PT

    paper to live gap analyzer

    by nowrich

    1

    Find why paper-trading results differ from live performance by measuring fills, latency, liquidity, data, psychology, and execution discipline.

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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 my logs: paper_orders.csv shows $500 profit but live_orders.csv shows a $200 loss. Why is there a gap?

    Your agent does

    Gap Analysis Summary

    • Total Gap: -$700
    • Fills: -350 (50%) - Live slippage on AAPL.
    • Latency: -200 (28%) - 1.5s delay in execution.
    • Psychology: -150 (22%) - Manual early exit on TSLA. Recommendation: Use limit orders instead of market orders.

    What you get

    Quantify slippage and fill quality differences between environments.Identify latency bottlenecks in the execution pipeline.Audit manual trading discipline against automated strategy rules.Decompose PnL variance into six core attribution categories.

    About this skill

    Paper to Live Gap Analyzer helps diagnose why a strategy that performs well in simulation may behave differently with real orders and real capital. The skill compares paper and live trade records, synchronizes timestamps, normalizes symbols and order data, and analyzes differences across six major dimensions: fills, latency, liquidity, psychology, data, and execution discipline. Each trade can be tagged by likely gap source while slippage, delayed execution, partial or missing fills, data-feed differences, manual deviations, and rule violations are quantified whenever the available evidence supports it. The final analysis can include paper versus live PnL, trade-by-trade comparisons, slippage measurements, root-cause attribution, percentage contribution by gap category, prioritized recommendations, and targeted experiments for isolating the largest problem. It also avoids automatically blaming live execution when unrealistic paper-trading assumptions may be responsible. Ideal for systematic, discretionary, and algorithmic traders who need to understand where simulated performance is being lost during real execution.

    How to install

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

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