A project-based image generation tool for maintaining visual consistency across multiple AI-generated outputs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install image-sprout
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 image-sprout 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 image-sprout?
image-sprout is a robust CLI tool and web interface designed for repeatable image generation within the ecosystem of Openclaw Skills. By utilizing a project-based model, it allows developers and AI agents to define visual style and subject identity through reference images, ensuring that subsequent generations adhere to specific aesthetic and branding constraints.
It bridges the gap between one-off generations and professional, consistent asset production. By turning reusable project context—including reference images, derived guides, and persistent instructions—into repeatable outputs, this tool is essential for any workflow requiring high-fidelity and predictable visual content.
image-sprout Use Cases
- Maintaining brand consistency across multiple marketing assets.
- Generating character iterations for gaming or storytelling with a persistent subject identity.
- Creating UI/UX mockups that adhere to a specific visual style guide.
- Automating image generation workflows within AI agent pipelines using Openclaw Skills.
How image-sprout Works
- Create a project to house specific context and reference assets.
- Add reference images to establish the desired style and subject identity.
- Derive style and subject guides from the provided references using AI analysis models.
- Execute generation commands with custom prompts that inherit the project context.
- Inspect and extract results using structured JSON output for downstream automation.
image-sprout Setup
First, configure your OpenRouter API key to enable the generation engine:
image-sprout config set apiKey <your-openrouter-key>
Next, initialize a project and add your reference images (3 or more recommended):
image-sprout project create my-brand-assets
image-sprout ref add --project my-brand-assets ./ref1.png ./ref2.png ./ref3.png
image-sprout project derive my-brand-assets --target both
You can then generate consistent images using:
image-sprout project generate my-brand-assets --prompt "product in a sunset setting"
image-sprout Data Schema & Taxonomy
The skill organizes data within a dedicated project model. All outputs and metadata are stored in an internal app data directory, accessible via standard Openclaw Skills integration patterns.
| Component | Description |
|---|---|
| Visual Style | Derived constraints representing the aesthetic look and feel. |
| Subject Guide | Derived identity details for the primary subject. |
| Instructions | Persistent text-based constraints (e.g., watermarks, branding). |
| Run History | A structured record of every generation, including local file paths. |
image-sprout Advanced Features
- JSON-first architecture with the --value flag for plucking specific image paths for automated workflows.
- Parallel-safe execution by explicitly passing project identifiers to avoid state collisions.
- Support for custom generation and analysis models via OpenRouter model management.
- Local Web UI for visual review and interactive canvas-based iteration, compatible with Openclaw Skills contexts.
SKILL.md
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