/add-strategy

name: add-strategy
description: Create a new trading strategy for the ai-trader backtesting framework. Handles file creation, registration, docstrings, and backtest scaffolding.
disable-model-invocation: true
argument-hint: "[strategy-type: classic|portfolio]"
allowed-tools: "Read, Write, Edit, Glob, Grep, Bash"

add-strategy Skill

Create a new trading strategy for the ai-trader backtesting framework with automatic file generation, registration, and validation.

Overview

This skill automates the creation of trading strategies following established patterns in the ai-trader project. It handles:

• File creation with proper naming conventions (PascalCase class → snake_case filename)
• Comprehensive docstrings (module and class level)
• Parameter validation and defaults
• Automatic registration in `__init__.py` files
• Standalone backtest scaffolding
• Pre-flight validation for name conflicts and custom indicators

Two strategy types are supported:

• **Classic**: Single-stock strategies (e.g., DoubleTopStrategy, BBandsStrategy)
• **Portfolio**: Multi-asset rotation strategies (e.g., ROCRotationStrategy, MultiBBandsRotationStrategy)

Interactive Workflow

The skill guides you through the following steps:

Step 1: Strategy Type

Confirm whether this is a classic (single-stock) or portfolio (multi-asset) strategy.

Step 2: Name & Description

• Provide the strategy name in PascalCase (e.g., "MACDBBands")
• Provide a 1-2 sentence description
• The skill automatically converts to snake_case for the filename (macd_bbands.py)

Step 3: Parameters

Define parameters as comma-separated `name=value` pairs:

• Example: `fast=12, slow=26, signal=9, bb_period=20`
• All parameters must have default values
• Parameter names must be valid Python identifiers

Step 4: Entry & Exit Logic

• Describe the entry condition (buy signal)
• Describe the exit condition (sell signal)
• For portfolio strategies, describe rotation/rebalancing logic

Step 5: Custom Indicators (Optional)

If your strategy uses custom indicators from `indicators.py`, list them:

• Available: DoubleTop, RSRS, NormRSRS, RecentHigh, TripleRSI, etc.
• The skill verifies they exist and generates the import statement

Step 6: Preview & Confirmation

Review the generated file structure before creation:

• Target file path
• Class name and type
• Parameters
• Files to be modified (__init__.py imports and __all__)

Step 7: Creation & Verification

The skill creates:

• Strategy file with complete structure
• Updates imports and __all__ list in __init__.py
• Validates syntax by attempting import
• Shows git status for verification

Usage Examples

Creating a Classic Strategy

$ /add-strategy classic

Creating a classic single-stock strategy.

What should we name this strategy? (e.g., "BollingerBreakout")
> MACDBBands

Brief description (1-2 sentences)?
> Combines MACD for trend and Bollinger Bands for entry timing

Parameters with defaults? (e.g., "fast=12, slow=26, signal=9, bb_period=20")
> fast=12, slow=26, signal=9, bb_period=20, bb_dev=2

Entry condition (buy signal)?
> MACD crosses above signal line AND price below lower Bollinger Band

Exit condition (sell signal)?
> MACD crosses below signal line OR price above upper Bollinger Band

Any custom indicators from indicators.py? (e.g., DoubleTop, RSRS)
> No

[Preview shown]

Proceed with creation? (yes/no)
> yes

✓ Created macd_bbands.py
✓ Updated classic/__init__.py (added import)
✓ Updated classic/__init__.py (added to __all__)
✓ Verified file is importable

Next steps:
1. Test standalone: python ai_trader/backtesting/strategies/classic/macd_bbands.py
2. Review generated code and refine logic
3. Test via CLI: ai-trader quick MACDBBandsStrategy your_data.csv
4. Check changes: git diff
5. Commit when ready

Creating a Portfolio Strategy

$ /add-strategy portfolio

Creating a portfolio multi-asset strategy.

What should we name this strategy? (e.g., "MomentumRotation")
> TripleEMARotation

Brief description?
> Rotates portfolio to assets with strongest triple EMA alignment

Parameters?
> short_ema=10, med_ema=20, long_ema=50, top_k=5

Rotation/Rebalancing logic?
> Rotate monthly to top-5 assets where all three EMAs are bullishly aligned

Custom indicators?
> No

[Preview shown]

Proceed with creation? (yes/no)
> yes

✓ Created triple_ema_rotation.py
✓ Updated portfolio/__init__.py (added import)
✓ Updated portfolio/__init__.py (added to __all__)
✓ Verified file is importable

File Templates

Classic Strategy Template

"""
[Strategy Name]

[1-2 sentence description of what the strategy does and the market conditions it targets.]
"""

import backtrader as bt

from ai_trader.backtesting.strategies.base import BaseStrategy
# [Add custom indicator imports if needed]
# from ai_trader.backtesting.strategies.indicators import CustomIndicator


class [StrategyName]Strategy(BaseStrategy):
    """
    [Strategy Name] - [One-line tagline describing the core approach].

    [Detailed description paragraph explaining the trading logic, market conditions,
    and why this strategy works in those conditions.]

    Entry Logic (Buy):
    - Condition 1
    - Condition 2

    Exit Logic (Sell):
    - Condition 1
    - Condition 2

    Parameters:
    - param_name (type): Description [default: value]

    Notes:
    - Insight 1
    - Insight 2
    """

    params = dict(param1=value1, param2=value2)

    def __init__(self):
        """Initialize indicators and signals."""
        super().__init__()
        # Initialize indicators here
        # self.indicator = bt.indicators.SMA(self.data)

    def next(self):
        """Execute trading logic each bar."""
        if self.position.size == 0:
            # Check buy signal and enter
            pass
        else:
            # Check exit signal and close
            pass


if __name__ == "__main__":
    from ai_trader.utils.backtest import run_backtest

    # Run backtest with [Strat