Custom Options RSI-MACD Algo

I’m building a systematic edge for trading equity options and need a solid algorithmic foundation that combines RSI and MACD signals to fine-tune my overall options strategy. The single objective is clear: optimise the trading strategy itself—entry, exit, sizing and adjustment—rather than simply predicting prices or running a passive risk overlay.

Here’s what I expect at hand-off:
• A clean, well-commented code base (Python, Pine, or AFL—whichever you prefer) that ingests live or historical option data and produces actionable buy/sell outputs.
• Logic that intertwines RSI and MACD parameters in a configurable way so I can tweak look-back periods, thresholds and weighting without rewriting the core.
• Back-test results that demonstrate performance over multiple market regimes, highlighting win-rate, drawdown and profit factor.
• A brief read-me explaining installation, required data feeds and how to adjust settings to reflect different option tactics (covered calls, straddles, iron condors, etc.) should I want to expand later.

If you have experience refining technical-indicator models for derivatives, this should be a concise project; I’m primarily interested in robust, easily extensible code and transparent performance metrics.