This repository is a production-grade, AI-powered stock analysis platform for CN, HK, US, JP, KR, and TW markets. In production it runs a scheduled analysis pipeline that fetches market data from multiple providers (akshare, yfinance, tushare, efinance, futu, etc.) with priority-based fallback, feeds the data to LLM backends via LiteLLM, generates structured decision reports, and pushes them through 15+ notification channels (WeChat, Feishu, DingTalk, Telegram, email, Discord, Slack, etc.). It also exposes a FastAPI REST API, a React/TypeScript web dashboard, an Electron desktop client, and bot integrations for Feishu/DingTalk/Discord. The system includes agent-based chat with tool use, screening, backtesting, alerts, portfolio management, decision-signal tracking, and market review capabilities.
This repository implements a complete quantitative trading framework for A-shares, known as 'zettaranc-skill'. It is a dual-track project: (1) a Python/Rust software application providing CLI tools, a FastAPI REST API, and a React frontend for stock analysis, backtesting, simulation, screening, and strategy optimization; (2) an AI character-play skill pack that encodes a specific trading methodology (Zettaranc/Shaofu strategies) into a SKILL.md for LLM role-play. The application side dominates: it has 15+ CLI subcommands, a modular architecture with 30+ technical indicators, 20+ strategy detectors, a multi-source data layer (Tushare, Indevs, A-Stock-Data, Hithink, SQLite), a Rust-accelerated backtesting engine (via PyO3), a walk-forward simulation framework, and a self-optimization pipeline. The codebase is well-structured with clean abstractions (DataSource protocol, unified error codes, parameter registration), extensive test coverage, and CI/CD. However, it suffers from some technical drift: dual Python/Rust implementations must stay synchronized, Chinese vernacular naming reduces readability, hardcoded constants persist, and the self-optimizer's LLM judge is a stub. Overall, it is a production-grade personal quant framework with high craftsmanship in its core components.