async-jobs

Implement asynchronous background job processing with Celery and ARQ.

217|20|Updated Dec 31, 2025
One-click install
npx skills add https://github.com/yonatangross/orchestkit --skill async-jobs
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: async-jobs
Source: https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/async-jobs
Command: npx skills add https://github.com/yonatangross/orchestkit --skill async-jobs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the implementation of robust background job processing, ensuring tasks are executed reliably, retried on failure, and managed efficiently.

Core Features & Use Cases

  • Task Queues: Implement background task processing using Celery or ARQ.
  • Workflows: Orchestrate complex task sequences with chains, groups, and chords.
  • Scheduling: Set up periodic tasks using Celery Beat.
  • Error Handling: Configure retry strategies, dead-letter queues, and idempotency.
  • Use Case: You need to process user-uploaded images asynchronously. This Skill provides patterns for setting up a Celery worker, defining the image processing task with retries, and enqueueing the job from your web application.

Quick Start

Use the async-jobs skill to implement a Celery task with retry and exponential backoff.

Frequently Asked Questions about async-jobs

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up background task processing with Celery for long-running operations?

Background task processing with Celery involves setting up a task queue to execute long-running or I/O-bound operations asynchronously. You define tasks, configure a Celery worker, and enqueue jobs from your application to ensure reliable execution without blocking the main thread.

What is the best way to orchestrate complex task sequences using Celery canvas primitives?

Orchestrating complex task sequences uses Celery canvas primitives like chains, groups, and chords. Chains execute tasks sequentially, groups run tasks in parallel, and chords combine a group with a callback, enabling structured workflow orchestration for distributed task processing.

How do I configure retries and exponential backoff for background jobs?

Configuring retries for background jobs involves defining retry strategies with exponential backoff within your task definition. This ensures failed operations are automatically re-attempted after increasing delays, improving reliability for transient errors in distributed systems.

Can I use ARQ instead of Celery for asynchronous background tasks in Python?

Yes, ARQ is an alternative for asynchronous background tasks. This Skill provides implementation patterns for both ARQ and Celery, allowing you to choose based on your specific requirements for task queue setup, scheduling, and workflow management.

How do I schedule periodic tasks using Celery Beat?

Scheduling periodic tasks uses Celery Beat to execute jobs at regular intervals. You configure the schedule in your application, allowing the system to automatically enqueue and process recurring background tasks without manual intervention.

How do I handle dead-letter queues and idempotency for failed background jobs?

Handling failed background jobs requires dead-letter queues to capture permanently failed tasks and idempotency to prevent duplicate execution. These error handling patterns ensure robust processing and prevent data corruption during task retries.