trading confidence rebuilder

    by nowrich

    1

    Reconstruct trading confidence through process-based evidence, rule adherence scoring, and controlled micro-exposure.

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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 just hit a 5% drawdown and I am afraid to take the next trade. I feel like my system stopped working. Can we audit my last 5 trades for process adherence?

    Your agent does

    Let's look at the evidence. For each trade, list: 1. Setup Filter, 2. Timing, 3. Stop Placement, 4. Target, 5. Position Size. Score 1 for followed, 0 for broken. We will ignore the P&L. If your score is >= 4/5, the loss was a market variance, not a failure. Ready to score Trade 1?

    What you get

    Audit recent losses to identify process violations vs. market variance.Create a Rule Adherence Scorecard to track execution quality.Establish a micro-lot re-entry plan to normalize live execution.Build a Trust File of objective competence evidence to review pre-session.

    About this skill

    The problem

    Trading drawdowns often lead to emotional damage where developers and traders lose trust in their systems. This lack of confidence manifests as hesitation, revenge trading, and fear-based execution errors that have nothing to do with technical ability.

    What it does

    • Separates outcome-based P&L from process-based performance metrics.
    • Facilitates neutral replay sessions to rewire perception of past trades.
    • Calculates Rule Adherence Scores to quantify competence regardless of market results.
    • Structures a controlled micro-exposure plan to re-establish live execution trust.
    • Builds an Evidence File of screenshots and logs to replace emotional bias with data.

    Why this beats prompting it yourself

    General LLMs often focus on positive thinking or generic psychological advice. This skill enforces a clinical, process-first methodology that treats confidence as a data problem, ensuring you don't return to full risk before your execution metrics justify it.

    Use cases

    • Recovering from a significant drawdown or account blow-up.
    • Eliminating hesitation when entering valid technical setups.
    • Transitioning from paper trading to live markets with micro-risk.
    • Auditing a losing streak to distinguish between bad luck and system failure.

    How to install

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

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