django-expert

jeffallan/claude-skills · updated May 26, 2026

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$npx skills add https://github.com/jeffallan/claude-skills --skill django-expert
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summary

Expert Django and DRF implementation with ORM optimization, serializers, viewsets, and JWT authentication.

  • Designs Django models with proper indexes, relationships, and managers; handles migrations and schema verification
  • Optimizes ORM queries using select_related and prefetch_related to prevent N+1 problems
  • Builds DRF serializers with validation, viewsets with permissions, and async views for Django 5.0
  • Configures JWT authentication, role-based permissions, and Django admin custo
skill.md

Django Expert

Senior Django specialist with deep expertise in Django 5.0, Django REST Framework, and production-grade web applications.

When to Use This Skill

  • Building Django web applications or REST APIs
  • Designing Django models with proper relationships
  • Implementing DRF serializers and viewsets
  • Optimizing Django ORM queries
  • Setting up authentication (JWT, session)
  • Django admin customization

Core Workflow

  1. Analyze requirements — Identify models, relationships, API endpoints
  2. Design models — Create models with proper fields, indexes, managers → run manage.py makemigrations and manage.py migrate; verify schema before proceeding
  3. Implement views — DRF viewsets or Django 5.0 async views
  4. Validate endpoints — Confirm each endpoint returns expected status codes with a quick APITestCase or curl check before adding auth
  5. Add auth — Permissions, JWT authentication
  6. Test — Django TestCase, APITestCase

Reference Guide

Load detailed guidance based on context:

Topic Reference Load When
Models references/models-orm.md Creating models, ORM queries, optimization
Serializers references/drf-serializers.md DRF serializers, validation
ViewSets references/viewsets-views.md Views, viewsets, async views
Authentication references/authentication.md JWT, permissions, SimpleJWT
Testing references/testing-django.md APITestCase, fixtures, factories

Minimal Working Example

The snippet below demonstrates the core MUST DO constraints: indexed fields, select_related, serializer validation, and endpoint permissions.

# models.py
from django.db import models

class Article(models.Model):
    title = models.CharField(max_length=255, db_index=True)
    author = models.ForeignKey(
        "auth.User", on_delete=models.CASCADE, related_name="articles"
    )
    published_at = models.DateTimeField(auto_now_add=True, db_index=True)

    class Meta:
        ordering = ["-published_at"]
        indexes = [models.Index(fields=["author", "published_at"])]

    def __str__(self):
        return self.title


# serializers.py
from rest_framework import serializers
from .models import Article

class ArticleSerializer(serializers.ModelSerializer):
    author_username = serializers.CharField(source="author.username", read_only=True)

    class Meta:
        model = Article
        fields = ["id", "title", "author_username", "published_at"]

    def validate_title(self, value):
        if len(value.strip()) < 3:
            raise serializers.ValidationError("Title must be at least 3 characters.")
        return value.strip()


# views.py
from rest_framework import viewsets, permissions
from .models import Article
from .serializers import ArticleSerializer

class ArticleViewSet(viewsets.ModelViewSet):
    """
    Uses select_related to avoid N+1 on author lookups.
    IsAuthenticatedOrReadOnly: safe methods are public, writes require auth.
    """
    serializer_class = ArticleSerializer
    permission_classes = [permissions.IsAuthenticatedOrReadOnly]

    def get_queryset(self):
        return Article.objects.select_related("author").all()

    def perform_create(self, serializer):
        serializer.save(author=self.request.user)
# tests.py
from rest_framework.test import APITestCase
from rest_framework import status
from django.contrib.auth.models import User

class ArticleAPITest(APITestCase):
    def setUp(self):
        self.user = User.objects.create_user("alice", password="pass")

    def test_list_public(self):
        res = self.client.get("/api/articles/")
        self.assertEqual(res.status_code, status.HTTP_200_OK)

    def test_create_requires_auth(self):
        res = self.client.post("/api/articles/", {"title": "Test"})
        self.assertEqual(res.status_code, status.HTTP_403_FORBIDDEN)

    def test_create_authenticated(self):
        self.client.force_authenticate(self.user)
        res = self.client.post("/api/articles/", {"title": "Hello Django"})
        self.assertEqual(res.status_code, status.HTTP_201_CREATED)

Constraints

MUST DO

  • Use select_related/prefetch_related for related objects
  • Add database indexes for frequently queried fields
  • Use environment variables for secrets
  • Implement proper permissions on all endpoints
  • Write tests for models and API endpoints
  • Use Django's built-in security features (CSRF, etc.)

MUST NOT DO

  • Use raw SQL without parameterization
  • Skip database migrations
  • Store secrets in settings.py
  • Use DEBUG=True in production
  • Trust user input without validation
  • Ignore query optimization

Output Templates

When implementing Django features, provide:

  1. Model definitions with indexes
  2. Serializers with validation
  3. ViewSet or views with permissions
  4. Brief note on query optimization

Knowledge Reference

Django 5.0, DRF, async views, ORM, QuerySet, select_related, prefetch_related, SimpleJWT, django-filter, drf-spectacular, pytest-django

how to use django-expert

How to use django-expert on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add django-expert
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jeffallan/claude-skills --skill django-expert

The skills CLI fetches django-expert from GitHub repository jeffallan/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/django-expert

Reload or restart Cursor to activate django-expert. Access the skill through slash commands (e.g., /django-expert) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.567 reviews
  • Camila Torres· Dec 24, 2024

    django-expert reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chinedu Brown· Dec 24, 2024

    Solid pick for teams standardizing on skills: django-expert is focused, and the summary matches what you get after install.

  • Camila Flores· Dec 20, 2024

    django-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Sakura Bansal· Dec 16, 2024

    Keeps context tight: django-expert is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Luis Mehta· Nov 15, 2024

    Registry listing for django-expert matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Mei Gonzalez· Nov 15, 2024

    django-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Hiroshi Choi· Nov 11, 2024

    Useful defaults in django-expert — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Camila Lopez· Nov 11, 2024

    Solid pick for teams standardizing on skills: django-expert is focused, and the summary matches what you get after install.

  • Mateo Abebe· Nov 7, 2024

    We added django-expert from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Nia Chawla· Oct 26, 2024

    Solid pick for teams standardizing on skills: django-expert is focused, and the summary matches what you get after install.

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