Skill UI

This guide provides a step-by-step walkthrough for setting up automated AI code reviews using CodeRabbit. It covers creating the necessary `.coderabbit.yaml` configuration file, defining path-specific instructions, triggering reviews via Pull Requests (PRs), and interacting with the feedback using PR comments or the local CLI. Essential for integrating quality gates into CI/CD workflows.

A comprehensive guide on installing and configuring CodeRabbit AI, an advanced AI-powered code review platform. Learn how to integrate CodeRabbit into your GitHub or GitLab repositories via App installation, CLI setup, and YAML configuration. Use this guide when setting up the service for the first time or connecting it to new repositories to ensure automated, high-quality code reviews on every pull request.

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 comprehensive checklist guides users through the process of elevating CodeRabbit from an optional AI review tool to a mandatory merge gate in a production environment. It covers configuration auditing, technical validation (YAML syntax, review coverage), team onboarding, and setting up branch protection rules to ensure a smooth transition to required status.

This skill provides a comprehensive guide to configuring CodeRabbit for advanced, security-focused code reviews. It teaches how to implement rules for detecting hardcoded secrets, common vulnerabilities (like SQL injection and XSS), and enforcing secure coding standards across APIs, databases, and infrastructure code. Use this when hardening a codebase's security posture or ensuring compliance with industry standards.

This guide helps users manage their CodeRabbit setup, covering plan upgrades (e.g., Free to Pro/Enterprise) and migrating configuration files. It details how to update the .coderabbit.yaml schema to adopt the latest features, advanced workflows, and best practices for enhanced code review automation.

Automates conditional request helper workflows for API development, offering guidance, best practices, and production-ready code/configurations for REST, GraphQL, OpenAPI, and authentication patterns.

This skill is designed to configure a Rails project workspace to function correctly within Conductor, a platform for parallel coding agents. It sets up the necessary scaffolding, including `conductor.json`, executable setup scripts, and server scripts. Additionally, it updates critical Rails configuration files (such as Sidekiq, Cable, and development environment settings) to ensure proper environment variable handling, Redis isolation, and port management for reliable parallel agent execution.

Automates configuration reference generation within technical documentation, offering guidance, best practices, and production-ready code while validating outputs against standards to support API docs, user guides, architecture docs, and automation workflows.

Generates production-ready auto-scaling configurations for apps and infrastructure, covering Kubernetes HPAs and scaling policies so you can handle load spikes, enforce high availability, and keep resource usage efficient.

Generate production-ready load balancer configurations for ALB, NLB, Nginx, or HAProxy based on requirements, and provide ready-to-deploy files for DevOps automation.

Automates Istio and Linkerd configuration for microservices, generating production-ready manifests and setup code tailored to your infrastructure, emphasizing security, observability, and traffic management best practices.