market-debrief-cn

This skill acts as a comprehensive quantitative and qualitative research assistant for the A-share market. Designed for professional traders, analysts, and investors, it automates the end-of-day market review process by synthesizing complex technical data with real-time news sentiment. By employing a multi-agent parallel processing framework, the skill dissects market behavior into six core modules—including macro scanning, sentiment measurement, sector analysis, capital flow, technical indicators, and forward-looking scenario planning. It transforms raw data into high-value insights formatted in an aesthetic, interactive Financial Times-inspired report.

• Multi-Agent Orchestration: Executes dedicated sub-agents for macro-sentiment analysis, sector-fund flow tracking, and technical valuation research to ensure depth and cross-validation.

• Data-Driven Integration: Leverages AkShare for comprehensive financial metrics (index data, PE/PB, capital flow, north-bound funds) and Tavily API for relevant, noise-filtered news events.

• Quantitative Analysis Engine: Processes raw market signals into structured indicators such as ERP (Equity Risk Premium), industry four-quadrant analysis, and technical trend matrices.

• Interactive Visualization: Outputs a structured HTML report featuring dynamic ECharts, providing a clean, professional, and visually consistent reading experience.

• Usage Note: Requires a TAVILY_API_KEY environment variable or a local MCP-auth JWT token to function.

• Input Process: The skill identifies the target trading date (defaults to the latest) and triggers iterative data gathering via scripts/fetch_market_data.py and search_news.py.

• Practical Constraint: Ensure Python dependencies (numpy, pandas, akshare) are installed in the host environment. The logic enforces strict data-source pairing, meaning it will not generate a report without both行情 and news data.

• Output Handling: Follows a strict directory structure (SKILL_ROOT/assets for JSON intermediate files) to maintain project hygiene and data integrity.