take profit planning coach

The problem

Traders often choose profit targets based on gut feeling or greed after entering a position, leading to inconsistent exits and poor risk management. Reactive target selection fails to account for market structure and volatility, often resulting in trades that hit stop losses before reaching arbitrary exit points.

What it does

• Generates rule-based take-profit plans using market structure, liquidity zones, and volatility.
• Calculates minimum risk-to-reward ratios for different setup classes like breakouts or reversals.
• Determines precise exit points based on ATR-adjusted distances and liquidity sweeps.
• Constructs partial-exit logic including breakeven triggers and trailing stop rules.
• Validates trade setups by checking if structural targets satisfy the required R:R profile.

Why this beats prompting it yourself

This skill enforces a rigorous, multi-factor framework that prevents the common bias of "forcing" a target to make a trade look viable. It automates the calculation of volatility-adjusted distances and structural hierarchy, ensuring every exit is backed by institutional order flow data rather than subjective intuition.

Use cases

• Pre-calculating exit levels for a crypto breakout setup based on equal highs.
• Designing a partial-exit strategy for a Forex trend pullback trade.
• Evaluating if a scalp trade has enough ATR room to meet a 1:2 R:R minimum.
• Standardizing exit checklists for a trading journal or proprietary firm evaluation.

Known limitations

Requires specific inputs including entry trigger, stop loss, timeframe, and current ATR. It will refuse to generate a plan if the structural data does not support the minimum risk-to-reward requirements.