A comprehensive suite of CLI tools for high-fidelity AI image generation, referencing, and canvas expansion using the Kling AI API.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install kling-image-generate
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install kling-image-generate using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Kling AI Image Generation?
The Kling AI Image Generation skill is a powerful integration designed for developers and creators who need programmatically controlled, high-quality visual assets. It leverages the Kling AI official API to provide a robust set of features including text-to-image (T2I), image-to-image (I2I), and advanced Omni-model capabilities for multi-image style transfers.
This Openclaw Skills contribution focuses on reliability and transparency, offering progress-tracking scripts and comprehensive task management. By utilizing local environment variables for JWT authentication, it ensures that your API credentials remain secure while providing professional-grade features like 2K resolution support and intelligent image outpainting.
Kling AI Image Generation Use Cases
- Automated generation of marketing assets and character designs using text prompts.
- Maintaining character consistency across multiple images using subject or face referencing.
- Extending existing artwork boundaries with intelligent outpainting (expansion).
- Batch processing image generation tasks with real-time progress monitoring.
- Complex style transfers and multi-image compositions using the Omni-model.
How Kling AI Image Generation Works
- The user provides an English or Chinese text prompt and optional reference images via the CLI scripts.
- The skill signs a JWT token using the KLING_ACCESS_KEY and KLING_SECRET_KEY stored in the local environment.
- A request is dispatched to the Kling AI API (api-beijing.klingai.com) to initiate a generation task.
- The script retrieves a task ID and, if the wait flag is used, polls the status endpoint to monitor progress.
- Once completed, the script returns the high-resolution image URLs and logs the task metadata.
Kling AI Image Generation Setup
First, ensure you have your API credentials from Kling AI. Set up your local environment as follows:
# Configure your API credentials
export KLING_ACCESS_KEY="your_access_key"
export KLING_SECRET_KEY="your_secret_key"
# Run a test generation with the progress script
python3 scripts/generate_image_with_progress.py \
--prompt "A cute cat in Pixar style" \
--model kling-v3 \
--aspect_ratio 1:1 \
--wait
Kling AI Image Generation Data Schema & Taxonomy
The skill interacts with the Kling AI task system. Below are the key data components used during operations:
| Component | Description |
|---|---|
| Model IDs | Supports kling-v3, kling-v2-1, and kling-v1-5 for various quality tiers. |
| Reference Types | subject (retains body/object) or face (retains facial features). |
| Task Metadata | Includes task_id, status (processing/completed), and result URLs. |
| Image Specs | Configurable aspect ratios (1:1, 16:9, etc.) and resolutions (1k, 2k). |
Kling AI Image Generation Advanced Features
- Multi-image Omni support: Apply the style of one image to the subject of another via the kling-v3-omni model.
- Intelligent Outpainting: Automatically calculate expansion ratios or manually specify up/down/left/right padding percentages.
- Progress Tracking: Integrated polling mechanism in generate_image_with_progress.py for real-time terminal feedback.
- Task Management: Built-in utilities for listing historical tasks and querying specific task statuses by ID.
- Fidelity Control: Adjustable image_fidelity parameters to balance creativity versus reference adherence.
SKILL.md
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