Skill UI

This skill provides production patterns for implementing robust data quality validation using Great Expectations, dbt tests, and formal data contracts. It is essential for building reliable, automated, and verifiable data pipelines, ensuring data integrity throughout the entire ETL/ELT process, and establishing clear data governance rules.

A comprehensive tool for tracking and analyzing cryptocurrency derivatives markets. It aggregates key metrics such as funding rates, open interest, liquidations, and options flow across major CEX and DEX exchanges. Use it to identify arbitrage opportunities, gauge market sentiment, predict trend strength, and perform deep risk analysis on perpetual swaps and futures contracts.

Analyzes options chain data by separating real calls and puts from lottery-like speculative contracts to produce more reliable put/call sentiment, anomaly detection, and expiry breakdowns for watchlists, sectors, and event-driven names.

This meta-skill is designed for complex decision analysis when a user provides or references structured documents such as contracts, quotes, spreadsheets, or notices. Instead of simple summarization, it extracts key evidence, identifies risks (e.g., renewal risk, payment terms), and structures the output into decision-ready formats, such as 'sign/reject/negotiate' recommendations, evidence tables, or required next actions. It supports input from PDF, DOCX, and XLSX formats.

This guide details how to assemble a comprehensive, reproducible replication package for academic manuscripts, especially in fields relying on complex institutional data (e.g., court records, contracts). It mandates creating a one-command master script, documenting the entire data pipeline from raw sources to final exhibits, and providing detailed protocols for hand-coded variables and data provenance. The goal is to ensure that any researcher can perfectly reproduce every finding.

A specialized skill designed to convert complex legal materials—such as contracts, matter descriptions, corporate structures, timelines, or compliance processes—into context-appropriate, structured Mermaid diagrams. It utilizes a multi-step process involving structured data extraction, LLM enrichment, and mandatory gates to ensure accuracy. Ideal for visualizing relationships, obligations, and flows in legal documents, but strictly limited to legal or legal-adjacent diagrams.