CQRS Implementation
SkillAI & modelsGuides your agent in splitting read and write models to build scalable architectures with event sourcing.
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the CQRS Implementation skill
About this capability
Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
What this skill tells your AI
The instructions your AI receives, as published by rudycity/superagent in .agents/skills/cqrs-implementation/SKILL.md and read by ahel’s review.
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 and detailed worked examples
Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.
Best Practices
Do's
- Separate command and query models - Different needs
- Use eventual consistency - Accept propagation delay
- Validate in command handlers - Before state change
- Denormalize read models - Optimize for queries
- Version your events - For schema evolution
Don'ts
- Don't query in commands - Use only for writes
- Don't couple read/write schemas - Independent evolution
- Don't over-engineer - Start simple
- Don't ignore consistency SLAs - Define acceptable lag
Signals
- GitHub stars
- 21
- Forks
- 3
- Last commit
- Sep 2026
Others that do the same job
Advanced
- Catalog kind
- skill
- Gateway key
cqrs-implementation- Source
- github.com/rudycity/superagent