Skill UI

Changelog Creator automatically surfaces best practices for DevOps basics by guiding requests that mention changelog creator, recommending version-control tips, container checks, and CI/CD fundamentals while also validating outputs and generating ready-to-use code/configurations.

Bash Script Helper automatically assists with foundational DevOps bash scripting tasks, guiding users through best practices, pattern explanations, and producing ready-to-use code or configurations while validating outputs.

A comprehensive, multi-phase workflow designed for creating production-ready Bash scripts. This guide covers the entire development lifecycle, including defensive pattern implementation, structured error handling (traps, retry logic), logging strategies, rigorous unit testing using Bats, and professional documentation. Ideal for system administration, CI/CD automation, and core DevOps scripting.

A comprehensive technical guide detailing essential patterns and techniques for analyzing compiled binaries. It covers foundational assembly concepts across x86-64, ARM architectures, and provides structured examples for function prologues, calling conventions, control flow (loops, branches), data structure access, and common arithmetic/string operations. Essential for reverse engineering and low-level systems programming.

Automated branch-naming guidance that activates within DevOps Basics to help teams follow consistent Git conventions, enforce patterns, and align naming with CI/CD and infrastructure workflows.

Creates production-ready GitOps workflows for ArgoCD or Flux, producing manifests, repository layout guidance, and deployment instructions tailored to the user’s infrastructure so Kubernetes clusters stay in sync with Git.

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

An expert AI specialist that integrates advanced static analysis (e.g., CodeQL, SonarQube) with modern DevOps practices. It performs multi-layered code reviews, checking for security vulnerabilities, performance bottlenecks, architectural flaws, and adherence to best practices across various languages. Ideal for CI/CD pipelines and pull request validation.

A comprehensive guide to optimizing costs associated with AI code review tools like CodeRabbit. Learn strategies for right-sizing seat allocation, scoping services to high-value repositories, and implementing granular file filters to minimize unnecessary AI processing and billing overhead. Essential for managing SaaS spend in a DevOps environment.

A comprehensive, phased guide detailing how to migrate your code review process to CodeRabbit. It covers the entire journey, from assessing current tools (like SonarCloud, DeepSource, or manual reviews) and mapping existing rules, through to running a parallel pilot phase and finally achieving full adoption. Ideal for engineering managers or DevOps teams planning a major CI/CD tool transition.

This skill details how to configure CodeRabbit review behavior using a `.coderabbit.yaml` file placed on base branches. It enables setting tailored code quality gates across the development lifecycle, allowing for relaxed reviews on feature branches and highly stringent, security-focused checks for production or release environments, ensuring quality matches risk.

This pattern demonstrates how to automate workflows around CodeRabbit reviews. By utilizing GitHub API, TypeScript, and Bash scripting, users can programmatically fetch review results, extract detailed line-level comments, trigger specific CodeRabbit actions (like 'summary' or 'resolve'), and implement CI/CD gates to enforce quality standards before merging.