Skill UI

Learn how to integrate CodeRabbit as a mandatory Continuous Integration (CI) gate within your GitHub repository. This comprehensive guide demonstrates setting up branch protection rules, creating GitHub Actions workflows, and enforcing CodeRabbit's reviews to ensure high code quality before merging. Includes advanced setup for PR size checks and notification mechanisms.

A comprehensive collection of patterns and best practices for automating GitHub workflows using advanced AI models. This skill enables automated PR reviews, sophisticated issue triage (labeling and commenting), and seamless integration of AI into CI/CD pipelines, significantly enhancing DevOps efficiency and code quality assurance.

A comprehensive guide featuring best practices and patterns for building robust GitLab CI/CD pipelines. Covers multi-stage deployments, containerization (Docker), infrastructure as code (Terraform), security scanning, caching strategies, and advanced GitOps workflows for automated testing and deployment to Kubernetes.

A comprehensive guide detailing how to implement declarative, Git-based continuous delivery for Kubernetes. It covers setup using industry-leading tools like ArgoCD and Flux CD, adhering to OpenGitOps principles for automated, reliable, and traceable application deployments and infrastructure management.

An expert guide for designing, implementing, and optimizing large-scale, secure, and highly available cloud-native infrastructure using Kubernetes. Covers advanced topics including GitOps workflows (ArgoCD/Flux), service mesh architecture (Istio), multi-cluster management, Policy as Code (OPA), and infrastructure automation with Terraform. Ideal for platform engineers building enterprise-grade container orchestration solutions.

This skill provides comprehensive guidance and tools for end-to-end software release management. It automates critical tasks such as generating changelogs from conventional commits, determining semantic version bumps (Major/Minor/Patch), assessing release readiness, and planning complex deployment workflows (e.g., Git Flow). Ideal for teams adopting robust DevOps practices.

A structured workflow designed to prevent 'reinventing the wheel.' Before writing custom code, this skill guides the user through analyzing needs, conducting parallel searches across multiple channels (npm, PyPI, GitHub, MCP), evaluating candidate solutions based on maintainability and community support, and making a decision (Adopt, Extend, or Custom Build). It ensures that solutions leverage existing, proven libraries and patterns.

Generates practical and robust CI/CD pipelines by programmatically detecting the project's entire technology stack (language, runtime, tooling). It provides fast baseline setup for GitHub Actions or GitLab CI, ensuring repeatability, environment awareness, and alignment with project dependencies. Ideal for onboarding new repositories, standardizing DevOps workflows, or migrating existing deployment processes.

This expert skill performs non-intrusive static analysis to thoroughly audit AI skills and bundles. It identifies malicious patterns, data leaks, system stability risks, and obfuscated payloads across major operating systems (Windows, macOS, Linux/Unix) and mobile platforms (Android/iOS). Use it when verifying skill legitimacy or performing deep cross-platform security reviews.

A comprehensive guide and workflow for investigating compromised Docker containers. This tool assists digital forensic experts in analyzing layers, volumes, logs, runtime artifacts, and host configurations to identify malicious activity, privilege escalation attempts, and system breaches during incident response.

Comprehensive digital forensic analysis guide for Linux systems. It covers the collection and examination of critical artifacts such as authentication logs, shell histories, user configurations, system files (passwd, shadow), and persistence mechanisms to effectively detect security compromises, unauthorized access, and malicious activity.

This guide details advanced digital forensics techniques for recovering deleted file metadata and content from NTFS volumes. It focuses on analyzing the Master File Table (MFT), USN Journals, and $LogFile transaction records. Techniques include parsing MFT slack space and utilizing specialized tools like MFTECmd to reconstruct file system timelines and identify deleted evidence remnants.