Comprehensive pre-deployment verification pipeline for Django projects covering migrations, linting, tests, security, and configuration.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add affaan-m/everything-claude-code --skill django-verificationCompatible with
Supported agents
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondjango-verificationExecute the skills CLI command in your project's root directory to begin installation:
epx add affaan-m/everything-claude-code --skill django-verificationFetches django-verification from affaan-m/everything-claude-code and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/django-verification
Restart Cursor to activate django-verification. Access via /django-verificationin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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django-verification is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
django-verification fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added django-verification from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
django-verification reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in django-verification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
django-verification fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
django-verification is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in django-verification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for django-verification matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in django-verification — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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