kling_v1_6_t2v

Name: kling_v1_6_t2v
Availability: InStock
Author: SeaCloudAI

Generate Kling text-to-video outputs from prompts via SeaCloud CLI.

1|Updated Apr 11, 2026

Search Tags:#cli #video #text-to-video #t2v #kling #seacloud #motion-stability

Ready to run

npx skills add https://github.com/SeaCloudAI/seacloud-cli --skill kling-v1-6-t2v

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kling_v1_6_t2v
Source: https://github.com/SeaCloudAI/seacloud-cli/tree/main/skills/video/kling_v1_6_t2v
Command: npx skills add https://github.com/SeaCloudAI/seacloud-cli --skill kling-v1-6-t2v

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Kling video generation from text prompts without sourcing an image, enabling fast, baseline Kling videos for rapid creative exploration.

Core Features & Use Cases

Prompt-only Kling V1.6 video generation for text-to-video workflows.
Motion-stability improvements compared to earlier Kling baselines for smoother clips.
Fast baseline vs high-end variants suitable for quick iterations and scaffolding.

Quick Start

Prompt the Kling v1.6 model via SeaCloud CLI to generate a baseline Kling video from a descriptive prompt.

Frequently Asked Questions about kling_v1_6_t2v

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

FAQPage Schema

How do I generate a Kling video from a text prompt without an image?▼

You can generate a Kling video from a text prompt without an image by using the SeaCloud CLI to run the kirin_v1_6_t2v spec, which creates source-image-free video clips directly from descriptive text.

What is the best way to quickly create baseline videos for concept validation?▼

The best way to create baseline videos for concept validation is prompt-only Kling v1.6 text-to-video generation, which enables rapid creative iteration and lightweight content scaffolding without sourcing images.

Does the Kling v1.6 text-to-video model support camera control and watermark settings?▼

Yes, the Kling v1.6 text-to-video model supports camera control and watermark settings through structured JSON fields like camera_control and watermark_info when executing SeaCloud CLI commands.

How does motion stability in Kling v1.6 compare to earlier text-to-video baselines?▼

Motion stability in Kling v1.6 provides smoother clip generation compared to earlier baselines, making it suitable for fast text-to-video workflows requiring stable motion during creative exploration.

Can I use multiple prompts for a single text-to-video generation task in Kling?▼

Yes, you can use multiple prompts for a single text-to-video generation task in Kling by passing the multi_prompt parameter within the structured JSON payload via the SeaCloud CLI.

When should I not use the fast baseline Kling v1.6 text-to-video generation?▼

You should not use the fast baseline Kling v1.6 generation when your creative workflow requires high-end video variants or source-image-based outputs, as this tool is designed for quick iterations and lightweight content scaffolding.