Skill UI

This skill generates a detailed, multi-phase plan for complex, multi-file refactoring projects. It ensures safety by first analyzing the codebase, identifying dependencies, and structuring changes in a safe sequence (e.g., Types first, then implementations, followed by tests and cleanup). It forces the AI to output a comprehensive plan, including rollback steps and verification points, and waits for user confirmation before making any actual code changes.

Acts as a senior software engineer to meticulously review and refactor entire codebases. This skill ensures that the code is clean, highly maintainable, and strictly adheres to defined coding standards and best practices specified across multiple project instruction files. It guarantees the integrity of the existing file structure and ensures all unit tests remain passing after modifications.

This structured prompt guides an AI model to proactively analyze a user's question and systematically list all necessary files for accurate answering. It forces the AI to categorize required context into 'Must See' (critical), 'Should See' (helpful), 'Already Have,' and 'Uncertainties.' Ideal for complex coding tasks, debugging, or feature implementation that spans multiple codebase files.

This skill guides the parallel assignment of specialized agents when debugging multiple, independent failure domains. Instead of using one agent for all issues, isolate each problem (e.g., a specific test file or subsystem) to its own dedicated agent. This allows agents to work concurrently without sharing context or interfering with each other, significantly accelerating the debugging process and maintaining context purity.

A comprehensive guide to setting up and managing Continuous Integration and Continuous Deployment (CI/CD) pipelines within KubeSphere. This tool integrates with Jenkins, supports both graphical editing and Jenkinsfile-based workflows, and enables automated deployments across multi-cluster environments using ArgoCD for GitOps management. Ideal for managing the full software delivery lifecycle.

This skill integrates the agent with the Matrix/Element messaging platform. It enables full conversational capabilities, allowing users to receive real-time alerts, search content, and control connected systems (such as cameras) directly from a designated Matrix room. It supports multi-turn interactions, including sending files, reacting, editing, and managing threads.

A comprehensive guide to optimizing performance when integrating with the Figma REST API. Techniques cover aggressive response caching (LRU), reducing payload size using depth parameters, batching multiple node fetches, and implementing webhook-driven cache invalidation. Essential for handling large, complex Figma files efficiently.

A powerful pre-action hook designed to enforce rigorous checks before AI agents modify code, create files, or execute destructive commands. Instead of relying on superficial self-evaluation, GateGuard forces the LLM to gather concrete facts (like dependencies, data schemas, and impacted modules), significantly improving code reliability and architectural depth. It provides multiple gates for edits, writes, and destructive bash commands.

A comprehensive guide on implementing robust Role-Based Access Control (RBAC) for Klaviyo integrations. It details how to use scoped API keys and OAuth 2.0 flows to define granular read/write permissions across various resources (profiles, campaigns, events). This is essential for building secure, multi-tenant applications that require precise permission management.

FastMCP CLI provides a unified command-line interface to interact with Model Context Protocol (MCP) servers. It allows users to discover available tools and invoke them programmatically using `fastmcp list` and `fastmcp call`. The CLI supports various server targets (HTTP URLs, local files, configs), complex argument types, and ensures structured output, making it essential for building automated, multi-tool workflows and system integrations.

This skill automatically converts structured data specifications (such as CSV, JSON schemas, SQL DDL, or Protobuf definitions) into functional, production-ready code. It generates complete models, validation logic, full CRUD API endpoints, and unit tests in multiple languages (Python, TypeScript, Go, etc.), significantly reducing boilerplate coding time and ensuring type safety.

This guide demonstrates core functionalities for integrating with Hootsuite using its REST API. It provides complete examples on how to list connected social profiles, schedule posts across multiple networks (Twitter, Facebook, etc.), and retrieve pending messages. It is ideal for developers starting a new social media automation tool or needing to test basic API posting patterns.