Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/engineerwithai/engineerwith-agents/cqrs-implementationnpx skills add EngineerWithAI/engineerwith-agents --skill cqrs-implementationgit clone --depth 1 https://github.com/EngineerWithAI/engineerwith-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/engineerwithai/engineerwith-agents/cqrs-implementation)<a href="https://agentmods.dev/skills/engineerwithai/engineerwith-agents/cqrs-implementation"><img src="https://agentmods.dev/badge/skills/engineerwithai/engineerwith-agents/cqrs-implementation.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00035 | $0.03404 |
| Opus 5 | $0.00017 | $0.01702 |
| Sonnet 5 | $0.00007 | $0.00681 |
| Haiku 4.5 | $0.00003 | $0.00340 |
Grade A, and why
cqrs-implementation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to cqrs-implementation — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 553 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
| Component | Responsibility |
|---|---|
| Command | Intent to change state |
| Command Handler | Validates and executes commands |
| Event | Record of state change |
| Query | Request for data |
| Query Handler | Retrieves data from read model |
| Projector | Updates read model from events |
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 553 lines · 35 tokens per session scan A 3aaa67191633
cqrs-implementation is a skill published in the GitHub repository EngineerWithAI/engineerwith-agents (4 stars, last pushed 7mo ago), licensed MIT. It adds 35 tokens to every session and 3,404 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to cqrs-implementation, differing in 16 lines, and is treated as a copy.
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