daily_stock_analysis ships AI stock dashboards

The interesting part here is not the stock-picking angle, it’s the automation stack: this is closer to an AI research pipeline than a chatbot wrapped around market data. The project is practical, forkable, and built for unattended runs, which makes it more useful than most “AI finance” demos.

• –Multi-source inputs matter more than a flashy model name here; the system combines quotes, news, announcements, capital flow, and fundamentals into one daily output
• –GitHub Actions plus optional Docker/local deployment keeps it genuinely low-friction and low-cost to run
• –The dashboard format is the right abstraction for retail workflows: score, thesis, risks, and action checklist instead of raw LLM prose
• –Broad push support is a real product feature, not a nice-to-have; users can route the same analysis into the tools they already live in
• –The main risk is signal quality, not execution: if the source mix or prompt logic is weak, the dashboard will still look confident