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v1.0.0
GitHub

About this Skill

Ideal for Python-based AI Agents requiring expert-level Django backend development capabilities django-expert is a skill that provides expert guidance for Django backend development with comprehensive coverage of models, views, and Django REST Framework.

Features

Model design with optimal ORM patterns
View implementation using FBV, CBV, and DRF viewsets
Django REST Framework API development
Testing and performance optimization
Implementation of authentication and forms

# Core Topics

emlopezr emlopezr
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
50
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add emlopezr/TrackWatch/django-expert

Agent Capability Analysis

The django-expert MCP Server by emlopezr is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use django-expert, django-expert setup guide, django-expert alternative.

Ideal Agent Persona

Ideal for Python-based AI Agents requiring expert-level Django backend development capabilities

Core Value

Empowers agents to design optimal Django models using ORM patterns, implement scalable views with FBV, CBV, and DRF viewsets, and develop high-performance REST APIs with Django REST Framework, following official Django best practices and modern Python conventions

Capabilities Granted for django-expert MCP Server

Building maintainable Django applications with robust model design
Implementing scalable and secure Django REST Framework APIs
Optimizing Django application performance using official best practices

! Prerequisites & Limits

  • Requires Python and Django installation
  • Limited to Django backend development
  • Follows official Django best practices, which may not be compatible with older Django versions
Project
SKILL.md
8.4 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
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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

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