real-time-backend

Name: real-time-backend
Availability: InStock
Author: Convex

Design reactive, type-safe backends with schema-first data modeling.

9|3|Updated Nov 28, 2025

Search Tags:#architecture #backend #real-time #type-safe #reactive #server-functions #schema-first

Ready to run

npx skills add https://github.com/get-convex/components-submissions-directory --skill real-time-backend-get-convex

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: real-time-backend
Source: https://github.com/get-convex/components-submissions-directory/tree/main/.claude/skills/real-time-backend
Command: npx skills add https://github.com/get-convex/components-submissions-directory --skill real-time-backend-get-convex

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Builds reactive, type-safe production-grade backends with strong contracts, live data semantics, and maintainable server logic to replace brittle, ad-hoc architectures.

Core Features & Use Cases

Reactive by default with live data updates and deterministic reads
Server-mediated data access with centralized auth, validation, and business rules
Schema-first data modeling that generates types and ensures end-to-end safety
End-to-end DX for AI agents to discover operations and call them safely
End-to-end transactional guarantees and predictable error handling
Use cases cover APIs, data models, server functions, scheduled jobs, and web/mobile backends

Quick Start

Describe your backend requirements, scale, and constraints, and I will produce a production-grade reactive backend design.

Frequently Asked Questions about real-time-backend

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a reactive backend that automatically syncs real-time data across web and mobile clients?▼

To build a reactive backend, define a schema-first data model and use deterministic server functions to mediate data access. This approach enables live data updates and automatic synchronization across web and mobile clients by default.

How do I ensure end-to-end type safety when designing server functions for data modeling?▼

Schema-first backend design enforces end-to-end type safety by generating types directly from your data definitions. It ensures predictable error handling and centralized validation, replacing brittle ad-hoc architectures with strong contracts.

What is the best way to implement server-mediated data access for centralized authentication and business rules?▼

The best way to implement server-mediated data access is through deterministic server functions that centralize auth, validation, and business rules. This ensures all data access is mediated by the server, providing end-to-end transactional guarantees.

Can I use this reactive backend approach for scheduled jobs and server logic without high operational overhead?▼

This approach handles scheduled jobs and server logic by using deterministic server functions within a reactive, type-safe backend. It manages background tasks and server operations predictably without minimal operational overhead.

Does schema-first backend design work for replacing ad-hoc backend architectures at production scale?▼

Schema-first backend design works for production scale by enforcing strong contracts, live data semantics, and maintainable server logic. It replaces brittle ad-hoc architectures with predictable error handling and end-to-end transactional guarantees.

Why should I avoid ad-hoc backend architectures when building real-time data synchronization?▼

You should not use ad-hoc backend architectures when you need reactive live data updates, end-to-end type safety, and centralized business rules. Schema-first reactive backends prevent brittle contracts and ensure maintainable server logic instead.