Skill UI

This skill guides the comprehensive, multi-step rollout of CodeRabbit AI code review across an entire organization. It covers setting organization-level defaults, customizing team-specific review rules (e.g., API security, frontend performance), and automating deployment via multi-repo scripts and branch protection enforcement. Use when establishing standardized, high-quality AI code review practices company-wide.

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.

Monitor the effectiveness and adoption of AI code reviews using CodeRabbit. This skill calculates critical metrics including review coverage percentage, time-to-first-review, and comment acceptance rates. It is ideal for building organizational dashboards to maintain high code quality and optimize development workflows.

This skill provides comprehensive patterns and scripts for managing rate limits when automating workflows involving CodeRabbit and the GitHub API. It covers both CodeRabbit's internal review limits and GitHub's core API limits, including best practices for safe pagination, GraphQL usage, and local caching to ensure robust, reliable automation.

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 comprehensive guide details how to implement robust webhook endpoints for CodeRabbit, an AI-powered code review tool. It covers essential security practices, including signature validation (HMAC-SHA256), and provides structured methods for handling various event types (e.g., PR reviews, check run completions, comments). Use this skill when integrating CodeRabbit into CI/CD pipelines to automate notifications, track metrics, and enforce quality gates.

This skill provides professional, AI-powered code review, integrated with Codex AI. It is designed to ensure high code quality before commits, automatically generate comprehensive CHANGELOGs, and assist in managing large-scale refactoring projects efficiently.

This skill generates commit messages strictly following Sentry's conventions and the Conventional Commit format. It mandates a structured commit message including a type, scope, subject, body (explaining what and why), and a footer for issue references. Use this whenever committing code changes to ensure a highly readable, traceable, and standardized version history.

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.

This skill guides the execution of development tasks defined in a structured implementation plan, strictly following the Test-Driven Development (TDD) workflow. It manages the entire development lifecycle, including pre-flight checks, context loading, task identification, writing failing tests, implementing minimal code, refactoring, committing changes, and performing phase-wise verification. Ideal for managing complex, structured software development projects.

This skill provides comprehensive management for the entire track lifecycle within a Conductor system. It allows users to perform critical operations such as archiving, restoring, deleting, renaming tracks, and cleaning up orphaned artifacts. Use it when managing track status across active, completed, or archived states to ensure data integrity and system organization.