ComfyUI-OpenClaw Skill 🎨✨

A professional, token-saving agent skill for connecting and controlling ComfyUI via API. Designed for high efficiency, automatic asset handling, and seamless integration with OpenClaw.

🏗️ Skill Structure

• Host Address: 192.168.1.38:8190 (Configured in TOOLS.md)
• Workflow Directory: skills/comfyui/workflows/ (Self-contained within the skill folder)
• Output Directory: outputs/comfy/ (Relative to workspace root)
• Core Script: skills/comfyui/comfy_client.py (Handles prompt injection, image uploads, and result polling)

🛠️ Tools (CLI)

Invoke via the exec command: python3 skills/comfyui/comfy_client.py "" [input_image_path/orientation] [orientation]

Parameters:

• template_id:

1. gen_z: Text-to-Image (uses image_z_image_turbo.json) 2. qwen_edit: Image-to-Image / Editing (uses qwen_image_edit_2511.json) - Supports automatic image upload.

• prompt: The description of the image to generate or edits to perform.
• input_image_path: (Optional) Local path for image-to-image tasks.
• orientation: (Optional) Set to portrait (720x1280) or landscape (1280x720). Defaults to portrait.

💡 How to Add New Workflows

You can expand this skill easily:

1. Place your new API-formatted JSON workflow in skills/comfyui/workflows/.
2. Update the WORKFLOW_MAP dictionary in skills/comfyui/comfy_client.py with a new ID and the file path.
3. (Optional) If the workflow uses unique node types, adjust the injection logic in the script's main() function.

🚀 Token-Saving Strategy

• Template Mapping: Never send full workflow JSONs in the chat. Refer to them by template_id.
• Vision-Saving Strategy: To minimize token usage, the agent should prioritize using the file path from metadata instead of analyzing image content via vision capabilities unless explicitly asked to describe or analyze the image.
• Direct Delivery: Deliver images directly to users via messaging plugins (e.g., Telegram) or local file openers (open) to avoid bloating the LLM's context window with base64 data.