rule breaking pattern detector

The problem

Traders often repeat the same behavioral mistakes without realizing it. Manually auditing journals to find patterns in FOMO entries or stop-loss adjustments is tedious and prone to bias.

What it does

• Identifies recurring violations like chasing, moving stops, and oversizing from raw journal logs.
• Calculates the frequency and impact of specific behavioral errors across your trade history.
• Extracts evidence from trader comments to pinpoint the exact emotional triggers for each mistake.
• Generates structured prevention rules with specific triggers and enforcement mechanisms.

Why this beats prompting it yourself

Generic prompts often miss the nuances of trading mechanics like risk-distance calculations or time-based re-entry windows. This skill uses specific heuristics to differentiate between a valid system exit and an impulsive early exit based on your actual trade data.

Use cases

• Audit monthly trading logs to identify the biggest leak in your PnL.
• Turn emotional venting in journals into a concrete pre-trade checklist.
• Standardize violation reporting for prop firm evaluations or mentor reviews.

Known limitations

Effectiveness depends on the quality of your journal notes. It cannot accurately detect oversizing if you do not record your planned risk or account equity.