order block liquidity zone decoder

    by nowrich

    1

    Decodes market structure to identify order blocks, liquidity pools, and institutional trading setups.

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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 ETHUSD on the 4H timeframe. Price just swept equal lows at 2400 and rejected strongly. Recent swing high is at 2750. There is a fresh unmitigated candle at 2380 from a month ago.

    Your agent does

    SMC Plan for ETHUSD (4H)

    Bias: Bullish Key Levels:

    • Bullish OB: 2380-2410
    • Buy-Side Liquidity: 2750
    • Sell-Side Liquidity: 2350 Trade Scenario:
    • Trigger: Sweep of 2400 into 2380 OB
    • Entry: 2410
    • Stop Loss: 2370
    • Targets: 2600, 2750 Invalidation: Price close below 2380.

    What you get

    Map institutional order blocks and fresh mitigation zones.Locate resting liquidity pools and potential sweep targets.Establish multi-timeframe market bias and structural labels.Generate trade-ready plans with precise invalidation levels.

    About this skill

    The problem

    Manual price action analysis is prone to bias and missing subtle liquidity traps. Identifying precise institutional order blocks and resting liquidity zones across multiple timeframes takes significant mental effort and leads to inconsistent entry points.

    What it does

    • Identifies fresh and tested bullish and bearish order blocks based on impulsive price moves.
    • Maps buy-side and sell-side liquidity pools including equal highs, lows, and breakout points.
    • Defines clear market structure by labeling swing points like HH, LH, HL, and LL.
    • Generates structured SMC trading plans with entry triggers, stop losses, and multi-stage targets.
    • Determines invalidation levels based on candle closes beyond structural boundaries.

    Why this beats prompting it yourself

    Generic LLMs often confuse basic support/resistance with institutional order blocks or fail to account for liquidity sweeps. This skill enforces strict Smart Money Concepts logic, ensuring that bias is derived from structure and entries are only planned at high-probability mitigation zones.

    Use cases

    • Identify institutional footprint in crypto, forex, or equity markets.
    • Find high-probability entry zones by spotting liquidity sweeps into order blocks.
    • Establish directional bias by analyzing internal vs. external market structure.
    • Draft objective trading plans with predefined invalidation criteria.

    How to install

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

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