Skills cqrs-implementation
📦

cqrs-implementation

Safe 🌐 Network access⚙️ External commands

Implement CQRS Architecture Patterns

Build scalable applications with Command Query Responsibility Segregation. Separate read and write operations for optimal performance and maintainability.

Supports: Claude Codex Code(CC)
📊 69 Adequate
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Test it

Using "cqrs-implementation". Generate a CQRS implementation for inventory management

Expected outcome:

  • Command handlers for stock adjustments, receipts, and transfers
  • Query handlers for inventory levels, locations, and history
  • Event sourcing for audit trail and stock movement tracking
  • FastAPI endpoints with proper HTTP method mapping
  • Read model optimization for real-time inventory queries
  • Eventual consistency handling for multi-warehouse scenarios

Security Audit

Safe
v4 • 1/17/2026

Pure documentation skill containing Python code examples for CQRS architecture patterns. All 38 static findings are false positives: cryptographic flags triggered by words like 'segregation' and 'separation'; system reconnaissance flags from architectural terms like 'Command' and 'Query'; external_commands flags from markdown backticks; and network flags from legitimate documentation URLs. The skill-report.json already contains a previous audit rating this 'safe'.

2
Files scanned
729
Lines analyzed
2
findings
4
Total audits

Risk Factors

🌐 Network access (4)
skill-report.json:6 SKILL.md:283 SKILL.md:551 SKILL.md:552
⚙️ External commands (11)
SKILL.md:23-47 SKILL.md:47-64 SKILL.md:64-154 SKILL.md:154-158 SKILL.md:158-301 SKILL.md:301-305 SKILL.md:305-419 SKILL.md:419-423 SKILL.md:423-484 SKILL.md:484-488 SKILL.md:488-532
Audited by: claude View Audit History →

Quality Score

38
Architecture
100
Maintainability
83
Content
21
Community
100
Security
87
Spec Compliance

What You Can Build

Build scalable order management

Implement CQRS to handle high-volume order processing with separate read/write models for inventory and reporting.

Design event-sourced microservices

Create event-driven architectures with proper command/query separation and eventual consistency.

Optimize database query performance

Separate read and write databases to scale queries independently and optimize for specific use cases.

Try These Prompts

Basic CQRS Setup 
Generate a CQRS implementation for a user registration system with CreateUserCommand and GetUserQuery handlers
Event Sourcing Integration 
Show me how to implement event sourcing with CQRS for an e-commerce order system using Python
FastAPI CQRS Endpoints 
Create FastAPI endpoints that use CQRS pattern for a blog post system with separate read/write operations
Read Model Synchronization 
Implement a read model synchronizer that updates query models from events with proper error handling

Best Practices

  • Separate command and query models completely to avoid mixing read/write logic
  • Use eventual consistency with defined SLAs for read model updates
  • Version events properly to handle schema evolution over time

Avoid

  • Querying within command handlers breaks separation of concerns
  • Sharing databases between read and write models creates coupling
  • Ignoring consistency requirements leads to stale data issues

Frequently Asked Questions

Which frameworks work with these CQRS examples?
Examples use Python with FastAPI, but patterns apply to any language or framework like Node.js, C#, or Java.
When should I avoid using CQRS?
Avoid CQRS for simple CRUD applications where read/write models are identical and performance is not critical.
How do I integrate with existing databases?
Use the read model synchronizer pattern to build query-optimized views from your existing write database.
Is event sourcing required for CQRS?
No, CQRS works without event sourcing, but combining them provides better audit trails and temporal queries.
How do I handle read-your-writes consistency?
Use the consistent query handler pattern with version checking to ensure users see their updates immediately.
What is the performance impact of CQRS?
Initial complexity adds overhead, but enables independent scaling of reads and writes for better performance at scale.

Developer Details

Author

wshobson

License

MIT

Repository

https://github.com/wshobson/agents/tree/main/plugins/backend-development/skills/cqrs-implementation

Ref

main

File structure

📄 SKILL.md