Beginner Stock Watchlist Manager

What It Solves

Stock watchlist management often breaks down in practical places: too many candidates, incomplete fundamentals, no consistent status for stop-loss and target prices, and no post-trade review trail. This skill organizes tracking into four tiers: Tier 1 sea-selection pool (50-100 names), Tier 2 watch pool (20-30 names), Tier 3 core pool (10-15 names), and Tier 4 trading pool (3-5 names). It stores state in a local SQLite database at ./data/stock_pools.db, which fits daily watchlists, stop-loss checks, and after-market review.

How It Works

• Pool management: Perform CRUD operations across the four pools. Add, query, move, update, or remove stocks. The core pool tracks entry points, stop-loss levels, target prices, and position suggestions; the trading pool further records planned/actual fill prices, cost basis, and unrealized P&L.
• Data refresh: scripts/data_fetcher.py wraps akshare for market and fundamentals data, while scripts/pool_manager.py handles persistence.
• Screening rules: Tier 1 filters include non-ST/*ST, market cap, and listing age. Tier 2 adds checks around average ROE, gross margin stability, and leverage. Later-stage checks include whether price breaks below the stop-loss level or whether turnover stays below 50 million for five consecutive days.
• Alert monitoring: scripts/alerter.py flags states in red, yellow, green, and blue using rules involving price, target levels, PE, ROE, and debt ratio, making it easier to spot positions that need attention.
• Post-market review: scripts/review.py generates daily/weekly/monthly reports, and scripts/cli.py acts as the command-line entry point that dispatches tasks to the other modules.

Limits

This skill is decision support only and is not investment advice. akshare is an open-source data source and quotes may be delayed. Alerts require human confirmation before any actual trade. Price and ratio inputs must be valid numbers, and pool maintenance automatically runs elimination checks.