Skill UI

Automates creation of acceptance criteria within enterprise workflows, guiding through best practices, generating code and configurations, and validating outputs against standards whenever acceptance criteria creator requests arrive.

Automates the creation of Airflow DAGs for ETL and streaming data workflows, offering best-practice guidance, production-ready code samples, and validation against common pipeline standards.

A specialist tool designed to generate, format, and validate comprehensive technical documentation. It supports multiple standards, including Google/NumPy docstrings (for Python), JSDoc (for TypeScript), and full OpenAPI/Swagger specifications. Key features include automated detection of code languages and frameworks, robust validation of code examples (using tools like doctest and OpenAPI linters), and generating structured user guides or site configurations.

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 skill guides users on fine-tuning CodeRabbit's review quality. It teaches the AI agent team preferences through PR feedback, integrates custom code guidelines (e.g., security policies), allows customization of the review tone, and implements path filters to drastically reduce false positives and noise. This ensures that all code feedback is highly relevant, actionable, and aligns with specific team standards.

Manages CodeRabbit's enterprise access control, seat assignment, and organization-wide policies. This is crucial for large organizations needing centralized control over who receives AI code reviews, defining global coding standards via YAML, and implementing granular Role-Based Access Control (RBAC) across multiple repositories and teams. Use when scaling AI code quality checks across multiple departments.

This comprehensive template provides a production-grade reference architecture for CodeRabbit AI code reviews. It is designed to guide teams in establishing rigorous coding standards by defining specific, best-practice instructions for various layers (API, Database, Authentication, Frontend, CI/CD, Infrastructure). Use this as a robust starting point to build a comprehensive, automated, and secure code quality review process.

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.

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.

Automated guidance for frontend color contrast checking, activated whenever the feature is mentioned; it walks through accessibility patterns, produces production-ready code, and validates results against standards.

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.

Assists container security auditors within the Security Advanced domain by auto-activating when key terms appear, walking through best-practice guidance, producing production-ready code/configurations, and validating results against compliance and threat-modeling standards.