zambav/comfyui-agent-toolkit

Run ComfyUI in plain English from your AI agent. Image, video, and LoRA workflows — any install, any model, any agent harness.

Quick start · Worked example · What you can ask · Why it works · Works with any agent · When to use · Repo structure

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Talk to ComfyUI in natural language

Stop hand-editing JSON workflows. Tell your agent what you want, and it builds the workflow, queues the jobs, watches them run, and reports back.

You:    "batch this entire image folder into cinematic portraits and pick good prompts"
Agent:  "Where are the photos? Where should outputs go? What should I call this batch?"
You:    "D:/photos/portraits, D:/photos/portraits/cinematic, 'portraits_v1'"
Agent:  "47 images found. Running FLUX 2 image edit, one prompt, randomized seed."
         [.. 47 jobs queued, each one blocks on completion, each one verified with /history ..]
Agent:  "Done. 47/47 OK. Output: D:/photos/portraits/cinematic/batch_01/"

No JSON editing. No fire-and-forget queueing. No silent failures. Just: describe it, run it, get the files.

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Quick start

# 1. Drop the skill into your agent's environment
git clone https://github.com/Zambav/comfyui-skill-public.git
cd comfyui-skill-public

# 2. Read the right entry point
#    - AI agent       -> AGENTS.md
#    - Human operator -> SKILL.md

# 3. (Optional) Copy the production helper into your project
cp scripts/api_lib.py /path/to/your/project/

# 4. Install runtime dependencies