ComfyUI工作流生成器。从自然语言描述生成ComfyUI工作流。基于ComfyGPT研究架构，经历生成→验证→构建三阶段管道。触发词：ComfyUI工作流、生成工作流、ComfyUI自动化。

This implementation appears to do what it claims, but take these precautions before installing: 1) Review requirements.txt and install the node in an isolated Python environment or container since it depends on torch, sentence-transformers, llama-cpp-python (which may require native compilation). 2) The "Update Node Catalog" step scans your local ComfyUI installation and writes catalog/TinyDB files — that's expected but means the node reads local ComfyUI modules and metadata. 3) Models are expected to be local (GGUF or HuggingFace); check whether you will download models from HuggingFace or provide them locally — automatic downloads can occur only if you run the provided loader code and have network access. 4) If you are unsure, run the node in a disposable VM/container and inspect the created files (catalog/, ComfyUI/models/LLM/) and network activity during initial runs. 5) If you need deeper assurance, review utils/model_loaders/huggingface_loader.py and any code that fetches remote models to confirm there are no unexpected remote endpoints or credentials used.

Type: OpenClaw Skill Name: comfyui-workflow-generator Version: 1.0.0 The skill bundle is a legitimate implementation of the ComfyGPT research architecture for generating ComfyUI workflows from natural language. It utilizes local LLMs (via llama-cpp-python or transformers) and semantic embeddings to generate, validate, and build workflow JSON files. The code includes a cataloging system to scan locally installed nodes and a layout engine for positioning. File operations are restricted to reading models and writing generated workflows to the standard ComfyUI output directory. No malicious indicators such as data exfiltration, obfuscation, or unauthorized remote execution were detected.