Hi everyone, I’m working on EasyQuant, an AI coding assistant for generating, explaining, and revising TradingView Pine Script.
One challenge we’re interested in is how a short trading instruction becomes a precise implementation. For example:
“Enter when a candle closes above the previous day’s high. Place the stop at the previous day’s low, allow only one open position, and exit at twice the initial risk.”
That description still leaves several implementation questions:
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Does “previous day” follow the exchange’s session or the chart’s calendar day?
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Should an entry require a fresh crossover, or any close above the level?
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Are the stop and target fixed at entry, or recalculated as new bars arrive?
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Should the signal appear only after the candle is confirmed?
EasyQuant helps turn written requirements into code that can be inspected and revised. The aim is to make the interpretation easier to examine—not to treat generated code or a backtest as proof that a strategy works.
For a rule like this, I would start by checking the session boundaries, plotting the reference levels, and comparing expected entries against individual candles before evaluating performance.
For people building or using AI coding tools: which validation step catches the most mistakes—clarifying the specification, reviewing the code, or inspecting its behavior on a chart?
EasyQuant: https://tradingviewai.dev