discipline habit builder

    by nowrich

    1

    Converts trading plans into actionable daily checklists and weighted discipline scorecards.

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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 struggle with over-trading and moving my stop losses. I trade the NYSE open and usually have 30 minutes to prep. Help me build a discipline routine.

    Your agent does

    Execution Habit Checklist

    | Trigger | Required Behavior | Pass/Fail | | :--- | :--- | :--- | | Placing an order | Set stop loss in platform before clicking 'Buy/Sell' | [ ] | | Price hits stop | Close platform for 15 minutes to prevent revenge trading | [ ] | | After 3rd trade | Log out of broker regardless of PnL | [ ] |

    Daily Compliance Score: (Passed / Total) x 100

    What you get

    Convert abstract trading rules into observable 'If-Then' habit loops.Generate weighted compliance scores to track rule adherence quantitatively.Build time-blocked pre-market routines tailored to specific market sessions.Create high-pressure execution prompts to prevent impulsive trade entries.

    About this skill

    The problem

    Trading plans often fail because rules are too abstract to follow under pressure. Traders struggle to bridge the gap between "don't be greedy" and the actual physical actions required during a live session.

    What it does

    • Converts vague trading rules into concrete "If-Then" implementation intentions.
    • Generates time-blocked pre-market checklists for session preparation.
    • Creates execution habit prompts to maintain discipline during live price action.
    • Builds a mathematical compliance scoring system to track process adherence.
    • Develops post-market review templates for objective performance analysis.

    Why this beats prompting it yourself

    Generic prompts result in vague advice that doesn't hold up during market volatility. This skill enforces a structured habit-stacking framework and a weighted scoring engine that turns qualitative discipline into quantitative data you can actually optimize.

    Use cases

    • Transforming a PDF trading plan into a daily interactive checklist.
    • Creating a structured routine for traders prone to revenge trading or over-leveraging.
    • Establishing a standardized post-session debrief to identify rule-breaking patterns.
    • Building a weighted performance scorecard to measure process over PnL.

    How to install

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

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