Skill UI

This comprehensive guide details the implementation of Firebase In-App Messaging within Flutter applications. It covers setup, programmatic message triggering and suppression during critical flows (like payments), and essential privacy controls for GDPR compliance. Learn best practices for testing campaigns, utilizing A/B testing, and managing the full lifecycle of in-app message campaigns.

A disciplined workflow that forces you to build in thin vertical slices, test, verify, and commit each working increment before moving on, ideal for multi-file features or large refactors.

Creates a structured spec before coding, covering objectives, commands, structure, style, tests, boundaries, and success criteria so teams surface assumptions and validate each phase before implementation.

Test-driven development requires writing a failing test before any implementation so logic, bug fixes, and behavioral changes are always backed by proof; it is ideal for guarding refactors and ensuring regressions stay caught by the automated suite.

This meta-skill provides a comprehensive guide through the entire software development lifecycle (SDLC). It teaches senior-level engineering discipline, covering everything from vague idea refinement and specification design to planning, implementation, testing, code review, and deployment. It emphasizes core behaviors like surfacing assumptions, managing ambiguity, maintaining scope discipline, and enforcing technical simplicity.

This advanced prompt acts as a structured guide for generating comprehensive, enterprise-grade technical implementation plans. It forces the detailed breakdown of a feature based on a PRD, covering system architecture (Mermaid diagrams), database schema design, API specifications, frontend component hierarchy, and deployment strategies, all while adhering to a monorepo structure. Ideal for large-scale SaaS development.

This tool analyzes specification files to extract all defined requirements and cross-references them with the current codebase implementation status. It systematically checks for unimplemented features, searches existing GitHub issues to prevent duplicates, and automatically generates detailed issues using a standardized feature request template. It is essential for robust product management, ensuring every defined requirement is tracked and scheduled for development.

A comprehensive methodology guiding technical professionals through the design process before coding. It helps structure complex features by producing detailed design documents, including system overviews, data models, API specifications, multiple trade-off analyses, and implementation plans, ensuring robustness and clarity from the start.

A comprehensive code review tool designed for C#/.NET projects. It evaluates the implementation of key design patterns (Command, Factory, Repository) and adherence to SOLID principles. The review covers architecture, best practices (async/await, logging), security, testability, and clean code principles, providing actionable recommendations for improvement.

A comprehensive workflow for discovering, integrating, and utilizing third-party APIs and SDKs. This skill guides the process by first detecting the project language, ensuring necessary guidelines and skills are present, systematically fetching API details, and providing structured guidance on authentication, model usage, and endpoint implementation. It tracks integration progress by recording specific development milestones (e.g., SDK setup, first call made).

This guide provides comprehensive patterns for migrating Enzyme unit tests to React Testing Library (RTL), especially when upgrading to React 18. It emphasizes the crucial philosophical shift from testing internal implementation details (like state or props) to asserting visible user behavior. Learn best practices for rewriting shallow/mount/simulate calls into modern, accessible, and resilient RTL queries, ensuring your tests reflect how a user genuinely interacts with the component.

A comprehensive tool that analyzes existing codebases to generate detailed, definitive architectural blueprints. It automatically detects technology stacks, identifies architectural patterns (e.g., Microservices, Clean Architecture), and documents implementation details, including dependency flow, cross-cutting concerns (security, logging), and data models. This ensures architectural consistency, aids in onboarding new team members, and guides future development efforts.