Skill UI

A comprehensive utility designed to manage and automate the safe migration of applications using the Apollo.io API. It guides developers through auditing current API usage, identifying deprecated endpoints and authentication methods, and implementing feature-flagged changes. Key features include generating migration maps and running shadow tests for parallel comparison between old and new API versions, ensuring zero downtime during major system upgrades.

This expert skill guides advanced integration with Atlassian products (Jira and Confluence) using the MCP protocol. It covers full lifecycle management, including setting up OAuth/API token authentication, designing complex JQL/CQL queries, automating sprint workflows, syncing documentation, and robust debugging of API calls. Ideal for system architects and developers building cohesive enterprise workflows.

This expert skill guides advanced integration with Atlassian products (Jira and Confluence) using the MCP protocol. It covers full lifecycle management, including setting up OAuth/API token authentication, designing complex JQL/CQL queries, automating sprint workflows, syncing documentation, and robust debugging of API calls. Ideal for system architects and developers building cohesive enterprise workflows.

A guide for building secure, scalable, and robust authentication and authorization systems. This skill covers industry-standard practices, including OAuth2, JWT, OIDC, RBAC, and session management, helping developers design secure APIs and identity infrastructure.

A guide for building secure, scalable, and robust authentication and authorization systems. This skill covers industry-standard practices, including OAuth2, JWT, OIDC, RBAC, and session management, helping developers design secure APIs and identity infrastructure.

A comprehensive platform designed for building, deploying, and managing continuous, autonomous AI agents. Users can create complex, multi-step automation workflows using a visual, drag-and-drop node editor, or extend functionality using a dedicated developer toolkit. Ideal for implementing persistent agents triggered by webhooks, schedules, or manual input, enabling sophisticated, end-to-end AI automation pipelines.

A comprehensive platform designed for building, deploying, and managing continuous, autonomous AI agents. Users can create complex, multi-step automation workflows using a visual, drag-and-drop node editor, or extend functionality using a dedicated developer toolkit. Ideal for implementing persistent agents triggered by webhooks, schedules, or manual input, enabling sophisticated, end-to-end AI automation pipelines.

A comprehensive guide detailing best practices for creating modern, clean, and highly maintainable user interfaces using Avalonia and Zafiro.Avalonia. It emphasizes leveraging semantic containers, defining shared styles, and utilizing generic components to dramatically reduce XAML redundancy and improve code structure. Learn to adopt patterns like Behaviors over Converters, and prevent deep nesting for optimal developer experience.

A comprehensive solution for deploying multi-service, containerized applications (frontend + backend) to Azure Container Apps. This utility uses the Azure Developer CLI (azd) to manage the entire lifecycle, ensuring idempotent infrastructure provisioning, remote builds, managed identity integration, and robust environment configuration across development, staging, and production environments.

A comprehensive solution for deploying multi-service, containerized applications (frontend + backend) to Azure Container Apps. This utility uses the Azure Developer CLI (azd) to manage the entire lifecycle, ensuring idempotent infrastructure provisioning, remote builds, managed identity integration, and robust environment configuration across development, staging, and production environments.

This SDK allows developers to build robust anomaly detection applications in Java using Azure AI services. It supports both univariate and multivariate time-series analysis, enabling detection of outliers, trend changes, and correlated signals over large datasets. Ideal for real-time monitoring, operational intelligence, and advanced data quality checks.

This SDK allows developers to build robust anomaly detection applications in Java using Azure AI services. It supports both univariate and multivariate time-series analysis, enabling detection of outliers, trend changes, and correlated signals over large datasets. Ideal for real-time monitoring, operational intelligence, and advanced data quality checks.