The daily_stock_analysis repository is an AI-driven intelligent analysis system designed for A-shares, Hong Kong, US, Japanese, Korean, and Taiwanese markets. The system automates the generation of comprehensive "decision dashboards" that include core conclusions, sentiment scores, trend analysis, buy/sell signals, and risk warnings. It leverages large language models (LLMs) such as OpenAI, Gemini, Claude, DeepSeek, and local models via Ollama to process multi-dimensional data. Technical implementation supports diverse data sources, including AkShare, Baostock, YFinance, and Longbridge for market quotes, alongside news search engines like Tavily, SerpAPI, and Bocha for sentiment and event analysis. Users can deploy the system via GitHub Actions, Docker, or local cron jobs, with automated reports pushed to platforms like WeChat, Telegram, Discord, and Slack. Key features include an Agent-based strategy query system supporting 15 built-in methodologies—such as Moving Averages, Chan Theory, and Wave Theory—and a Web/Desktop workbench for manual analysis, backtesting, and portfolio management. The system allows for highly customized workflows through environment variable configurations for API keys and notification webhooks, enabling zero-cost deployment using free data sources like AkShare and Baostock.