Skill UI

Automates correlation analyzer workflows by offering best-practice guidance, executable SQL, visualization tips, and statistical validation for data analytics requests.

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.

deepTools is a Python command-line suite for NGS workflows, converting BAM files into normalized coverage, running QC (fingerprint, correlation, PCA), comparing samples, and rendering heatmaps or profiles for ChIP-seq, RNA-seq, and ATAC-seq analyses.

A comprehensive tool for analyzing long-term health data, tracking trends across multiple dimensions such as weight, vital signs, symptoms, medication adherence, lab results, and mood. It identifies significant changes, correlations between lifestyle factors and health metrics, and provides data-driven insights, risk assessments, and predictive recommendations for proactive health management.

Analyze dietary and nutrient data, identify nutrition patterns, assess nutritional status, and generate personalized improvement advice. Also supports correlation analysis with exercise, sleep, weight, blood pressure, and blood sugar data.

This comprehensive skill analyzes sleep data to identify patterns, assess quality, and detect potential sleep disorders. It tracks trends in sleep duration, efficiency, and consistency, and performs advanced correlation analysis with other health metrics like exercise, diet, and mood. The output provides actionable, personalized recommendations based on scientific data, helping users improve their overall sleep health.

This guide details how to write advanced correlation searches using Splunk's Search Processing Language (SPL). It covers techniques like threshold-based detection, sequence analysis, and anomaly detection to identify sophisticated security threats (e.g., brute force, data exfiltration, lateral movement) in a Security Operations Center (SOC) environment. Mastery of SPL is essential for closing SIEM detection gaps and ensuring compliance.

This skill uses advanced AI and LLM capabilities to correlate fragmented Open Source Intelligence (OSINT) data. It ingests findings from diverse sources—including username enumeration, email lookups, social media, domain records, and breach databases—to generate unified, intelligence-grade profiles. It provides link analysis and confidence scoring, transforming raw data into actionable threat intelligence for target profiling.

Structured pipeline for credit risk pre-loan modeling that loads and formats raw data, filters abnormal periods, trims high-missing/low-IV/high-PSI/high-correlation features, denoises via Null Importance, and exports an Excel cleaning report for review.

DeepTools is a comprehensive command-line toolkit for processing and analyzing high-throughput sequencing data. It supports workflows for ChIP-seq, RNA-seq, ATAC-seq, and other NGS experiments. Core capabilities include converting BAM files to normalized coverage tracks (bigWig), performing quality control (QC), sample correlation analysis, and generating publication-quality visualizations, such as heatmaps and profile plots across genomic regions.

This tool automates the entire process of optimizing investment portfolio allocations using a sophisticated mean-variance engine. Users can set specific risk targets, assess detailed risk metrics (variance, correlation), predict expected returns using neural networks, and generate actionable, step-by-step rebalancing plans. It is designed for quantitative traders managing complex asset baskets and historical pattern analysis.

A comprehensive tool for assessing both portfolio and single-position risk using the neural-trader risk engine. It calculates critical metrics such as VaR, CVaR, and Sharpe Ratio. Furthermore, it provides optimal position sizing recommendations (e.g., Kelly criterion) and checks for market stress signals via circuit breaker status (e.g., loss limits, correlation spikes). Ideal for quantitative analysis and risk management in trading.