Skill UI

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.

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.

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 comprehensive guide provides templates for integrating MaintainX API testing into automated CI/CD pipelines. It covers multiple stages, including unit tests (mocked), live integration tests against staging environments, and security scans (like gitleaks). Use this when setting up robust, automated quality gates for your MaintainX SaaS integrations.

This comprehensive checklist guides the safe and robust deployment of Mistral AI integrations to a production environment. It covers critical operational steps, including secure credential management, rigorous code quality gates, establishing health endpoints, implementing circuit breakers for resilience, executing gradual rollouts, and defining emergency rollback procedures to ensure system stability and high availability.

This skill coordinates the complex parallel execution of end-to-end, integration, and unit tests across multiple frameworks (e.g., Jest, Playwright, pytest) and CI/CD environments. It manages test splitting, worker allocation, tiered execution strategies, and aggregates results into unified reports. Ideal for optimizing the testing lifecycle and ensuring robust quality assurance in large-scale, multi-component applications. Key functions include intelligent retry logic for flaky tests and building CI pipelines (e.g., GitHub Actions matrix).

Provides comprehensive guidance for setting up and configuring Static Application Security Testing (SAST) tools, including Semgrep, SonarQube, and CodeQL. Learn how to integrate security scanning into CI/CD pipelines, define custom security rules, enforce quality gates, and manage compliance policies to proactively identify and remediate code vulnerabilities across multiple programming languages.

This skill guides the integration of Windsurf workflows into CI/CD pipelines (like GitHub Actions). It provides comprehensive mechanisms for validating configuration files and enforcing AI code quality standards. Use it to automate policy checks, detect hardcoded secrets, ensure sufficient test coverage for new files, and manage complex config deployments across repositories, ensuring highly reliable and compliant code merges.

This policy set establishes comprehensive guardrails for using AI coding assistants (like Windsurf/Cascade). It governs terminal commands, enforces workspace isolation (preventing access to secrets/credentials), and integrates CI/CD gates for code quality. Use this when setting up team development standards, mandatory code review policies for AI output, or implementing secure development pipelines.

This skill provides guidance for implementing tasks using structured workflow patterns, specifically following Conductor's TDD (Test-Driven Development) workflow. It helps manage phase checkpoints, organize git commits, and execute rigorous verification protocols. Use it when adhering to a defined development plan, ensuring quality gates are passed, and managing the entire lifecycle from initial planning to final validation.