Skill UI

This skill performs a comprehensive security audit of Model Context Protocol (MCP) server configurations found in .mcp.json files. It is designed to identify critical vulnerabilities, including hardcoded secrets (API keys, tokens), dangerous shell injection patterns, unpinned dependencies, and compliance issues regarding approved server lists. Use this skill during security reviews, project onboarding, or pre-commit checks to ensure secure deployment.

This skill automates the comprehensive localization and translation of an entire MkDocs documentation suite. It translates all Markdown files from source English folders into a specified target language, preserving the exact folder structure and Markdown formatting. Additionally, it updates include references and modifies the core mkdocs.yml configuration file to properly support the new locale, ensuring a seamless multilingual documentation setup.

An expert assistant specializing in n8n workflow engineering. It guides users through the entire lifecycle of n8n automation, from initial workspace setup and configuration management to developing, editing, and validating complex workflows using version-controlled TypeScript files. It ensures adherence to n8n best practices and provides access to complete node documentation to prevent parameter hallucination.

This expert guide provides comprehensive knowledge for interpreting and systematically resolving validation errors within n8n workflows. It covers various error types (e.g., missing required fields, type mismatches, invalid expressions) and outlines best practices for iterative validation, including understanding different validation profiles like 'runtime' and 'strict' for various deployment stages. Ideal for debugging complex automation logic.

This tool automates the entire process of creating a complete, production-ready application structure solely from an OpenAPI (Swagger) specification. It analyzes the spec to design the application architecture, generating all necessary layers including controllers, service logic, data models (DTOs), and repositories, adhering to best practices, framework conventions, and separation of concerns. The output includes unit tests, configuration files, and setup instructions, providing a robust, ready-to-use codebase.

A powerful tool that converts complex Unified Modeling Language (UML) diagrams—such as Sequence, Class, Activity, and State diagrams—into plain text ASCII art. This is crucial for documentation in environments that do not support image embedding, such as terminal sessions, README files, or Git commit messages. Supports both standard ASCII and enhanced Unicode ASCII formats for better visual fidelity.

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

Transforms existing code files into highly effective learning resources by adding context-aware educational comments. Acting as an expert educator, this tool tailors explanations—from foundational concepts for beginners to deep architectural insights for advanced practitioners—while strictly maintaining the original file's structure, encoding, and syntax. Ideal for generating self-documenting, pedagogically rich codebases.

Analyzes IaC files and live Azure resources to validate SKUs, usage, and costs, then generates GitHub issues (one per recommendation plus an EPIC) so teams can track implementation of prioritized savings.

Guides teams through creating a complete GitHub Copilot configuration by outlining required instructions, reusable skills, and agent/workflow files tailored to the chosen tech stack and workflow preferences.

A comprehensive template for planning large-scale, multi-file refactoring tasks. It enforces a systematic approach by requiring developers to map out the current state, target state, affected files, and execution phases (Types, Implementation, Tests). Crucially, it mandates detailed verification and a robust rollback plan to ensure code stability during major changes.

Scans repository context and chat history to recommend awesome-copilot Custom Agent files that are missing or outdated locally, outlines relevance/rationale, and waits for user approval before installing or updating.