HomeSkills › ComfyUI ImageGen (Flux2)
Automation & Workflows

ComfyUI ImageGen (Flux2)

2.7K downloads 0 stars Version 1.5.0 Rank #3908 of 10,000+

What this skill does

Generate images via ComfyUI API (localhost:8188) using Flux2 workflow. Supports structured JSON prompts sent directly as positive prompt parameter, seed/steps customization. Async watcher via sub-agent for low-latency, token-efficient polling (every 5s).

ComfyUI ImageGen (Flux2) is part of the Automation & Workflows category — automation and workflow skills that schedule, trigger, and orchestrate tasks. You can install it on its own or alongside other automation & workflows skills from the OpenClaw catalog.

ComfyUI ImageGen (Flux2) is ranked #3908 by downloads in the OpenClaw skill catalog (2.7K total downloads, 0 stars). It belongs to the Automation & Workflows category alongside 1059 other top-10000 skills.

How to install ComfyUI ImageGen (Flux2)

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

  1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
  2. Open the in-app Skills panel.
  3. Search for comfyui-imagegen and click Install.
  4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add ComfyUI ImageGen (Flux2) with a single command:

openclaw skills add comfyui-imagegen

This pulls comfyui-imagegen from ClawHub and installs it into ~/.openclaw/skills/comfyui-imagegen/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use ComfyUI ImageGen (Flux2)

Once installed, ComfyUI ImageGen (Flux2) activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Turning images into video

ComfyUI ImageGen (Flux2) works with images. Getting from there to something postable is a separate job: ViralMint — an open-source video pipeline — turns stills into motion — pans and transitions, synced captions, and a vertical export for short-form feeds.

It runs as an MCP server, so an OpenClaw agent can drive it from the same chat you already use: ask for a short, and the render comes back finished. See how to connect a video pipeline to your agent.

Manual install (advanced)

If you prefer manual installation:

  1. Click the Download .zip button above to grab comfyui-imagegen-1.5.0.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/comfyui-imagegen/ (create the directory if it does not exist).
  3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install ComfyUI ImageGen (Flux2)?

Install ComfyUI ImageGen (Flux2) in the OpenClaw Easy desktop app by opening the Skills panel, searching for comfyui-imagegen, and clicking Install. From a terminal you can run: openclaw skills add comfyui-imagegen. Either way the skill is placed in ~/.openclaw/skills/comfyui-imagegen/.

Is ComfyUI ImageGen (Flux2) free?

Yes. ComfyUI ImageGen (Flux2) is free and open-source, distributed under the Apache-2.0 license through ClawHub. No account or payment is required to download or run it.

What does ComfyUI ImageGen (Flux2) do?

Generate images via ComfyUI API (localhost:8188) using Flux2 workflow. Supports structured JSON prompts sent directly as positive prompt parameter, seed/steps customization. Async watcher via sub-agent for low-latency, token-efficient polling (every 5s).

Related: more automation & workflows skills

If ComfyUI ImageGen (Flux2) looks useful, you may also want to check out other automation & workflows skills in the OpenClaw catalog:

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Install ComfyUI ImageGen (Flux2) and 10,000+ other OpenClaw skills in one click. Free, open-source, runs locally on macOS & Windows.

Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models