Skill UI

A comprehensive tool for analyzing Decentralized Exchange (DEX) liquidity pools across major protocols (e.g., Uniswap, Curve). It calculates vital metrics such as Total Value Locked (TVL), trading volume, fee income, and impermanent loss (IL). Use this when comparing LP opportunities, assessing protocol risk, or projecting returns from yield farming.

A comprehensive tool for analyzing Decentralized Exchange (DEX) liquidity pools across major protocols (e.g., Uniswap, Curve). It calculates vital metrics such as Total Value Locked (TVL), trading volume, fee income, and impermanent loss (IL). Use this when comparing LP opportunities, assessing protocol risk, or projecting returns from yield farming.

A comprehensive skill for analyzing Non-Fungible Tokens (NFTs). It fetches collection metadata from APIs (like OpenSea), parses trait attributes, and calculates advanced rarity scores using multiple algorithms (e.g., rarity_score, information entropy). Use this tool to rank tokens by uniqueness, compare specific NFTs, or analyze the distribution of traits within an entire collection, outputting results in JSON or CSV format. Ideal for crypto research and market due diligence.

Automatically activates when chart type recommender needs arise, guiding data analysts through SQL, visualization, statistics, and BI patterns to deliver production-ready recommendations.

This comprehensive framework allows users to validate and test both crypto and traditional trading strategies against extensive historical market data. It calculates essential performance metrics (Sharpe Ratio, Sortino Ratio, Max Drawdown), simulates trade execution, generates equity curves, and includes advanced parameter grid search optimization tools for robust strategy validation.

Automates creating and validating GCP BigQuery views with best-practice guidance, production-ready code snippets, and integrations for Vertex AI, Cloud Run, Firebase, and similar services to keep analytics workloads consistent.

Automates churn analysis workflows by offering guidance, best practices, and production-ready code for SQL, visualization, statistical work, and BI outputs within data analytics projects.

Provides comprehensive monitoring for the Clay data enrichment pipeline. It tracks critical operational metrics such as credit consumption velocity, enrichment success rates (hit rates), data quality scores, and lead distribution. Essential for cost control and ensuring pipeline health in data-intensive CRM workflows.

Automates cohort analysis creation by offering step-by-step analytics guidance, SQL patterns, visualization advice, and validation so analysts can produce production-ready insights within data analytics workflows.

Automates common CTE query builder tasks for data analytics, offering best-practice guidance, production-ready SQL snippets, and validation against standard requirements when you need help with BI, visualization, or statistical analysis.

This skill models the expertise of a senior data scientist, covering the entire data science lifecycle. It provides advanced capabilities in statistical modeling, machine learning (deep learning, XGBoost), predictive analytics, and business intelligence. From raw data exploration (EDA) to deploying production-ready models and creating actionable dashboards, it covers technical depth across Python, R, SQL, and cloud platforms, while applying domain knowledge in finance, marketing, and operations.

A comprehensive guide to implementing best practices for security within Databricks. Learn how to manage secrets using scoped storage, enforce the principle of least privilege via Unity Catalog grants, audit API tokens, and apply advanced data protection techniques like column-level masking and row-level security for enhanced data governance and compliance.