Skill UI

A comprehensive SDK guide for managing Azure MySQL Flexible Server deployments using C# and the .NET framework. This skill provides workflows for automated resource management, including server creation, database provisioning, configuring firewall rules, tuning server parameters, and integrating Entra ID (Azure AD) for robust security and operational control.

This SDK provides comprehensive management capabilities for Azure PostgreSQL Flexible Server deployments using the .NET framework. It allows developers to programmatically perform core database operations, including creating the server instance, managing databases, configuring firewall rules, and updating server parameters, all through the Azure Resource Manager SDK.

This SDK provides the management plane interface for provisioning and administering Azure SQL resources (servers, databases, firewalls, etc.) using C# and .NET. It allows developers to automate the deployment lifecycle of SQL infrastructure entirely through code, integrating seamlessly with the Azure Resource Manager.

This comprehensive skill guide details essential security best practices for modern application development. It covers identifying and mitigating common vulnerabilities such as hardcoded secrets, SQL injection, XSS, and CSRF. Use this when implementing authentication, handling user input, managing sensitive credentials, or building new API endpoints to ensure robust and secure code.

An expert developer specializing in secure backend coding practices, vulnerability mitigation, and robust API design. Proficient in preventing common attacks such as SQL injection, XSS, and CSRF. Covers comprehensive areas including input validation, authentication mechanisms (OAuth 2.0, MFA), database security, and implementing necessary security headers (CSP, HSTS) for building secure-by-design applications. Ideal for implementing security fixes or building new, hardened backend services.

This skill provides comprehensive guidance on using LibreOffice Base for full-cycle database management. Users can create ODB databases, define schemas, manage tables, and establish relationships. It supports connecting to various external databases (MySQL, PostgreSQL, etc.), performing complex data operations, and automating professional reports and forms using SQL and Python scripting (UNO). Ideal for building data-driven applications.

This skill provides a comprehensive guide to configuring CodeRabbit for advanced, security-focused code reviews. It teaches how to implement rules for detecting hardcoded secrets, common vulnerabilities (like SQL injection and XSS), and enforcing secure coding standards across APIs, databases, and infrastructure code. Use this when hardening a codebase's security posture or ensuring compliance with industry standards.

Compares PostgreSQL or MySQL schemas using the database-diff-tool, produces transaction-safe migration scripts and rollback procedures, and outlines synchronization steps for staging/production deployments.

Provides automated, industry-standard guidance and code for complex SQL joins, visualizations, and BI analyses whenever the “complex join helper” skill is invoked in a data analytics context.

Automates dashboard layout planning for data analytics tasks, guiding best practices, generating robust configs, and validating layouts for SQL-driven BI scenarios.

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.

This comprehensive workflow guides the entire database lifecycle, from initial architecture design (covering both SQL and NoSQL) to advanced implementation, optimization, and maintenance. It covers crucial stages like schema design, implementing migrations, optimizing query performance, developing robust data pipelines (using tools like Airflow and dbt), and managing data quality and operations. Ideal for engineers building complex, production-grade data systems.