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eachlabs-workflows

Create and execute multi-step AI workflows by chaining EachLabs models.

28|5|Updated Feb 9, 2026
Search Tags:#automation#content generation#api integration#workflows#model orchestration#ai pipeline
One-click install
npx skills add https://github.com/eachlabs/skills --skill eachlabs-workflows
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: eachlabs-workflows
Source: https://github.com/eachlabs/skills/tree/main/skills/eachlabs-workflows
Command: npx skills add https://github.com/eachlabs/skills --skill eachlabs-workflows

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill allows users to chain multiple AI models together to create complex, automated content generation pipelines, eliminating the need for manual step-by-step execution.

Core Features & Use Cases

  • Workflow Creation: Define multi-step processes by combining different AI models.
  • Step Chaining: Reference outputs from previous steps as inputs for subsequent ones.
  • Input Variables: Dynamically pass data into workflows.
  • Use Case: Automatically generate a product image, enhance it with studio lighting, and then create a short promotional video, all within a single, automated workflow.

Quick Start

Use the eachlabs-workflows skill to build a workflow that enhances a product photo and then generates a video from it.

Frequently Asked Questions about eachlabs-workflows

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

FAQPage Schema
How do I build a multi-step AI pipeline for content generation?▼

To build a multi-step AI pipeline, you create a workflow that orchestrates various EachLabs models sequentially. This allows you to chain outputs from one model as inputs for the next, automating complex content generation tasks.

Can I chain multiple AI models together to automate image and video creation?▼

Yes, you can chain AI models to automate image and video creation by referencing outputs from previous workflow steps. For example, you can generate a product image, enhance it, and create a promotional video within a single automated workflow.

What are dynamic inputs and how do they work in AI model orchestration?▼

Dynamic inputs in AI model orchestration allow you to pass variable data into your workflows at runtime. This enables flexible multi-step pipelines where sequential model execution adapts to the specific data provided for each automated run.

Does this workflow automation support asynchronous results and webhooks?▼

Yes, this workflow automation supports webhook notifications for asynchronous results. You can trigger workflows in bulk and receive webhook callbacks once the multi-step AI pipelines finish processing.

How do I manage different versions when orchestrating AI pipelines?▼

When orchestrating AI pipelines, you can manage different versions through built-in version management capabilities. This ensures your multi-step workflows execute consistently using the specified model versions and configurations.

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