Skill UI

This expert skill acts as a master orchestrator for Test-Driven Development (TDD), guiding users through the complete Red-Green-Refactor cycle. It specializes in coordinating complex, multi-agent testing workflows, integrating modern practices like BDD, ATDD, and AI-assisted test generation. Use it to ensure robust, highly maintainable, and thoroughly tested software systems across diverse technological stacks and complex development pipelines.

A comprehensive guide for developing, optimizing, and standardizing skills for AI agents. This resource provides a decision tree for choosing the right architecture (Tier 1-3), incorporating best practices like CSO (LLM SEO) and Anti-Rationalization, and ensuring compliance through rigorous testing and checklists. Essential for robust AI system building.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

Automates the final pre-release verification by running documentation, quality, testing, and security gates through the Centinela QA agent before shipment, then records results and verdict in docs for each version.

This guide details implementing Policy-as-Code using Open Policy Agent (OPA) and Gatekeeper. It covers writing complex Rego policies, deploying OPA Gatekeeper as a Kubernetes admission controller, and integrating policy testing into CI/CD pipelines to enforce security standards across clusters. Ideal for DevSecOps practitioners requiring robust governance.

This skill automates red team operations using the Covenant C2 framework, providing comprehensive capabilities for authorized adversary simulation. It covers the full attack lifecycle, including listener setup, deploying agents (grunts), executing tasks on compromised hosts, and tracking lateral movement via the Covenant API. Ideal for professional penetration testing and security auditing.

This agent facilitates comprehensive debugging and testing of iOS applications running on a simulated environment. It leverages XcodeBuildMCP to manage the entire lifecycle, including building, running, interacting with the UI (tap, type, gesture), taking screenshots, and capturing detailed runtime logs. Use it whenever you need to simulate real-world app testing or diagnose issues on a booted simulator.

This tool enables deep inspection and validation of web applications by connecting to the browser's DevTools Protocol (MCP). It allows agents to perform tasks like DOM inspection, capturing console logs, monitoring network requests, profiling performance, and taking screenshots in a live environment. Essential for debugging UIs, validating API integrations, and performing end-to-end automated testing.

This skill guides users to discover and install specialized agent capabilities from a vast open marketplace. It handles complex natural language queries like "how do I do X" or "find a skill for Y," ensuring the user receives the most relevant, high-quality, and battle-tested tools for development, testing, or design tasks, followed by secure, managed installation procedures.

This skill acts as a comprehensive Go modernization engineer, scanning entire codebases to update outdated patterns, deprecated APIs, and standard library usage. It utilizes multi-agent orchestration to check language features, testing patterns, and tooling/infra, ensuring the codebase adheres to the latest Go idioms for maximum safety and readability. Ideal for CI/CD pipelines or large-scale code reviews.

This skill enables users to create new AI skills from scratch, modify existing ones, and optimize performance through evaluation and benchmarking. It supports iterative development loops, including drafting, testing with prompts, quantitative analysis, and refining descriptions for better triggering accuracy. Ideal for developers building custom agent workflows.