What problem does it solve? Running ComfyUI workflows remotely requires manually provisioning GPU infrastructure, uploading models, and polling job status. This Skill automates the entire pipeline: it analyzes your workflow JSON, finds and downloads the required models to a RunPod network volume, submits the workflow to a serverless endpoint, and returns structured JSON with output URLs. ## Core Features & Use Cases - Workflow Analysis & Model Resolution: Scans ComfyUI API-format workflows for model references (checkpoints, LoRAs, VAEs, CLIP encoders), searches HuggingFace and CivitAI for download URLs, and downloads everything to the network volume before submission. - Serverless Execution: Submits workflows with parameter overrides (--override 7.seed=42) and input file mapping (--input 193=photo.jpg), polls with real-time progress, and returns pre-signed S3 output URLs with model hashes. - Infrastructure & Model Management: Sets up RunPod endpoints via comfy-gen init, lists installed models, queries available samplers/schedulers, and cancels or checks job status. - Use Case: A user shares a Wan 2.2 video workflow. The Skill identifies five required models, locates them on HuggingFace, batch-downloads them to the volume, then submits the workflow with a 900-second timeout and returns the video URL. ## Quick Start Ask the agent to analyze your ComfyUI workflow JSON, download any missing models to the RunPod volume, and submit it for generation.