tool_name: finance_api_inclusive_etf_list_get
- args: values such as trakType, roc1m, sort, limit, and addRealTimeRoc

In the example, trakType is set to industry, roc1m uses 5~, and sort uses -roc1m, meaning the top 20 ETFs are returned by descending one-month return. addRealTimeRoc is set to 1 to include real-time return.

Boundaries

This is useful when the caller already has access to the Guangfa Securities MCP service and only needs ETF list filtering. Results depend on API permissions, field semantics, and rate limits; parameters like roc1m and trakType should match the intended business query. The skill does not handle trading, backtesting, or portfolio construction.

Use Cases

  • Research analysts filter ETFs by sector and one-month return before morning briefings, then review the top 20 names.
  • Quant scripts call the API periodically to fetch industry ETFs sorted by one-month return for strategy inputs.
  • Product managers validate ETF selection rules by querying results with specific sector, return, and real-time return fields.
  • Operations staff compile ETF watchlists by pulling candidate lists using sector, return threshold, and sorting parameters.

Best For

  • Research analysts: who need to shortlist ETFs by sector and recent performance.
  • Quant developers: who want to wrap ETF list queries into strategy or preprocessing pipelines.
  • Product operations staff: who maintain ETF watchlists and need top-N results by defined filters.
  • Financial engineers: who debug ETF filtering calls with existing Guangfa Securities API access.