What problem does it solve? It turns trading ideas into executable strategy JSON and validates them with real backtest evidence instead of untested prose, so strategy decisions rest on measured Sharpe, drawdown, and trade statistics. ## Core Features & Use Cases - Strategy Design and Backtesting: Converts user-specified entry and exit rules into valid strategy JSON and runs single-range backtests with backtest_run_strategy_tool. - Iterative Optimization: Runs a build-test-analyze-adjust loop with parameter sensitivity comparisons and train/out-of-sample validation. - Walk-Forward Robustness: Uses backtest_walk_forward_tool for multi-period overfitting checks on strategies with four or more years of data. - Use Case: Ask to backtest a 5-minute RSI mean-reversion on NVDA's opening hour; the skill builds the JSON, executes the backtest, and returns a verdict with full metrics and the final executable strategy. ## Quick Start Backtest a long-only RSI mean-reversion strategy on AAPL and MSFT over the last five years and give me the verdict with the final strategy JSON.