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kling-omni-image-generation

Generate Kling Omni image tasks and retrieve finished image URLs.

23|4|Updated May 7, 2026
Search Tags:#image generation#image editing#text-to-image#reference images#kling#asynchronous workflow
One-click install
npx skills add https://github.com/qq5855144/GitHubM --skill kling-omni-image-generation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kling-omni-image-generation
Source: https://github.com/qq5855144/GitHubM/tree/main/.skills/kling-omni-image-generation
Command: npx skills add https://github.com/qq5855144/GitHubM --skill kling-omni-image-generation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill removes the manual overhead of producing high-quality images from prompts or reference materials by guiding a complete Kling Omni generation workflow from request submission to finished output retrieval.

Core Features & Use Cases

  • Text-to-Image Generation: Create original visuals from natural-language prompts for concept art, marketing graphics, and social content.
  • Reference-Based Editing: Use one or more input images or subject references to blend, transform, or reimagine existing visuals with more control.
  • Production-Friendly Controls: Choose model, resolution, aspect ratio, single or series output, and handle asynchronous task completion with result polling.
  • Use Case: A designer can submit a poster prompt with a reference image, wait for the task to finish, and then save the returned image URL for immediate review or distribution.

Quick Start

Use the kling-omni-image-generation skill to generate a Kling Omni image from your prompt and any reference images, then wait for the task to complete and download the returned result locally.

Frequently Asked Questions about kling-omni-image-generation

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

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

To generate images from text prompts, submit a natural-language description or reference images to create an asynchronous task, then poll the task status until completion to retrieve the finished image URLs.

Can I use reference images to edit or reimagine existing visuals?▼

Reference images can be used for editing and subject-reference workflows, allowing you to blend, transform, or reimagine existing visuals with more control for creative design and asset production.

What resolutions and aspect ratios are supported for text-to-image generation?▼

Text-to-image generation supports 1k or 2k resolution outputs with aspect-ratio control, offering single or series output options for producing creative design, posters, and web or app assets.

How does asynchronous image generation workflow handle task completion?▼

Asynchronous image generation uses a submit-and-poll execution model where you submit a generation task, wait for processing to finish, and then retrieve the returned image URLs for immediate review or distribution.

Are there validation rules for series output and image payload formats?▼

Series output and image payload formats undergo strict validation, ensuring that series_amount values and reference image lists meet required specifications before the generation task is accepted.

What's the best way to produce marketing graphics and social content?▼

Producing marketing graphics and social content is best handled by submitting poster prompts with reference images, waiting for the asynchronous task to finish, and saving the returned image URL for distribution.

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