This skill provides expert-level architecture review capabilities covering all aspects of Python backend systems, from high-level design patterns to specific implementation details.

What This Skill Reviews

System Architecture: Monolithic vs microservices, service boundaries, communication patterns
Database Design: Schema design, scaling strategies, ORM choices, query optimization
API Design: REST/GraphQL/gRPC design, versioning, documentation
Security: Authentication, authorization, encryption, vulnerability prevention
Scalability: Horizontal/vertical scaling, caching, load balancing, async processing
Observability: Logging, metrics, tracing, error tracking
Deployment: Containerization, orchestration, CI/CD, infrastructure as code
Code Organization: Project structure, dependency management, testing strategies
Resilience: Retry patterns, circuit breakers, graceful degradation
Performance: Optimization strategies, profiling, Python-specific considerations

When to Use

Activate this skill when you need to:

Review a backend architecture design document
Get feedback on system design choices
Analyze scalability and performance patterns
Evaluate security architecture
Assess database design decisions
Review API design
Get recommendations for technology stack
Analyze code organization and structure

Resources Included

SKILL.md

The main skill definition with comprehensive review framework and instructions.

architecture-checklist.md

A detailed checklist covering all aspects of backend architecture review. Use this for quick assessments or to ensure nothing is missed during reviews.

common-patterns.md

Code examples and reference implementations for common architectural patterns:

Repository Pattern
Service Layer Pattern
Dependency Injection
Event-Driven Architecture
Circuit Breaker Pattern
CQRS Pattern
Retry Patterns
Background Task Processing
API Versioning
Middleware Patterns
And more...

technology-recommendations.md

Curated recommendations for technology choices including:

Web frameworks (FastAPI, Django, Flask)
Database solutions (PostgreSQL, MongoDB, Redis)
ORMs (SQLAlchemy, Tortoise ORM)
Authentication libraries
Task queues (Celery, RQ, Dramatiq)
Testing frameworks
Observability tools
Recommended stack combinations

Installation

From Marketplace

Add this marketplace to Claude Code:

/plugin marketplace add rknall/Skills

Install the skill:

/plugin install python-architecture-review

Manual Installation

Clone or download this repository
Copy the python-architecture-review directory to ~/.claude/skills/
Restart Claude Code or reload skills

Usage Examples

Example 1: Full Architecture Review

I have a design document for a new SaaS application backend. It will handle:
- 100K users initially, scaling to 1M
- Real-time notifications
- File uploads and processing
- Multi-tenant architecture
- PostgreSQL for main database
- Redis for caching
- FastAPI as the web framework

Can you review this architecture?

Example 2: Specific Area Review

I'm designing the authentication system for my Python backend.
I'm planning to use JWT tokens with refresh tokens, stored in Redis.
Can you review this approach and suggest improvements?

Example 3: Technology Stack Assessment

I'm choosing between Django and FastAPI for a new project that needs:
- Admin interface
- Complex business logic
- High read/write throughput
- Microservices architecture in the future

Which would you recommend?

Example 4: Security Review

Here's my API security setup:
- JWT authentication
- CORS configured for frontend domain
- Rate limiting on all endpoints
- HTTPS only
- Environment variables for secrets

What am I missing from a security perspective?

Review Output

The skill provides structured reviews including:

Executive Summary: High-level assessment and critical concerns
Detailed Findings: Analysis across all review areas with prioritized concerns
Recommendations: Specific, actionable improvements
Technology Assessment: Evaluation of chosen technologies
Security Checklist: Security-specific items to address
Scalability Roadmap: Scaling strategy and timeline
Next Steps: Prioritized action items

Review Areas Covered

The skill evaluates architectures across these dimensions:

System Architecture & Design Patterns
Database Architecture
API Design & Communication
Security Architecture
Scalability & Performance
Observability & Monitoring
Deployment & Infrastructure
Code Organization & Project Structure
Data Flow & State Management
Resilience & Error Handling

Each area includes both general best practices and Python-specific considerations.

Contributing

To improve this skill:

Update the SKILL.md file with new review criteria
Add new patterns to common-patterns.md
Update technology recommendations as new libraries emerge
Expand the checklist with additional items

Version History

1.0.0 (2025-10-18): Initial release
- Comprehensive review framework
- 10+ architectural patterns
- Technology recommendations
- Complete checklist

License

This skill is provided as-is for use with Claude Code.

Support

For issues, questions, or suggestions, please contact the skill maintainer.