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django-expert

vintasoftware/django-ai-plugins

Expert Django backend development guidance for models, views, APIs, and performance optimization.

What is django-expert?

This skill provides comprehensive guidance for Django backend development, covering models, views, Django REST Framework, authentication, testing, and performance optimization. Use it when building Django applications, debugging ORM queries, optimizing database performance, or implementing APIs following Django best practices.

  • Design Django models with optimal ORM patterns and relationships
  • Implement views and APIs using function-based views, class-based views, and Django REST Framework viewsets
  • Optimize database queries and resolve N+1 query problems
  • Configure authentication, permissions, and security best practices
  • Write and structure tests for Django applications
  • Debug migrations, ORM issues, and common Django errors

How to install django-expert

npx skills add https://github.com/vintasoftware/django-ai-plugins --skill django-expert
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How to use django-expert

  1. 1.Describe your Django development task (model design, view implementation, query optimization, testing, or deployment)
  2. 2.The skill will analyze the request and reference appropriate Django best practices documentation
  3. 3.Follow the provided code examples and patterns for your specific use case
  4. 4.Implement the solution using the recommended Django conventions and security practices
  5. 5.Test your implementation and validate for performance and security concerns

Use cases

Good for
  • Creating a REST API with Django REST Framework serializers and viewsets
  • Optimizing slow database queries using select_related and prefetch_related
  • Implementing custom user authentication and permission systems
  • Writing comprehensive test suites with fixtures and factories
  • Debugging N+1 query problems and database performance issues
Who it's for
  • Backend developers building Django applications
  • Full-stack developers implementing Django REST APIs
  • DevOps engineers deploying Django to production
  • QA engineers writing Django application tests
  • Technical leads reviewing Django code for best practices

django-expert FAQ

When should I use this skill vs. general coding help?

Use django-expert when working specifically with Django models, views, serializers, ORM queries, authentication, testing, or production deployment. It provides Django-specific best practices and patterns beyond general Python coding guidance.

Does this skill help with Django REST Framework?

Yes. It covers DRF extensively including serializers, viewsets, routers, pagination, filtering, authentication, and permission classes with modern API development patterns.

Can it help optimize slow Django queries?

Yes. It provides guidance on N+1 query problems, select_related/prefetch_related optimization, database indexing, caching strategies, and query profiling techniques.

Does it cover production deployment?

Yes. It includes comprehensive production deployment guidance covering critical settings, HTTPS/SSL configuration, database and cache setup, static file serving, error monitoring, and health checks.

What Django versions does this cover?

The skill follows current Django best practices and conventions. Reference the bundled documentation for version-specific considerations when needed.

Full instructions (SKILL.md)

Source of truth, from vintasoftware/django-ai-plugins.


name: django-expert description: Expert Django backend development guidance. Use when creating Django models, views, serializers, or APIs; debugging ORM queries or migrations; optimizing database performance; implementing authentication; writing tests; or working with Django REST Framework. Follows Django best practices and modern patterns.

Django Expert

Overview

This skill provides expert guidance for Django backend development with comprehensive coverage of models, views, Django REST Framework, forms, authentication, testing, and performance optimization. It follows official Django best practices and modern Python conventions to help you build robust, maintainable applications.

Key Capabilities:

  • Model design with optimal ORM patterns
  • View implementation (FBV, CBV, DRF viewsets)
  • Django REST Framework API development
  • Query optimization and performance tuning
  • Authentication and permissions
  • Testing strategies and patterns
  • Security best practices

When to Use

Invoke this skill when you encounter these triggers:

Model & Database Work:

  • "Create a Django model for..."
  • "Optimize this queryset/database query"
  • "Generate migrations for..."
  • "Design database schema for..."
  • "Fix N+1 query problem"

View & API Development:

  • "Create an API endpoint for..."
  • "Build a Django view that..."
  • "Implement DRF serializer/viewset"
  • "Add filtering/pagination to API"

Authentication & Security:

  • "Implement authentication/permissions"
  • "Create custom user model"
  • "Secure this endpoint/view"

Testing & Quality:

  • "Write tests for this Django app"
  • "Debug this Django error/issue"
  • "Review Django code for issues"

Performance & Optimization:

  • "This Django view is slow"
  • "Optimize database queries"
  • "Add caching to..."

Production Deployment:

  • "Deploy Django to production"
  • "Configure Django for production"
  • "Set up HTTPS/SSL for Django"
  • "Production settings checklist"
  • "Configure production database/cache"

Instructions

Follow this workflow when handling Django development requests:

1. Analyze the Request and Gather Context

Identify the task type:

  • Model design (database schema, relationships, migrations)
  • View/API development (FBV, CBV, DRF viewsets, serializers)
  • Query optimization (N+1 problems, database performance)
  • Authentication/permissions (user models, access control)
  • Testing (unit tests, integration tests, fixtures)
  • Security review (CSRF, XSS, SQL injection, permissions)
  • Production deployment (settings, HTTPS, database, caching, monitoring)
  • Template rendering (Django templates, context processors)

Leverage available context:

  • If django-ai-boost MCP server is available, use it to understand project structure and existing patterns
  • Read relevant existing code to understand conventions
  • Check Django version for compatibility considerations

2. Load Relevant Reference Documentation

Based on the task type, reference the appropriate bundled documentation:

  • Models/ORM work -> references/models-and-orm.md

    • Model design patterns and field choices
    • Relationship configurations (ForeignKey, ManyToMany)
    • Custom managers and QuerySet methods
    • Migration strategies
  • View/API development -> references/views-and-urls.md + references/drf-guidelines.md

    • FBV vs CBV decision criteria
    • DRF serializers, viewsets, and routers
    • URL configuration patterns
    • Middleware and request/response handling
  • Performance issues -> references/performance-optimization.md

    • Query optimization techniques (select_related, prefetch_related)
    • Caching strategies (Redis, Memcached, database caching)
    • Database indexing and query profiling
    • Connection pooling and async patterns
  • Production deployment -> references/production-deployment.md

    • Critical settings (DEBUG, SECRET_KEY, ALLOWED_HOSTS)
    • HTTPS and SSL/TLS configuration
    • Database and cache configuration
    • Static/media file serving
    • Error monitoring and logging
    • Deployment process and health checks
  • Security concerns -> references/security-checklist.md

    • CSRF/XSS/SQL injection prevention
    • Authentication and authorization patterns
    • Secure configuration practices
    • Input validation and sanitization
  • Testing tasks -> references/testing-strategies.md

    • Test structure and organization
    • Fixtures and factories
    • Mocking external dependencies
    • Coverage and CI/CD integration

3. Implement Following Django Best Practices

Code quality standards:

  • Follow PEP 8 and Django coding style
  • Use Django built-ins over third-party packages when possible
  • Keep views thin, use services/managers for business logic
  • Write descriptive variable names and add docstrings for complex logic
  • Handle errors gracefully with appropriate exceptions

Django-specific patterns:

  • Use select_related() for FK/OneToOne, prefetch_related() for reverse FK/M2M
  • Leverage class-based views and mixins for code reuse
  • Use Django forms/serializers for validation
  • Follow Django's migration workflow (never edit applied migrations)
  • Use Django's built-in security features (CSRF tokens, auth decorators)

API development (DRF):

  • Use ModelSerializer for standard CRUD operations
  • Implement proper pagination and filtering
  • Use appropriate permission classes
  • Follow RESTful conventions for endpoints
  • Version APIs when making breaking changes

4. Validate and Test

Before presenting the solution:

Code review:

  • Check for N+1 query problems (use Django Debug Toolbar mentally)
  • Verify proper error handling and edge cases
  • Ensure security best practices are followed
  • Confirm migrations are clean and reversible

Testing considerations:

  • Suggest or write appropriate tests for new functionality
  • Verify test coverage for critical paths
  • Check that fixtures/factories are maintainable

Performance check:

  • Review database queries for efficiency
  • Consider caching opportunities
  • Verify proper use of database indexes

Bundled Resources

references/ - Comprehensive Django documentation loaded into context as needed

These reference files provide detailed guidance beyond this SKILL.md overview:

  • references/models-and-orm.md (~11k words)

    • Model field types and best practices
    • Relationship configurations (ForeignKey, OneToOne, ManyToMany)
    • Custom managers and QuerySet methods
    • Migration patterns and common pitfalls
    • Database-level constraints and indexes
  • references/views-and-urls.md (~17k words)

    • Function-based vs class-based view trade-offs
    • CBV mixins and inheritance patterns
    • URL routing and reverse resolution
    • Middleware implementation
    • Request/response lifecycle
  • references/drf-guidelines.md (~18k words)

    • Serializer patterns (ModelSerializer, nested serializers)
    • ViewSet and router configurations
    • Pagination, filtering, and search
    • Authentication and permission classes
    • API versioning strategies
    • Performance optimization for APIs
  • references/testing-strategies.md (~18k words)

    • Test organization and structure
    • Factory patterns vs fixtures
    • Testing views, models, and serializers
    • Mocking external services
    • Test database optimization
    • CI/CD integration
  • references/security-checklist.md (~12k words)

    • CSRF protection implementation
    • XSS prevention techniques
    • SQL injection defense
    • Authentication best practices
    • Permission and authorization patterns
    • Secure settings configuration
  • references/performance-optimization.md (~14k words)

    • Query optimization (select_related, prefetch_related, only, defer)
    • Database indexing strategies
    • Caching layers (Redis, Memcached, database cache)
    • Database connection pooling
    • Profiling and monitoring tools
    • Async views and background tasks
  • references/production-deployment.md (~20k words)

    • Critical settings (DEBUG, SECRET_KEY, ALLOWED_HOSTS)
    • Database configuration and connection pooling
    • HTTPS/SSL configuration and security headers
    • Static and media file serving
    • Caching with Redis/Memcached
    • Email configuration for production
    • Error monitoring with Sentry
    • Logging and health checks
    • Zero-downtime deployment strategies
  • references/examples.md - Practical implementation examples

    • Model design with custom managers
    • N+1 query optimization
    • DRF API endpoint implementation
    • Writing Django tests

Additional Notes

Django Version Compatibility:

  • Consider LTS releases (4.2, 5.2) for production
  • Check deprecation warnings when upgrading
  • Use django-upgrade tool for automated migration

Common Pitfalls to Avoid:

  • Circular imports (use lazy references)
  • Missing related_name on relationships
  • Forgetting database indexes on frequently queried fields
  • Using get() without exception handling
  • N+1 queries in templates and serializers