Skill UI

LEX is a structured truth engine designed to eliminate legal hallucinations by grounding AI agents in verified government references and legislation across 29+ jurisdictions (including US, EU, and CA). It provides deterministic context for comparing legal requirements, drafting compliant business, and employment documents, ensuring high jurisdictional accuracy.

This skill guides SOC analysts and detection engineers on how to correlate complex, multi-stage attacks within the IBM QRadar SIEM platform. It covers advanced usage of AQL (Ariel Query Language) for deep event investigation, building custom correlation rules (Building Blocks and Offenses), and cross-source data correlation (e.g., auth failures with network flows). It is essential for reducing false positives and improving threat detection accuracy.

Provides a detailed, multi-platform workflow to monitor long-running computational experiments. It checks the status of jobs across various environments (SSH, vast.ai, Modal), collects screen logs, fetches structured JSON results, and pulls detailed training metrics (loss curves, accuracy) from Weights & Biases (W&B). Essential for MLOps and automated result review.

This guide details how to perform authenticated (credentialed) vulnerability scans using industry-leading tools like Nessus, Qualys, and OpenVAS. By utilizing service credentials (SSH, SMB, WinRM, SNMPv3), the scan moves beyond superficial banner checks to deeply inspect installed patches, configurations, and local system settings on Linux, Windows, and network devices. This is crucial for detecting vulnerabilities that unauthenticated scans often miss, significantly improving security assessment accuracy.

A comprehensive guide for Security Operations Center (SOC) analysts on reducing false positive alerts in SIEM systems. Techniques include systematic threshold tuning, refining correlation logic, implementing allowlisting, and enriching data with threat intelligence to combat alert fatigue and improve detection accuracy.

This skill enforces a rigorous, 5-phase debugging protocol (Reproduce, Isolate, Root Cause, Fix, Verify) for AI coding agents. It forces a disciplined approach, preventing agents from guessing fixes or making premature edits. Use this when debugging complex, intermittent, or hard-to-isolate bugs to ensure the root cause is fully confirmed before any code changes are applied, maximizing debugging accuracy.

An automated verification system designed for critical healthcare application deployments (EMR/EHR). This harness enforces stringent patient safety standards by running multiple mandatory test gates, including Clinical Decision Support System (CDSS) accuracy, Protected Health Information (PHI) leakage prevention, and data integrity checks. A single failure in critical gates automatically blocks deployment, ensuring regulatory compliance and optimal patient safety in the CI/CD pipeline.

This comprehensive tool generates high-quality Mermaid diagram code (including flowcharts, sequence diagrams, ER diagrams, etc.) directly from natural language user requirements. It handles complex structured output, mandatory syntax validation using dedicated CLI tools, and detailed visual review to ensure the accuracy of all components and connections.

This tool is designed to enhance lead intelligence by processing and analyzing prospect data. It helps users gain deep insights into potential customers, improving targeting accuracy, optimizing sales pipelines, and refining marketing strategies for business growth.

This expert tool provides deep, systematic auditing of datasets to assess completeness, consistency, accuracy, and structural validity. It performs full data profiling, detects anomalies (outliers), analyzes missing data mechanisms (MCAR/MAR/MNAR), and calculates a Data Quality Score (DQS). Use it when validating data for model training, debugging pipelines, or establishing ongoing monitoring checks.

An AI communication style that minimizes token usage while maintaining technical accuracy. It removes filler words, articles, and hedging, adhering to Simplified Technical English principles. Offers intensity levels from lite to ultra and classical Chinese variants for maximum brevity and clarity in technical contexts.

This skill enables users to create new AI skills from scratch, modify existing ones, and optimize performance through evaluation and benchmarking. It supports iterative development loops, including drafting, testing with prompts, quantitative analysis, and refining descriptions for better triggering accuracy. Ideal for developers building custom agent workflows.