alphaear-news
rkiding/awesome-finance-skills
Fetch real-time finance news, unified trends, and prediction market data from multiple sources.
What is alphaear-news?
Aggregates hot financial news from sources like Weibo, Zhihu, and WallstreetCN, generates unified trend reports, and retrieves Polymarket prediction data. Use when you need current market sentiment, multi-source financial trends, or prediction market insights.
- Fetch hot news from multiple finance sources (Weibo, Zhihu, WallstreetCN, etc.) with configurable count
- Generate unified trend reports aggregating top news across sources
- Retrieve active prediction markets from Polymarket with formatted summaries
- Query local database for cached financial data
How to install alphaear-news
npx skills add https://github.com/rkiding/awesome-finance-skills --skill alphaear-news- Python with requests and loguru libraries installed
- Access to sources.md for valid source identifiers
- Local database setup via database_manager.py
How to use alphaear-news
- 1.Install the skill using npx skills add
- 2.Import NewsNowTools or PolymarketTools from scripts/news_tools.py
- 3.Call fetch_hot_news(source_id, count) with a valid source ID to retrieve news
- 4.Call get_unified_trends(sources) with a list of source IDs to aggregate trends
- 5.Call get_market_summary(limit) to fetch active Polymarket prediction data
- 6.Parse the returned formatted reports for analysis
Use cases
- Monitor real-time financial news sentiment across Chinese and Western finance platforms
- Generate daily or weekly unified trend reports for market analysis
- Track prediction market odds on financial events and outcomes
- Research emerging finance trends across multiple sources simultaneously
- Financial analysts
- Traders and investors
- Finance researchers
- Market sentiment analysts
alphaear-news FAQ
Valid sources are listed in references/sources.md and include Weibo, Zhihu, WallstreetCN, and others; use the source_id parameter to specify which to query.
Yes, use get_unified_trends(sources) and pass a list of source IDs to generate a single aggregated trend report.
Polymarket provides prediction market odds on financial and other events; use get_market_summary() to retrieve active markets for sentiment and probability analysis.
Yes, the skill uses a local database managed by database_manager.py to cache financial data.
Reports are returned as formatted text summaries suitable for direct analysis or further processing.
Full instructions (SKILL.md)
Source of truth, from rkiding/awesome-finance-skills.
name: alphaear-news description: Fetch hot finance news, unified trends, and prediction financial market data. Use when the user needs real-time financial news, trend reports from multiple finance sources (Weibo, Zhihu, WallstreetCN, etc.), or Polymarket finance market prediction data.
AlphaEar News Skill
Overview
Fetch real-time hot news, generate unified trend reports, and retrieve Polymarket prediction data.
Capabilities
1. Fetch Hot News & Trends
Use scripts/news_tools.py via NewsNowTools.
- Fetch News:
fetch_hot_news(source_id, count)- See sources.md for valid
source_ids (e.g.,cls,weibo).
- See sources.md for valid
- Unified Report:
get_unified_trends(sources)- Aggregates top news from multiple sources.
2. Fetch Prediction Markets
Use scripts/news_tools.py via PolymarketTools.
- Market Summary:
get_market_summary(limit)- Returns a formatted report of active prediction markets.
Dependencies
requests,loguruscripts/database_manager.py(Local DB)
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