breakout fakeout detector

The problem

Traders often lose capital by chasing price breakouts that lack institutional support, leading to costly "fakeout" traps. Manual analysis frequently overlooks critical volume and liquidity signals, resulting in emotional entries at price extremes.

What it does

• Evaluates breakout quality using a 60-point quantitative framework covering location, volume, and displacement.
• Filters out low-conviction moves by analyzing retest behavior and liquidity targets.
• Provides a standardized quality score and classification to remove emotional bias from trade entries.
• Generates structured risk management actions based on objective price action data.

Why this beats prompting it yourself

This skill enforces a rigid scoring system that prevents the LLM from being "fooled" by a single positive indicator like price alone. It implements hard override rules for volume and displacement that generic prompts often ignore. You get a consistent, repeatable audit trail for every trade setup.

Use cases

• Vetting a potential long entry after a resistance break on a 4h chart.
• Identifying false breakdowns in low-volume environments to avoid stop-outs.
• Auditing historical trades to identify why specific breakouts failed to follow through.
• Scaling position sizes based on the quantified quality score of a setup.

Known limitations

Requires manual input of volume and candle data if not connected to a live data feed. Performance depends on the accuracy of the user provided support and resistance levels.