Coordinate asynchronous tasks with Upstash Workflow and QStash.
npx skills add https://github.com/mDevsLabs/mAI --skill upstash-workflow-mdevslabs
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
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.
Configure your environment and trigger a sample Upstash workflow with a small batch to observe fan-out and per-item execution
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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.
mabdulraufOrchestrate Upstash workflows with process, paginate, and execute layers.
xkl2013Automates asynchronous workflows in LobeHub using Upstash Workflow and QStash.
alceupassosAutomate asynchronous fan-out and paginated workflows with Upstash Workflow and QStash.
StaysrDesign and orchestrate asynchronous Upstash Workflow pipelines with QStash.
