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name: python-trading-bot description: Generate, refactor, and maintain Python live trading bots for NQ futures prop firm trading (Apex Trader Funding). Supports Databento API for market data, TradersPost for execution, eval/PA modes, custom strategies, and comprehensive production features. Triggers: "live trading bot", "Python bot", "NQ bot", "futures bot", "create bot", "refactor bot", "/bot:new", "/bot:refactor", "/bot:custom". allowed-tools: Read, Write, Edit, Grep, Glob, Bash(pip:, python3:)

Python Trading Bot Skill

Generate, refactor, and maintain production-ready Python trading bots for NQ futures prop firm trading with:

• Databento API for real-time and historical market data
• TradersPost webhooks for order execution (Apex Trader Funding compatible)
• Eval and PA modes with trailing drawdown, profit targets, dynamic sizing
• 5 backtested signals + support for custom strategies
• Production features (state persistence, news filtering, alerting, comprehensive testing)

Commands

Bot Generation

Bot Refactoring

Top 5 Entry Signals

Metrics from 219-day NQ futures backtest (May 2025 - Jan 2026) with ADX di_rising, threshold 35.

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When to Use This Skill

Use this skill when:

• Creating a new live trading bot for NQ futures
• Refactoring or modifying existing trading bots
• Converting eval bots to PA mode (or vice versa)
• Adding features to bots (news filter, alerts, new indicators)
• Building custom strategies beyond the 5 pre-built signals
• Setting up Apex Trader Funding eval or PA accounts
• Implementing prop firm risk management (trailing DD, dynamic sizing)
• Testing strategies with CSV backtest before going live

Do NOT use for:

• Offline backtesting only (use Python/backtest.py instead)
• Creating platform indicators (use indicator-generator skill for TradingView/NinjaTrader/Tradovate)
• Multi-account management (run separate bot instances)
• Non-futures markets (skill optimized for NQ futures)

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Generated Bot Structure

Each generated bot includes these files:

CopyPython/bots/<signal>/
├── bot_<signal>.py              # Main entry point (asyncio)
├── config.py                    # Configuration from .env
├── databento_client.py          # Market data (Databento API)
├── traderspost_client.py        # Order execution (TradersPost webhook)
├── risk_manager.py              # Apex account tracking (eval/PA modes)
├── indicators.py                # Self-contained indicator calculations
├── news_calendar.py             # Economic calendar filtering (optional)
├── alerting.py                  # Email/SMS alerts (optional)
├── bot_state.db                 # SQLite persistence (created at runtime)
├── requirements.txt             # Python dependencies
├── .env.example                 # Credential template
├── .gitignore                   # Exclude .env, logs, *.db
└── README.md                    # Bot documentation

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Bot Architecture

Copy┌─────────────────────────────────────────────────────────────┐
│                    DATABENTO API                             │
│  https://databento.com (real-time & historical 2-min bars)  │
│  + CSV files for backtesting                                 │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│                      PYTHON BOT                              │
│  • Indicator calculation (EMA, ATR, ADX, signal-specific)   │
│  • Signal detection (edge-triggered crossovers)              │
│  • Apex account tracking (eval/PA modes, trailing DD)       │
│  • Position management (SL/TP/trailing stops)               │
│  • Re-entry logic (3 bars wait, ADX > 40)                   │
│  • News calendar filtering (blackout periods)               │
│  • State persistence (SQLite - survive restarts)            │
│  • Alerting (email/SMS on critical events)                  │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│                   TRADERSPOST WEBHOOK                        │
│  POST https://webhooks.traderspost.io/trading/webhook/...   │
│  {ticker, action, quantity, stopLoss, takeProfit}           │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│          BROKER (Tradovate / Apex Trader Funding)           │
│  Order execution, position management, OCO brackets          │
└─────────────────────────────────────────────────────────────┘

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Key Features

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Quick Start

1. Interactive Mode

CopyUser: Create a live trading bot
Assistant: [Runs /bot:new workflow]
  - Step 1: Select signal (keltner, ema_cross, vwap, supertrend, alligator)
  - Step 2: Configure signal parameters
  - Step 3: Set risk parameters (contracts, daily max loss)
  - Step 4: Configure exits (SL, TP, trailing)
  - Step 5: API credentials guidance
  - Step 6: Generate bot files

2. Direct Signal

CopyUser: /bot:keltner
Assistant: [Generates Keltner bot with optimal settings]

3. Quick Mode

CopyUser: /bot:new keltner --quick
Assistant: [Uses all defaults, generates immediately]

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ADX Filter Modes

All 5 modes from backtest.py supported:

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Exit Priority Order

1. Trailing Stop (if active AND hit)
2. Stop Loss (hard protective stop)
3. Take Profit (profit target)

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Skill References

Core Documentation

Configuration Topics

Guides

Signal Details

Templates

Workflows

Examples

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Related Files