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.

This tool provides comprehensive on-chain analysis for DeFi protocols, allowing users to track metrics like Total Value Locked (TVL), fee revenue, DEX volumes, and yield opportunities. It is essential for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to deep blockchain insights using the DeFiLlama API.

This tool provides comprehensive on-chain analysis for DeFi protocols, allowing users to track metrics like Total Value Locked (TVL), fee revenue, DEX volumes, and yield opportunities. It is essential for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to deep blockchain insights using the DeFiLlama API.

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 building and evaluating classification models by analyzing datasets, selecting features, tuning hyperparameters, and reporting metrics via the classification-model-builder plugin for supervised learning requests.

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.

Builds AutoML pipelines by analyzing user requests, generating code for data preparation, model selection, hyperparameter tuning, validation, and metrics, then documenting artifacts for streamlined automated machine learning workflows.

Provides detailed evaluation of machine learning models using plugin metrics to assess accuracy, precision, recall, F1, and other key indicators, helping users compare models and validate performance before deployment.

This advanced workflow provides comprehensive meeting intelligence by allowing users to search across stored transcripts using keywords and date filters. It integrates the AskFred AI assistant for natural language Q&A over single or cross-meeting data. Furthermore, it aggregates detailed meeting analytics, providing key metrics such as total duration, action items, and top keywords for robust reporting and knowledge retrieval.

Enables Claude to analyze historical time series patterns, select the best forecasting model, and predict future values with confidence intervals for sales, traffic, or other time-dependent metrics.

This skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.