choppy market avoidance coach

    by nowrich

    1

    Technical market regime filter to detect choppy ranges and prevent overtrading during low-volatility compression.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    See it in action

    You say

    Analyze the current BTC/USD 15m chart. ATR is down 25%, price is bouncing between 64200 and 64500 for 4 hours, and the last upside break closed back inside within 2 candles.

    Your agent does

    Regime: Choppy Filter Status: No-trade Key Levels: 64200, 64500 Reason: Volatility compression (ATR -25%) and failed upside breakout. Price is oscillating in a narrow 300-point band with no directional conviction. Stand aside.

    What you get

    Identify low-quality ranges using ATR and Bollinger Band compression.Detect failed breakouts and liquidity sweeps to avoid fakeouts.Quantify momentum follow-through to validate directional moves.Enforce no-trade zones when structural conditions are poor.

    About this skill

    The problem

    Traders often lose capital by overtrading in sideways markets where breakouts lack follow-through. Identifying the transition from a trending environment to a low-quality, choppy range is difficult in real-time.

    What it does

    • Analyzes price structure to detect narrow bands and flat trendlines.
    • Tracks failed breakouts and liquidity sweeps to identify fakeouts.
    • Monitors volatility compression using ATR and Bollinger Band width.
    • Measures momentum follow-through relative to ATR to confirm directional conviction.
    • Applies strict no-trade filters when market conditions favor capital preservation over entry.

    Why this beats prompting it yourself

    Generic prompts often miss the technical nuances of volatility compression and structural failure. This skill uses a multi-factor detection framework, combining ATR analysis, Bollinger Band percentiles, and candle body overlap to provide a binary trade/no-trade decision based on objective math rather than intuition.

    Use cases

    • Screening intraday setups to avoid entering during lunch-hour lulls.
    • Filtering breakout strategies during periods of low volume or high indecision.
    • Validating trend continuation after a period of consolidation.
    • Automating capital preservation rules during compressed market regimes.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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