CQRS Implementation

Comprehensive guide to implementing CQRS (Command Query Responsibility Segregation) patterns.

When to Use This Skill

• Separating read and write concerns
• Scaling reads independently from writes
• Building event-sourced systems
• Optimizing complex query scenarios
• Different read/write data models needed
• High-performance reporting requirements

Core Concepts

1. CQRS Architecture

                    ┌─────────────┐
                    │   Client    │
                    └──────┬──────┘
                           │
              ┌────────────┴────────────┐
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │  Commands   │          │   Queries   │
       │    API      │          │    API      │
       └──────┬──────┘          └──────┬──────┘
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │  Command    │          │   Query     │
       │  Handlers   │          │  Handlers   │
       └──────┬──────┘          └──────┬──────┘
              │                         │
              ▼                         ▼
       ┌─────────────┐          ┌─────────────┐
       │   Write     │─────────►│    Read     │
       │   Model     │  Events  │   Model     │
       └─────────────┘          └─────────────┘

2. Key Components

Templates

Template 1: Command Infrastructure

from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import TypeVar, Generic, Dict, Any, Type
from datetime import datetime
import uuid

# Command base
@dataclass
class Command:
    command_id: str = None
    timestamp: datetime = None

    def __post_init__(self):
        self.command_id = self.command_id or str(uuid.uuid4())
        self.timestamp = self.timestamp or datetime.utcnow()


# Concrete commands
@dataclass
class CreateOrder(Command):
    customer_id: str
    items: list
    shipping_address: dict


@dataclass
class AddOrderItem(Command):
    order_id: str
    product_id: str
    quantity: int
    price: float


@dataclass
class CancelOrder(Command):
    order_id: str
    reason: str


# Command handler base
T = TypeVar('T', bound=Command)

class CommandHandler(ABC, Generic[T]):
    @abstractmethod
    async def handle(self, command: T) -> Any:
        pass


# Command bus
class CommandBus:
    def __init__(self):
        self._handlers: Dict[Type[Command], CommandHandler] = {}

    def register(self, command_type: Type[Command], handler: CommandHandler):
        self._handlers[command_type] = handler

    async def dispatch(self, command: Command) -> Any:
        handler = self._handlers.get(type(command))
        if not handler:
            raise ValueError(f"No handler for {type(command).__name__}")
        return await handler.handle(command)


# Command handler implementation
class CreateOrderHandler(CommandHandler[CreateOrder]):
    def __init__(self, order_repository, event_store):
        self.order_repository = order_repository
        self.event_store = event_store

    async def handle(self, command: CreateOrder) -> str:
        # Validate
        if not command.items:
            raise ValueError("Order must have at least one item")

        # Create aggregate
        order = Order.create(
            customer_id=command.customer_id,
            items=command.items,
            shipping_address=command.shipping_address
        )

        # Persist events
        await self.event_store.append_events(
            stream_id=f"Order-{order.id}",
            stream_type="Order",
            events=order.uncommitted_events
        )

        return order.id

Template 2: Query Infrastructure

from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import TypeVar, Generic, List, Optional

# Query base
@dataclass
class Query:
    pass


# Concrete queries
@dataclass
class GetOrderById(Query):
    order_id: str


@dataclass
class GetCustomerOrders(Query):
    customer_id: str
    status: Optional[str] = None
    page: int = 1
    page_size: int = 20


@dataclass
class SearchOrders(Query):
    query: str
    filters: dict = None
    sort_by: str = "created_at"
    sort_order: str = "desc"


# Query result types
@dataclass
class OrderView:
    order_id: str
    customer_id: str
    status: str
    total_amount: float
    item_count: int
    created_at: datetime
    shipped_at: Optional[datetime] = None


@dataclass
class PaginatedResult(Generic[T])
how to use cqrs-implementation
CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity
How to use cqrs-implementation on Cursor
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1
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add cqrs-implementation
2
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/wshobson/agents --skill cqrs-implementationcopy
The skills CLI fetches cqrs-implementation from GitHub repository wshobson/agents and configures it for Cursor.
3
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│   • Amp
│   • Antigravity
│   • Cline
│   • Codex
│ ●Cursor(selected)
│   • Cursor
│   • Windsurf
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/cqrs-implementation
Reload or restart Cursor to activate cqrs-implementation. Access the skill through slash commands (e.g., /cqrs-implementation) or your agent's skill management interface.
⚠
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?