Stock Sentiment AI Assistant
Paste the following prompt into your AI chat to install this skill:
Please install @user_8c7f0f65/topnews according to the guide at https://skillhub.cn/install/skillhub.md.
About this skill
The Problem of Pre-Market Information Overload
Before each trading day opens, investors and traders need to quickly grasp key overnight changes in global markets, breaking financial news, and sentiment signals that might affect the day's trading. However, this information is scattered across numerous websites, news terminals, and market software. Manual collection and filtering are time-consuming and inefficient, making it difficult to effectively integrate perspectives on macroeconomics, policy, and capital flows to quickly assess whether the overall market sentiment is bullish, bearish, or ranging.
How It Works: Data Pipeline and Intelligent Analysis
This skill builds an automated data collection and analysis pipeline that executes the following key steps before market open:
- Multi-Source Data Collection: Via a pre-set cron scheduled task, it automatically pulls data from multiple APIs, including those from East Money, Sina Finance, and Cailian Press. Coverage includes real-time closing prices for the three major U.S. stock indices (Dow Jones, Nasdaq, S&P 500), key futures (FTSE A50, Crude Oil, Gold, Copper), as well as Northbound capital flow and margin trading data.
- Financial Wire Processing & Sentiment Classification: It parses the fetched Cailian Press 24/7 financial wires and uses an algorithm to automatically label the sentiment of each wire (Positive/Negative/Neutral), a core step in constructing market sentiment.
- Structured Briefing Generation & Intelligent Conclusion: It integrates and analyzes the raw collected data, the sentiment-labeled wires, and obtained macroeconomic/policy news. The skill ultimately generates a structured morning briefing and, based on the multi-dimensional data, outputs a qualitative judgment on the day's market environment (Bullish/Bearish/Ranging).
- Execution & Output: Users can trigger the complete process immediately via the run_now action. The skill supports pushing the generated briefing to the user and also offers a collect action for advanced users to retrieve the raw JSON data for custom analysis.
Use Case Boundaries and Considerations
This skill is designed to provide information integration and sentiment prompting services, not investment advice.
- It relies on the stability and availability of third-party data sources (e.g., the East Money API). Changes or rate limits on source interfaces may impact results.
- Sentiment analysis and intelligent conclusions are based on automated rules or models, which may have biases. Investors should use them as supplementary references and combine them with their own analysis for decision-making.
- Prior setup is required, including configuring necessary environment variables as per the .env.example file to ensure normal access to the relevant data interfaces.
Use Cases
- Each trading day at 6:30 AM, a trader needs to quickly understand overnight US stock, futures index movements, and major financial wires before market open to assess the day's A-share sentiment and formulate an opening strategy.
- An individual investor wants to grasp Northbound capital flows, key futures price changes, and official policy points over breakfast via a structured report to serve as a reference for the day's investment decisions.
- An entry-level analyst at a brokerage or fund needs to prepare materials for the morning meeting, requiring a clear market data overview and automatic sentiment classification (positive/negative) of key information to save time on manual compilation.
- A quantitative researcher needs to obtain the scheduled push of sentiment-tagged financial wire raw data (in JSON format) to construct sentiment factors or perform historical backtesting on a strategy.
Best For
- An individual investor or trader who needs to quickly obtain market overviews and sentiment indicators each morning to assist in their trading decisions.
- A research assistant or junior analyst at a brokerage or fund company whose daily work involves preparing morning briefings and compiling market data, with a demand for structured, sentiment-analyzed, semi-finished materials.
- A quantitative finance researcher or strategy developer whose core need is high-quality, formatted, and sentiment-tagged textual data for modeling or factor testing.
- A financial media content creator (blogger or podcast host) who needs timely, accurate market information and unique analytical perspectives to produce daily content, enhancing the professionalism and efficiency of information gathering.
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