upstash-workflow

Coordinate asynchronous tasks with Upstash Workflow and QStash.

1|Updated May 20, 2026

Search Tags:#automation #workflow #asynchronous #pagination #qstash #upstash #fan-out

Ready to run

npx skills add https://github.com/mDevsLabs/mAI --skill upstash-workflow-mdevslabs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: upstash-workflow
Source: https://github.com/mDevsLabs/mAI/tree/main/.agents/skills/upstash-workflow
Command: npx skills add https://github.com/mDevsLabs/mAI --skill upstash-workflow-mdevslabs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides standardized guidance and patterns for implementing Upstash Workflow + QStash-based asynchronous workflows, enabling reliable fan-out, pagination, and single-item execution within distributed systems.

Core Features & Use Cases

Dry-run mode for statistics and safe pre-execution insight
Fan-out pagination to handle large batches efficiently
Layered 3-tier architecture: process, paginate, execute
Idempotent per-item execution with context.run-based orchestration
Reference implementations and best practices for Upstash workflows

Quick Start

Configure your environment and trigger a sample Upstash workflow with a small batch to observe fan-out and per-item execution

Frequently Asked Questions about upstash-workflow

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

FAQPage Schema

How do I build asynchronous workflows with Upstash QStash for batch processing?▼

Asynchronous workflows with Upstash QStash coordinate batched processing through a three-layer pattern: process, paginate, and execute. This architecture enables reliable fan-out across many items using idempotent context.run steps for orchestration.

What is the best way to handle large batch fan-out in Lobehub deployments?▼

Large batch fan-out in Lobehub deployments is handled using pagination within the Upstash Workflow. The pattern separates pagination logic from execution, ensuring items are processed efficiently in parallel without overwhelming the system.

Do I need APP_URL and QSTASH_TOKEN environment variables to run Upstash workflows?▼

Yes, APP_URL and QSTASH_TOKEN environment variables are required to run Upstash workflows. These variables authenticate QStash requests and provide the endpoint URL necessary for asynchronous task coordination and callback execution.

Can I simulate Upstash workflow execution before processing a full batch?▼

Yes, you can simulate Upstash workflow execution using the dry-run mode. This feature provides statistics and safe pre-execution insight, allowing you to observe fan-out behavior and per-item orchestration before processing actual data.

How does idempotent execution work in Upstash Workflow orchestration?▼

Idempotent execution in Upstash Workflow orchestration uses unique context.run steps for each item. This ensures that individual tasks within a fan-out batch can be retried safely without duplicating side effects or processing the same item twice.

When should I use a three-tier process, paginate, and execute architecture for async tasks?▼

A three-tier process, paginate, and execute architecture should be used for async tasks requiring scalable fan-out across large datasets. It separates orchestration, batch handling, and individual item execution to maintain reliability in distributed systems.