ai strategy code reviewer

    by nowrich

    1

    Audit AI-generated trading strategies for lookahead bias, repainting, and unrealistic execution logic.

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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

    Review this Pine Script strategy. It uses request.security to get daily data for a 15-minute timeframe crossover. I'm getting 90% win rate and want to check for lookahead bias.

    Your agent does

    Summary

    Verdict: FAIL Severity count: Critical: 1, Major: 0, Minor: 1

    Issues Found

    Issue 1

    • Severity: Critical
    • Category: Lookahead
    • Description: request.security is called without barmerge.lookahead_off.
    • Impact: Accesses future daily closes.

    What you get

    Detect lookahead bias in backtests to prevent false performance metrics.Identify state management errors that cause incorrect position tracking.Verify position-sizing logic to ensure account equity is protected.Audit order execution realism including slippage and commission assumptions.

    About this skill

    The problem

    AI-generated trading strategies often produce impossible backtest results due to lookahead bias and repainting. These scripts frequently lack the safeguards and execution realism required to survive live market conditions without blowing up an account.

    What it does

    • Audits code for lookahead bias and repainting that invalidates backtest results.
    • Identifies state management bugs where position flags fail to reset or update correctly.
    • Verifies position-sizing math to ensure risk calculations and lot sizes are accurate.
    • Checks for unrealistic order execution like zero-slippage fills or same-bar entries/exits.
    • Flags missing safeguards such as drawdown limits, cooldown periods, and input validation.

    Frameworks & tools

    Pine Script (TradingView), Python (backtesting.py, Backtrader, vectorbt, zipline), C# (NinjaScript), and MQL4/MQL5.

    Why this beats prompting it yourself

    Standard LLMs often overlook subtle indexing errors or framework-specific quirks like Pine Script's barmerge behavior. This skill applies a rigid, multi-point audit process specifically designed to catch the "too good to be true" bugs that generic prompts miss.

    Use cases

    • Reviewing a Pine Script strategy before deploying it to a TradingView alert.
    • Auditing a Python backtest for hidden future-data leakage in dataframes.
    • Validating the risk management logic of an MQL5 Expert Advisor.
    • Converting a backtest-only script into a live-ready execution bot.

    Known limitations

    Cannot verify external data quality or broker-side execution latency. Assumes standard framework behavior unless custom libraries are fully provided.

    How to install

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

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