django-verification▌
affaan-m/everything-claude-code · updated Apr 8, 2026
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Comprehensive pre-deployment verification pipeline for Django projects covering migrations, linting, tests, security, and configuration.
- ›Runs 12 sequential phases: environment validation, code quality checks (mypy, ruff, black, isort), migration safety, test coverage analysis, security scanning (pip-audit, bandit, gitleaks), and Django-specific configuration verification
- ›Includes coverage targets by component (models 90%+, views 80%+, overall 80%+) and pre-deployment checklist covering
Django Verification Loop
Run before PRs, after major changes, and pre-deploy to ensure Django application quality and security.
When to Activate
- Before opening a pull request for a Django project
- After major model changes, migration updates, or dependency upgrades
- Pre-deployment verification for staging or production
- Running full environment → lint → test → security → deploy readiness pipeline
- Validating migration safety and test coverage
Phase 1: Environment Check
# Verify Python version
python --version # Should match project requirements
# Check virtual environment
which python
pip list --outdated
# Verify environment variables
python -c "import os; import environ; print('DJANGO_SECRET_KEY set' if os.environ.get('DJANGO_SECRET_KEY') else 'MISSING: DJANGO_SECRET_KEY')"
If environment is misconfigured, stop and fix.
Phase 2: Code Quality & Formatting
# Type checking
mypy . --config-file pyproject.toml
# Linting with ruff
ruff check . --fix
# Formatting with black
black . --check
black . # Auto-fix
# Import sorting
isort . --check-only
isort . # Auto-fix
# Django-specific checks
python manage.py check --deploy
Common issues:
- Missing type hints on public functions
- PEP 8 formatting violations
- Unsorted imports
- Debug settings left in production configuration
Phase 3: Migrations
# Check for unapplied migrations
python manage.py showmigrations
# Create missing migrations
python manage.py makemigrations --check
# Dry-run migration application
python manage.py migrate --plan
# Apply migrations (test environment)
python manage.py migrate
# Check for migration conflicts
python manage.py makemigrations --merge # Only if conflicts exist
Report:
- Number of pending migrations
- Any migration conflicts
- Model changes without migrations
Phase 4: Tests + Coverage
# Run all tests with pytest
pytest --cov=apps --cov-report=html --cov-report=term-missing --reuse-db
# Run specific app tests
pytest apps/users/tests/
# Run with markers
pytest -m "not slow" # Skip slow tests
pytest -m integration # Only integration tests
# Coverage report
open htmlcov/index.html
Report:
- Total tests: X passed, Y failed, Z skipped
- Overall coverage: XX%
- Per-app coverage breakdown
Coverage targets:
| Component | Target |
|---|---|
| Models | 90%+ |
| Serializers | 85%+ |
| Views | 80%+ |
| Services | 90%+ |
| Overall | 80%+ |
Phase 5: Security Scan
# Dependency vulnerabilities
pip-audit
safety check --full-report
# Django security checks
python manage.py check --deploy
# Bandit security linter
bandit -r . -f json -o bandit-report.json
# Secret scanning (if gitleaks is installed)
gitleaks detect --source . --verbose
# Environment variable check
python -c "from django.core.exceptions import ImproperlyConfigured; from django.conf import settings; settings.DEBUG"
Report:
- Vulnerable dependencies found
- Security configuration issues
- Hardcoded secrets detected
- DEBUG mode status (should be False in production)
Phase 6: Django Management Commands
# Check for model issues
python manage.py check
# Collect static files
python manage.py collectstatic --noinput --clear
# Create superuser (if needed for tests)
echo "from apps.users.models import User; User.objects.create_superuser('[email protected]', 'admin')" | python manage.py shell
# Database integrity
python manage.py check --database default
# Cache verification (if using Redis)
python -c "from django.core.cache import cache; cache.set('test', 'value', 10); print(cache.get('test'))"
Phase 7: Performance Checks
# Django Debug Toolbar output (check for N+1 queries)
# Run in dev mode with DEBUG=True and access a page
# Look for duplicate queries in SQL panel
# Query count analysis
django-admin debugsqlshell # If django-debug-sqlshell installed
# Check for missing indexes
python manage.py shell << EOF
from django.db import connection
with connection.cursor() as cursor:
cursor.execute("SELECT table_name, index_name FROM information_schema.statistics WHERE table_schema = 'public'")
print(cursor.fetchall())
EOF
Report:
- Number of queries per page (should be < 50 for typical pages)
- Missing database indexes
- Duplicate queries detected
Phase 8: Static Assets
# Check for npm dependencies (if using npm)
npm audit
npm audit fix
# Build static files (if using webpack/vite)
npm run build
# Verify static files
ls -la staticfiles/
python manage.py findstatic css/style.css
Phase 9: Configuration Review
# Run in Python shell to verify settings
python manage.py shell << EOF
from django.conf import settings
import os
# Critical checks
checks = {
'DEBUG is False': not settings.DEBUG,
'SECRET_KEY set': bool(settings.SECRET_KEY and len(settings.SECRET_KEY) > 30),
'ALLOWED_HOSTS set': len(settings.ALLOWED_HOSTS) > 0,
'HTTPS enabled': getattr(settings, 'SECURE_SSL_REDIRECT', False),
'HSTS enabled': getattr(settings, 'SECURE_HSTS_SECONDS', 0) > 0,
'Database configured': settings.DATABASES['default']['ENGINE'] != 'django.db.backends.sqlite3',
}
for check, result in checks.items():
status = '✓' if result else '✗'
print(f"{status} {check}")
EOF
Phase 10: Logging Configuration
# Test logging output
python manage.py shell << EOF
import logging
logger = logging.getLogger('django')
logger.warning('Test warning message')
logger.error('Test error message')
EOF
# Check log files (if configured)
tail -f /var/log/django/django.log
Phase 11: API Documentation (if DRF)
# Generate schema
python manage.py generateschema --format openapi-json > schema.json
# Validate schema
# Check if schema.json is valid JSON
python -c "import json; json.load(open('schema.json'))"
# Access Swagger UI (if using drf-yasg)
# Visit http://localhost:8000/swagger/ in browser
Phase 12: Diff Review
# Show diff statistics
git diff --stat
# Show actual changes
git diff
# Show changed files
git diff --name-only
# Check for common issues
git diff | grep -i "todo\|fixme\|hack\|xxx"
git diff | grep "print(" # Debug statements
git diff | grep "DEBUG = True" # Debug mode
git diff | grep "import pdb" # Debugger
Checklist:
- No debugging statements (print, pdb, breakpoint())
- No TODO/FIXME comments in critical code
- No hardcoded secrets or credentials
- Database migrations included for model changes
- Configuration changes documented
- Error handling present for external calls
- Transaction management where needed
Output Template
DJANGO VERIFICATION REPORT
==========================
Phase 1: Environment Check
✓ Python 3.11.5
✓ Virtual environment active
✓ All environment variables set
Phase 2: Code Quality
✓ mypy: No type errors
✗ ruff: 3 issues found (auto-fixed)
✓ black: No formatting issues
✓ isort: Imports properly sorted
✓ manage.py check: No issues
Phase 3: Migrations
✓ No unapplied migrations
✓ No migration conflicts
✓ All models have migrations
Phase 4: Tests + Coverage
Tests: 247 passed, 0 failed, 5 skipped
Coverage:
Overall: 87%
users: 92%
products: 89%
orders: 85%
payments: 91%
Phase 5: Security Scan
How to use django-verification on Cursor
AI-first code editor with Composer
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-verification
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches django-verification from GitHub repository affaan-m/everything-claude-code and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate django-verification. Access the skill through slash commands (e.g., /django-verification) 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
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★51 reviews- ★★★★★Dhruvi Jain· Dec 20, 2024
django-verification is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Amelia Gonzalez· Dec 20, 2024
django-verification fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Zara Harris· Dec 20, 2024
We added django-verification from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Xiao Iyer· Dec 16, 2024
django-verification reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aditi Agarwal· Dec 16, 2024
Useful defaults in django-verification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Oshnikdeep· Nov 11, 2024
django-verification fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Nia Gill· Nov 11, 2024
django-verification is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diego Patel· Nov 11, 2024
Useful defaults in django-verification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Aanya Haddad· Nov 7, 2024
Registry listing for django-verification matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aanya Farah· Oct 26, 2024
Useful defaults in django-verification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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