Skill UI

The official skill for the XcodeBuildMCP CLI, providing a unified interface for complex Apple development tasks. It streamlines build, test, run, debug, and UI automation across iOS, macOS, watchOS, tvOS, and visionOS. Use this tool to simplify multi-stage workflows and manage project lifecycles without relying on raw, complex xcodebuild commands.

This guide outlines a sophisticated development workflow using dedicated subagents for each independent task within a plan. It mandates a two-stage review process—first for specification compliance, then for code quality—ensuring highly reliable, high-quality, and rapidly iterative development cycles while maintaining strict context isolation.

This comprehensive guide serves as a decision flowchart for developers using Claude Code. It details when to use specific slash commands (/plan, /compact, /loop), select specialized agents (planner, code-reviewer, build-error-resolver), or invoke workflow skills (e2e-testing, tdd-workflow). It helps users select the optimal tool combination for complex tasks across the entire software development lifecycle, including feature planning, bug fixing, testing, and architectural design.

Expert assistance for building, modifying, and debugging Minecraft server plugins for the Paper, Spigot, and Bukkit ecosystems. This includes implementing complex gameplay mechanics such as minigames, advanced combat systems, persistent player progression (perks, economy, quests), custom command handling, and robust state management. We handle configuration, listener registration, and adherence to best practices for Java-based server API usage.

This skill performs comprehensive, feature-level integration validation after all associated development tasks are implemented. It goes beyond checking individual tasks to ensure cross-task consistency, full test suite passage, and complete specification coverage. It validates data flow, architectural adherence, and performs critical security scans for residual issues (e.g., TODOs, hardcoded secrets), providing a holistic GO/NO-GO assessment for deployment. Use this skill as a final quality gate to verify that the completed feature set respects the designed boundaries and dependencies end-...

This skill guides the end-to-end development, implementation, and validation of production-ready Python modules for Azure IoT Edge. It covers critical aspects including telemetry processing, protocol adaptation (Modbus, OPC-UA), local inference, and ensuring robust, secure edge-to-cloud messaging under variable network conditions.

This skill analyzes your entire codebase to ensure it is optimized for AI contributions and developer tooling. It automatically generates essential configuration files such as `AGENTS.md`, Copilot instructions, CI workflows, and customizable issue templates. It learns from your existing PR review patterns to tailor the setup precisely to your project's stack. Use it when you need to prepare a repository for advanced AI-assisted development.

Squirrel is an advanced, full-cycle AI coding skill designed to guide software development from concept to production. It automatically detects the current project state (greenfield, in-progress, or mature) and adapts an 8-phase engineering pipeline. This comprehensive workflow covers planning, building, rigorous testing, bug hunting, code polishing, documentation, and deployment readiness, ensuring high-quality, maintainable results.

Cavecrew provides a set of specialized subagents (investigator, builder, reviewer) designed for efficient code development delegation. Unlike vanilla agents, Cavecrew compresses output results, drastically reducing the token usage injected back into the main context. This allows users to maintain context over much longer, complex coding sessions, effectively preventing context exhaustion during large-scale refactoring, debugging, or multi-step feature development.

This comprehensive, zero-trust security auditor scans third-party AI agent skills before installation. It performs a rigorous 6-phase review process, analyzing surface patterns, script integrity, permissions, and supply chain risks. It is designed to detect malicious payloads, credential theft, instruction overrides, and prompt injection attacks, ensuring secure AI development and deployment.

This skill assesses the AI readiness of a codebase by running a comprehensive audit against multiple technical and governance pillars. It generates a self-contained, detailed HTML dashboard that provides an overall maturity score, identifies strengths, and, most importantly, delivers a prioritized remediation plan (Fix First / Fix Next). Ideal for auditing repositories before major AI feature development.

Manage and apply custom policies to customize readiness scoring across development artifacts. Users can set pass-rate thresholds, override criteria impact, or disable irrelevant checks to tailor scoring to specific organizational standards or project needs. Essential for CI gating and ensuring compliance.