Diagnose trading-strategy weaknesses and ship Pine v6 or Python modules.
npx skills add https://github.com/Fearvox/data-algo-skill --skill data-algo-fin
Please help me install this Agent Skill. Skill: data-algo-fin Source: https://github.com/Fearvox/data-algo-skill/tree/main/data-algo-fin Command: npx skills add https://github.com/Fearvox/data-algo-skill --skill data-algo-fin
Data-Algo-Fin diagnostically analyzes trading-strategy weaknesses, recommends production-ready patterns, and ships Pine v6 / Python modules to implement fixes within the propfirm-v4 workflow.
.strategy-profile/ for reproducibility.Provide a Pine v6 implementation for the chosen trading pattern and integrate it with the propfirm engine for immediate testing.
High-intent search queries and answers about installing and using this skill.
To diagnose trading strategy weaknesses and regime fit, you evaluate backtest metrics against current market conditions to identify performance degradation. This process proposes 2-3 viable production-ready pattern options with specific trade-offs and generates strategy-profile cards for reproducibility.
Yes, you can ship Pine v6 indicators and Python modules for the same trading strategy. The workflow generates production-ready code for both environments, integrating Pine implementations with the propfirm engine for immediate testing while archiving memory profiles in `.strategy-profile/` for reproducibility.
A strategy-profile card is a diagnostic summary generated to evaluate trading strategy weaknesses and regime fit during backtesting. You need it when transitioning strategies through the Diagnose, Recommend, Decide, and Ship workflow to ensure reproducible results and clear visualization reports.
To transition a trading strategy from backtest to live-paper trading, you apply the propfirm-v4 workflow across the Diagnose, Recommend, Decide, and Ship stages. This generates strategy-profile cards, creates three-panel visual reports, and ships Pine v6 or Python modules for live-paper execution.
Yes, this backtest evaluation workflow supports both Python and Pine script integration. It ships Pine v6 indicators and Python modules as production-ready patterns, applying diagnostic analysis across backtests and live-paper transitions while generating visualization reports within the propfirm-v4 workflow.
Confluence patterns in trading backtests can suffer from regime misfit and overfitting if not properly evaluated. This Skill diagnoses these strategy weaknesses by proposing 2-3 viable pattern options with explicit trade-offs, ensuring you understand the limitations before shipping Pine v6 or Python modules.
Liangwei-zhangTranslate Python backtest strategies into TradingView Pine Script v6.
DrinkBooozAudit Pine Script v6 and Python trading systems with eight-lens adversarial checks.
Gami19Generate a frontend visual strategy with color, typography, and CSS-ready assets.
CambixxBuild, test, and deploy trading strategies for prediction markets in Python.