wan2.7-image-skill

Automate text-to-image generation, reference-image editing, and multi-image series creation.

4|Updated Mar 6, 2026
One-click install
npx skills add https://github.com/OpenLabor/openlabor --skill wan2-7-image-skill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: wan2.7-image-skill
Source: https://github.com/OpenLabor/openlabor/tree/main/skills/wan2.7-image-skill
Command: npx skills add https://github.com/OpenLabor/openlabor --skill wan2-7-image-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, and includes scripts (resource) and references (resource) components.

## What problem does it solve? Wan2.7 Image Skill enables end-to-end AI image creation and editing workflows by unifying text-to-image generation, image editing from references, and multi-image composition under a single model and pipeline.

## Core Features & Use Cases

  • Generate high-quality images from descriptive prompts (文生图) and create image series (组图生成) for tutorials, storyboards, or campaigns.
  • Edit existing images by applying styles, merging multiple references, or transferring artistic directions onto new inputs.
  • Support asynchronous task execution with final URL delivery and optional local OSS uploads for reference images.

### Quick Start Provide a text prompt and optional reference images to generate or edit images with Wan2.7-Image.

Frequently Asked Questions about wan2.7-image-skill

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate AI images from text prompts?▼

AI image generation from text prompts requires inputting descriptive text into the Wan2.7-image model to automate creation. The skill handles resolution parsing and asynchronous API polling to deliver the final image URL for your creative projects.

Can I edit existing images using AI reference images?▼

Editing existing images using AI reference images is supported by uploading inputs via file_to_oss to the Wan2.7-image model. You can apply styles, merge multiple references, or transfer artistic directions onto new inputs through asynchronous task execution.

How do I create a multi-image series for a storyboard?▼

Creating a multi-image series for storyboards or tutorials uses the Wan2.7-image model to generate related visuals sequentially. You provide text prompts and optional references, and the asynchronous pipeline processes and delivers each final image URL.

Do I need to handle asynchronous task polling for AI image generation?▼

Asynchronous task polling for AI image generation is handled automatically by the skill via API requests. You provide the prompt and optional OSS-uploaded reference images, and the system polls the Wan2.7-image model until task completion to return the final URL.

What is the best way to manage resolution and input images for AI art?▼

Managing resolution and input images for AI art involves using parse_resolution for dimensions and file_to_oss for uploads. The Wan2.7-image pipeline requires these inputs to properly configure the model before executing the asynchronous generation tasks.

Why does AI image editing require uploading reference images to OSS?▼

AI image editing requires uploading reference images to OSS to provide accessible URLs for the Wan2.7-image model API. This enables the asynchronous processing pipeline to fetch and apply your reference styles or compositions during the generation task.