weekly trading review masterclass

The problem

Trading journals often sit unread, filled with raw data that fails to improve performance. Traders struggle to separate luck from skill, leading to repeated behavioral mistakes and inconsistent risk management.

What it does

• Calculates performance metrics including profit factor, win rate, and R-multiple distribution.
• Classifies every trade into a 2x2 matrix of process quality versus financial outcome.
• Identifies specific behavioral patterns, such as revenge trading or cutting winners short, using trade-level evidence.
• Audits risk behavior to flag position sizing violations and stop-loss tampering.
• Generates three measurable, behavior-focused priorities for the upcoming trading week.

Why this beats prompting it yourself

General LLMs focus on P/L and surface-level encouragement. This skill enforces a professional post-mortem framework that explicitly decouples outcome from process, ensuring you don't reward yourself for profitable mistakes or punish yourself for disciplined losses.

Use cases

• Conducting a Sunday night prep session to analyze the previous week's execution.
• Auditing a specific string of losses to determine if the strategy has failed or if the trader has.
• Tracking compliance with risk limits and position sizing rules over a high-volume period.

Known limitations

Requires specific trade data (entry/exit, instrument, size) to be effective. It cannot predict future market movements or provide financial advice.