Skill UI

A comprehensive guide to structuring effective custom prompts for AI coding assistants like Cursor. Learn the four components of prompt anatomy (Context, Task, Constraints, Format), and utilize reusable templates for complex tasks such as feature implementation, bug fixing, code review, and test generation. Master advanced techniques like Chain of Thought and Few-Shot examples to ensure high-quality, consistent code output.

Defines MCP server tooling with file search, query execution, resource endpoints, prompt templates, and transport configurations alongside a client setup example for streamlined project automation.

This skill enables teams to create, manage, and organize custom prompt libraries for developer workflows within the Cascade environment. Users can build reusable prompt templates for common tasks, including code generation, code review, documentation, debugging, and general software development, ensuring consistency and boosting team efficiency.

Provides architecture design support including ADR templates, system design checklists, scalability assessment prompts, architecture patterns, and API guidance so engineers can document decisions and ensure reliability during technical design phases.

This advanced prompt simulates a Senior Project Manager and DevOps specialist. It takes comprehensive feature artifacts (PRD, technical breakdowns, testing plans) and generates a structured, automated GitHub project plan. It enforces Agile best practices (Epic > Feature > Story > Enabler > Task) and includes templates for issue creation, dependency management, risk assessment, and Definition of Done, ensuring robust project tracking within GitHub.

This utility automates the creation of a complete, production-ready Model Context Protocol (MCP) server project using Java. It generates full source code templates, including configuration, tool handling, resource definitions, and prompt logic. The generator provides robust setup for both Maven and Gradle, ensuring the resulting backend service is structured, scalable, and ready for deployment with support for reactive streams and optional Spring Boot integration.

Design, analyze, and refine Azure infrastructure through natural language prompts, generate interactive architecture diagrams locally with bundled scripts, and produce deployable Bicep templates to automate infrastructure-as-code workflows.