---
title: Architecture
description: Technical overview of how ComfyUI Skills maps agent input into ComfyUI workflow execution through the CLI, schema layer, and multi-server routing.
permalink: /architecture/
---
Architecture
The architecture is intentionally simple: expose workflows, map a small parameter surface,
queue the job, poll for completion, and download images back to local disk.
How the repository turns agent input into ComfyUI execution.
System Model
pip install comfyui-skill-cli.<server_id>/<workflow_id>/.CLI Commands
Execution Flow
comfyui-skill list to discover enabled workflows.schema.json./prompt, /history/{prompt_id}, and /view.Storage Model
data/
<server_id>/
<workflow_id>/
workflow.json # ComfyUI API-format workflow
schema.json # Parameter mapping for agents
history/ # Execution history records
This structure makes workflows portable and easy to inspect. It also gives the repository a clean namespace for multi-server execution.
Why The Schema Layer Matters
A graph can contain dozens of nodes and many internal fields that should not be exposed directly. The schema layer narrows that surface into a predictable interface with aliases, descriptions, required flags, and types. That is what makes agent calls more reliable and easier to maintain.
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