Skill UI

This skill acts as an expert risk manager, providing comprehensive guidance on monitoring portfolio risk, calculating R-multiples, and optimizing position limits. It covers advanced quantitative finance topics such as Value at Risk (VaR), correlation analysis, and stress testing using Monte Carlo simulations. Use it for systematic risk assessment, developing hedging strategies (options/futures), and implementing rigorous risk controls in trading workflows.

This skill provides a comprehensive toolkit for calculating essential portfolio risk metrics. It includes Value at Risk (VaR), Conditional VaR (CVaR), Sharpe Ratio, Sortino Ratio, and drawdown analysis. It is crucial for measuring overall portfolio risk, implementing risk limits, building sophisticated risk dashboards, and ensuring compliance for regulatory reporting in finance.

Automates ROC curve plotting tasks in ML training, guiding data prep, model training, tuning, tracking, and code generation for production-ready results.

Automates schema validation within data pipelines, providing guidance on best practices, workflow orchestration, and streaming ETL scenarios while producing production-ready code and configurations.

This skill functions as an expert-level web researcher, utilizing advanced search strategies (query optimization, domain filtering) to gather, synthesize, and validate information from multiple web sources. It is ideal for complex research tasks requiring fact verification, identifying trends, and producing structured, actionable insights, ensuring high credibility for the final output.

Guides senior data scientists through designing controlled experiments, engineering structured features, training ML models, and translating results into decisions using Python, R, SQL, and tools like Scikit-learn, XGBoost, and MLflow.

Guides production ML engineering with patterns for deploying models, building MLOps pipelines, monitoring drift, integrating LLMs and RAG systems, and enforcing feature-store, retraining, and cost controls in live environments.

Streamlines Simple Analytics tasks by orchestrating Composio toolkits through Rube MCP, guiding tool discovery, connection checks, schema-aware arguments, and execution workflows.

This advanced tool simulates complex DeFi flash loan strategies across major protocols like Aave, dYdX, and Balancer. It calculates net profitability, estimates gas costs, and assesses comprehensive risks (MEV, liquidity, execution). Use it to evaluate arbitrage opportunities, analyze liquidation potential, or compare multiple lending providers before executing real transactions.

Automates sklearn pipeline builder tasks within ML training, activating on relevant triggers to guide data prep, model training, hyperparameter tuning, and experiment tracking with production-ready code and standards validation.

Automates spark job creation within data pipelines by guiding etl, transformation, orchestration, and streaming workflows; includes industry best practices, code templates, and validation to deliver production-ready jobs.

This guide provides advanced patterns and best practices for optimizing Apache Spark jobs. It covers critical areas like effective partitioning, memory tuning, minimizing data skew, and optimizing different types of joins (broadcast, bucket). Use this when troubleshooting slow, large-scale data processing workflows or needing to scale Spark pipelines efficiently and reliably.