How does this skill handle real-time updates?

It utilizes an EventBus to broadcast Domain Events (like TranslationUpdated). These events are consumed by WebSocket handlers that push updates to connected clients for instant collaboration.

Is this architecture compatible with microservices?

Yes, the event-driven nature and modular directory structure make it easy to extract specific domains into independent microservices if the application grows.

Does it support asynchronous background tasks?

Absolutely. It integrates with workers (like BullMQ) to process events such as AI translations or webhooks without blocking the main API response.

What is CQRS-lite in the context of this skill?

CQRS-lite is a simplified version of Command Query Responsibility Segregation that separates write operations (Commands) from read operations (Queries) within the same data store, improving code maintainability and scalability.

Lingx Backend Architecture

Name: Lingx Backend Architecture
Author: VinniZP

byVinniZP

0•

API 开发

Standardizes backend development using CQRS-lite and event-driven patterns for scalable translation management.

This skill provides comprehensive architectural guidance for the Lingx backend, implementing a CQRS-lite and event-driven pattern designed for high-performance translation management systems. It assists developers in maintaining a strict separation between read and write operations, managing asynchronous tasks via an EventBus, and implementing real-time collaboration features through WebSockets. By enforcing a modular directory structure and standardized command/query handlers, it ensures codebase consistency, testability, and scalability for complex features like AI-assisted translation and live presence tracking.

主要功能

010 GitHub stars

02Real-time collaboration patterns via WebSocket broadcasting and presence management

03Event-driven architecture support using BullMQ for asynchronous side effects

04Modular directory structure guidance for organized domain logic

05Standardized command and query handler generation for consistent code patterns

06CQRS-lite pattern implementation for clear separation of reads and writes

使用场景

01Refactoring legacy services into the modular CQRS-lite structure

02Implementing new backend features like bulk translation imports or project management

03Designing real-time synchronization for collaborative translation workbenches

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add vinnizp/lingx target-be-architecture

For use in Claude.ai and ChatGPT

Download Skill