mistake to rule converter

    by nowrich

    1

    Converts recurring trading mistakes into objective preventive rules, checklists, and measurable compliance criteria.

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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

    I keep averaging down on losing trades in TSLA when I get angry. I did it twice today on the 5m chart and blew my daily stop. I thought it had to turn around.

    Your agent does

    Rule ID: MC-risk-20231027-001 Preventive Rule: When a 5m trade moves against my stop AND I feel the urge to add to the position, I must close the trade instead of averaging down. Trigger: Price hits SL; feeling of anger/denial. Checklist: [ ] Stop loss hit? [ ] Close now.

    What you get

    Identify root causes of recurring trading errorsCreate objective pre-trade checklists based on past failuresStandardize risk management rules for specific setupsEstablish measurable compliance rates for trading performance reviews

    About this skill

    The problem

    Traders often repeat the same behavioral errors despite knowing they are wrong. Vague resolutions like "I won't revenge trade" fail because they lack objective triggers and measurable enforcement.

    What it does

    • Identifies recurring mistake patterns from raw trade logs or descriptions.
    • Inverts errors into binary preventive rules using specific market conditions.
    • Generates objective checklists for pre-trade, real-time, and post-trade phases.
    • Establishes quantifiable review criteria to track compliance and enforce consequences.

    Why this beats prompting it yourself

    General prompts often produce soft advice or generic psychology tips. This skill enforces a structured conversion process that turns emotional impulses into technical constraints, ensuring every rule has a unique ID, clear trigger conditions, and a mandatory escalation path.

    Use cases

    • Convert emotional revenge trading into mandatory lockout periods.
    • Transform counter-trend entry errors into hard EMA-based filters.
    • Turn position-sizing mistakes into fixed risk-per-trade checklists.
    • Create measurable accountability systems for weekly trading performance reviews.

    Known limitations

    Requires the user to provide market context and emotional triggers to be effective. It is designed for recurring patterns rather than one-off technical glitches.

    How to install

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

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