Generate Kling images from prompts and reference images via SeaCloud CLI.
npx skills add https://github.com/SeaCloudAI/seacloud-cli --skill kling-image-o1
Please help me install this Agent Skill. Skill: kling_image_o1 Source: https://github.com/SeaCloudAI/seacloud-cli/tree/main/skills/image/kling_image_o1 Command: npx skills add https://github.com/SeaCloudAI/seacloud-cli --skill kling-image-o1
Kling image work often requires premium polish across multiple inputs, including prompts and reference images; this skill streamlines high-end generation and precise editing through Kirin Image Omni via SeaCloud CLI.
Invoke kling_image_o1 with your prompt and optional reference images to produce a premium Kling image.
High-intent search queries and answers about installing and using this skill.
To generate Kling images using multiple reference images, you combine text prompts with one or more reference images. This skill leverages the Kirin Image Omni model via the SeaCloud CLI for high-end visual polish and precise control over inputs.
Prompt-based editing for premium image generation allows you to adjust visuals with targeted refinements. It uses the Kirin Image Omni model to apply specific text prompt modifications to existing images or concepts.
Yes, the SeaCloud CLI supports automated image generation pipelines. It enforces safe CLI parameter mapping with dry-run validation, error handling, and deterministic execution to ensure reliable automated workflows.
You can use Kling image generation for concept art and advertising visuals. It applies high-end visual polish and precise control over inputs, making it suitable for creative production scenarios like editorial illustrations.
The limitations of using the Kirin Image Omni model via CLI include the requirement for live model specs and safe CLI parameter mapping. It enforces deterministic execution, meaning strict parameter validation and error handling apply.
CLI command translation requires live JSON for image generation to ensure safe parameter mapping and deterministic execution. It supports command translation from live JSON to maintain accurate model specs during runtime.
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