Skill UI

This skill simulates an autonomous, overnight development cycle by leveraging Git hooks to enforce Test-Driven Development (TDD). It ensures that all code changes, whether building new features, refactoring, or fixing bugs, are rigorously tested and meet high quality standards before commitment. Use this when high code reliability and comprehensive testing are critical requirements.

This guide details how to integrate Vast.ai's GPU provisioning capabilities into automated CI/CD pipelines, such as GitHub Actions. It enables developers to run GPU-accelerated tests, model benchmarks, and validations automatically. Key features include robust instance lifecycle management (provisioning, running, and cleanup) and advanced cost-control mechanisms (e.g., setting budget limits) to ensure reliable and efficient testing in a cloud environment.

This guide outlines critical reliability patterns for integrating advanced AI coding assistants into professional development workflows. It emphasizes best practices such as mandatory Git checkpointing, utilizing dedicated feature branches, breaking large tasks into incremental steps, and implementing comprehensive validation gates (linting, testing). Use this when developing fault-tolerant, AI-assisted applications to prevent accidental code breaks and maintain project stability.

This advanced pipeline orchestrates complex feature development based on Request for Comments (RFCs). It breaks down monolithic changes into small, independently verifiable work units, managing dependencies through a Directed Acyclic Graph (DAG). It includes multiple quality gates, dedicated unit testing, and a safe merge queue to ensure robust integration and controlled deployment.

AWT provides AI coding tools with the ability to perform sophisticated End-to-End (E2E) web testing using a real browser. It accepts declarative YAML scenarios and executes them via Playwright. Key features include visual matching (OpenCV + OCR) instead of relying on fragile DOM selectors, automatic platform detection (React, Vue, etc.), and structured failure diagnosis for improved AI coding workflows.

A comprehensive guide on utilizing Firebase Remote Config within Flutter applications. Learn how to implement dynamic feature flags, execute A/B testing, manage remote parameter defaults, and fetch real-time configuration values. This skill allows developers to modify app behavior and user experiences without requiring an app store update, ensuring fast iteration and efficient product testing.

Master the art of creating, maintaining, and running robust end-to-end (E2E) tests for Flutter applications using the Patrol framework. This skill covers validating complex user journeys, testing interactions with native system features (like permissions and deep links), capturing UI regressions, and ensuring consistent cross-platform behavior across Android, iOS, and Web. Best practice guidelines for deterministic testing are included.

This advanced prompt simulates a Senior Project Manager and DevOps specialist. It takes comprehensive feature artifacts (PRD, technical breakdowns, testing plans) and generates a structured, automated GitHub project plan. It enforces Agile best practices (Epic > Feature > Story > Enabler > Task) and includes templates for issue creation, dependency management, risk assessment, and Definition of Done, ensuring robust project tracking within GitHub.

This comprehensive guide outlines best practices for developing high-quality, idiomatic, and maintainable enterprise applications using Kotlin and Spring Boot. It covers architectural patterns, dependency injection using primary constructors, managing state with data classes, implementing robust RESTful APIs, handling transactions, and leveraging Kotlin features like null safety and Coroutines for asynchronous programming. It also provides guidance on modern testing strategies (Kotest, Testcontainers).

This setup provides a comprehensive local development workflow for integrating with the ClickUp API v2. It includes mock services, unit tests, and live integration testing, enabling developers to build and test ClickUp features efficiently with hot reloading and reliable API mocking, minimizing reliance on live credentials during development.

Automate the entire deployment lifecycle for ML inference services on CoreWeave GPU cloud. This workflow integrates unit testing, container image building (to GHCR), and rolling deployment to CoreWeave Kubernetes clusters via GitHub Actions. Ideal for ensuring stable, high-performance deployment of GPU-dependent models. Key features include validating GPU manifest requests and managing deployments using standard Kubernetes APIs.

This guide establishes a comprehensive local development workflow for building Hootsuite API integrations. It features a robust API client with automatic OAuth 2.0 token refresh, a standardized project structure, and a complete mocked test suite using Vitest. Ideal for developers needing to build reliable, automated social media publishing tools or complex platform connectors.