Skill UI

Automates CodeQL database builds, suite selection, and taint-aware scans to surface security and quality issues across supported languages, handling output directories, SARIF results, and extensions in one workflow.

This skill executes CodeRabbit's core workflow, providing automated, in-depth code reviews directly on pull requests. It analyzes code diffs based on custom rules (e.g., API validation, DB security), generates detailed walkthrough summaries, and posts line-level feedback. Ideal for setting up robust CI/CD quality gates and maintaining high code standards throughout the development lifecycle.

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 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 automatically generates comprehensive and highly structured Pull Request (PR) descriptions directly from Git diffs. It goes beyond simple summaries by automatically adding detailed change categories (e.g., source, test, config), security risk assessments, and required review checklists based on the modified file types. Use this when submitting complex code changes or when the diff is large and requires explicit structure for thorough review.

This skill converts vague coding requests into a highly structured, actionable, and atomic development plan. It guides the user through defining the approach, scope (In/Out), and breaking down the task into a mandatory checklist of ordered, concrete steps (e.g., discovery, implementation, validation). Ideal for ensuring comprehensive and traceable project development workflows.

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

Automates cross-browser compatibility verification by orchestrating BrowserStack, Selenium Grid, or Playwright runs across Chrome, Firefox, Safari, and Edge, capturing screenshots/logs and producing a report when requested via `/browser-test`/`/bt` to confirm web app behavior across devices.

This skill provides a comprehensive, actionable overview of the Conductor project's status. It aggregates information from project plans, active tracks, and detailed specifications to display overall progress, identify next critical tasks, and flag potential blockers. Use it when you need a high-level dashboard view of project health and required actions.

This skill validates the completeness, consistency, and correctness of Conductor project artifacts. It checks for the existence of required directories, verifies essential project documentation (like index.md, product.md, etc.), and confirms adherence to established naming and status patterns. Use this tool after setup, when diagnosing issues, or before implementation to ensure the project context is sound.

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