# Cqrs

> Apply Command Query Responsibility Segregation to separate read and write models when their needs diverge significantly. Use when read and write performance, scaling, or model complexity requirements are very different.

- Skill: `itsual/cqrs` (Agent Skill)
- Install (CLI): `npx skillmds@latest add itsual/cqrs`
- Raw SKILL.md: https://api.skillmd.com/api/skills/itsual/cqrs/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: itsual (https://skillmd.com/u/itsual)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/itsual/cqrs

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# CQRS

## Overview

CQRS separates the model used for updates from the model used for reads. It is powerful but adds complexity and should be used when the benefits are clear.

## When to Use

- Read and write workloads have very different shapes or scale requirements
- Complex domains where a single model becomes awkward
- Event-sourced systems (often paired with CQRS)

## Key Points

- Commands change state; queries return data without side effects
- Different models (and sometimes different stores) for reads vs writes
- Eventual consistency between write side and read side is common
- Requires clear discipline around where validation and business rules live

## Principles

- Don’t apply CQRS by default — it increases moving parts
- Start with a single model and separate only when pain appears
- Make consistency expectations explicit to clients

## Verification

- Write-side invariants are protected
- Read models are updated reliably (or lag is acceptable and visible)
- Complexity is justified by measurable benefits