django-celery-expert — Claude Code skill for Django Celery tasks
A skill that gives your AI agent Django Celery guidance: background tasks, retries, periodic jobs, worker monitoring.
npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a claude-codeWhat django-celery-expert does
The skill steers an agent through Celery work in Django: designing background tasks, configuring workers, handling retries and errors, running periodic jobs with Celery Beat, and setting up production monitoring. The agent first classifies the request, then reads the matching file under references/ — Django integration, task design, configuration, error handling, periodic tasks, monitoring, production deployment. Only then does it write code.
Examples ship with it: sending a welcome email after registration via transaction.on_commit, a CSV import that reports progress through update_state, and a chain that validates inventory, charges payment and sends confirmation. Before handing over a solution the agent checks that task arguments are serializable, retried tasks are idempotent, errors carry context in the log, and long-running tasks have timeouts.
It stays out of general Django questions that have nothing to do with Celery, and out of Django Q, Huey or RQ. ML and data pipeline orchestration in Airflow or Prefect is also outside its scope. If your project runs one of those, this skill won't help.
What it helps with
- debug a Celery task that fails without retrying
- set up retries with backoff and timeouts
- move periodic jobs to Celery Beat with crontab
- wire up Flower or Prometheus for worker monitoring
- build a multi-step chain of tasks
Example prompts for the agent
- Set up background email sending after user registration
- Build a Celery chain: validate inventory, charge payment, send confirmation
- How do I schedule a periodic task with Celery Beat every hour?
How to install django-celery-expert
1Skills CLI (Vercel)
npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a claude-code2Manually: put the files in place
~/.claude/skills/django-celery-expert/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/django-celery-expert/
1Skills CLI (Vercel)
npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a codex2Manually: put the files in place
.agents/skills/django-celery-expert/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a cursor2Manually: put the files in place
.cursor/skills/django-celery-expert/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install vintasoftware/django-ai-plugins django-celery-expert2Manually: put the files in place
.github/skills/django-celery-expert/SKILL.md1Skills CLI (Vercel)
npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a gemini-cli2Platform CLI
gemini skills install https://github.com/vintasoftware/django-ai-plugins --path skills/django-celery-expertManually: put the files in place
.devin/skills/django-celery-expert/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about django-celery-expert
How do I install django-celery-expert in Claude?
Run npx skills add vintasoftware/django-ai-plugins --skill django-celery-expert -a claude-code. The skill lands in ~/.claude/skills/django-celery-expert/SKILL.md.
What does django-celery-expert do?
It gives an agent instructions for Django Celery work: task design, worker configuration, retries, periodic tasks with Celery Beat, monitoring. The agent reads the relevant file under references/ for the request category.
What is django-celery-expert not for?
General Django questions without Celery, other task systems like Django Q, Huey or RQ, ML pipeline orchestration in Airflow or Prefect, and frontend or API-only concerns.