Skill UI

A comprehensive guide to configuring and maximizing the potential of Claude Code, an advanced agentic coding tool. This resource details best practices, setup templates (CLAUDE.md), advanced prompting techniques (e.g., thinking keywords), and debugging strategies for building reliable, complex software autonomously.

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.

Recommends suitable Nano Banana Pro image generation prompts from a 6000+ library, guiding users through direct image requests or illustrating existing articles, videos, or podcasts with matched prompt templates.

This skill specializes in designing, optimizing, and evaluating prompts for Large Language Models (LLMs). It allows users to generate optimized prompt templates, structured output schemas (e.g., JSON mode, function calling), and comprehensive test suites. Use this skill when building new LLM applications, implementing complex reasoning patterns like Chain-of-Thought, defining system guardrails, or building robust evaluation frameworks to measure and improve model performance.

Guides engineers through advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability across few-shot learning, reasoning patterns, templates, and system prompt design.

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.

This skill provides comprehensive techniques for optimizing prompts used with any Large Language Model (LLM). It teaches proven methodologies—including Role definition (R), Context setting (S), Constraints (C), Instructions (I), and Templates (T)—to transform vague inputs into precision-engineered instructions. Users can reliably achieve structured JSON output, implement Chain-of-Thought reasoning, reduce hallucinations, and minimize token usage, ensuring consistent and high-quality results across different AI platforms.

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.

Sanitize user prompts through Google Model Armor templates via the gws CLI command, ensuring outbound safety and supporting stdin, text, or explicit JSON inputs for prompt filtering.

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.