Trading strategy development sandbox. User describes trading intent in natural language, agent writes a Python backtest strategy and returns results.
Real data. Real impact.
Growing
Developers
Per week
Open source
Skills give you superpowers. Install in 30 seconds.
Help users develop and backtest trading strategies from natural language descriptions.
Parse the user's trading intent into structured parameters:
Confirm the parsed parameters with the user before proceeding.
Generate a Python backtest strategy using backtrader:
mkdir -p /tmp/trading-devbox && cat > /tmp/trading-devbox/strategy.py << 'PYEOF' import backtrader as bt import sys import jsonclass UserStrategy(bt.Strategy): params = dict( entry_drop_pct=10, take_profit_pct=30, stop_loss_pct=5, )
def __init__(self): self.order = None self.buy_price = None def next(self): if self.order: return if not self.position: # entry: price dropped by entry_drop_pct from recent high high = max(self.data.close.get(size=20) or [self.data.close[0]]) drop = (high - self.data.close[0]) / high * 100 if drop >= self.p.entry_drop_pct: self.order = self.buy() self.buy_price = self.data.close[0] else: pnl = (self.data.close[0] - self.buy_price) / self.buy_price * 100 if pnl >= self.p.take_profit_pct or pnl <= -self.p.stop_loss_pct: self.order = self.sell()if name == 'main': print(json.dumps({"status": "ok", "message": "Strategy generated"})) PYEOF python3 /tmp/trading-devbox/strategy.py
Always respond in the user's language. Structure the response as:
No automatic installation available. Please visit the source repository for installation instructions.
View Installation Instructions
1,500+ AI skills, agents & workflows. Install in 30 seconds. Part of the Torly.ai family.
© 2026 Torly.ai. All rights reserved.