baoyu-imagine

Orchestrate multi-provider AI image generation from prompts and assets.

Updated Feb 6, 2026

Search Tags:#image generation #CLI #batch processing #multi-provider #prompt #reference images

Ready to run

npx skills add https://github.com/glfruit/gorin-skills --skill baoyu-imagine-glfruit

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: baoyu-imagine
Source: https://github.com/glfruit/gorin-skills/tree/main/openclaw/baoyu-imagine
Command: npx skills add https://github.com/glfruit/gorin-skills --skill baoyu-imagine-glfruit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Orchestrates image generation across multiple AI providers from a single prompt, enabling cross-provider workflows.

Core Features & Use Cases

Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream, and Replicate for versatile image generation.
Handles prompts, optional reference images, aspect ratios, batch prompts, and per-image settings, with sensible defaults and robust error handling.
Real-world use: teams comparing styles and costs across providers before selecting a final output.

Quick Start

Provide a prompt and optional references to generate an image.

Frequently Asked Questions about baoyu-imagine

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

FAQPage Schema

How do I generate AI images across multiple providers from a single prompt?▼

To generate images across multiple providers, you can use a unified CLI tool that orchestrates prompt-driven generation. This allows you to compare styles and costs across platforms like OpenAI, Google, and Replicate before selecting a final output.

Can I use reference images and batch prompts for AI image generation?▼

Yes, batch processing and reference images are supported for AI image generation. The system handles optional reference images, aspect ratios, batch prompts, and per-image settings, enforcing sensible defaults to ensure consistent workflows.

What multi-provider AI image generation platforms are supported for cross-provider workflows?▼

Supported platforms for multi-provider AI image generation include OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream, and Replicate. This enables versatile cross-provider workflows from a single interface.

How does the system handle model resolution and credential checks during image generation?▼

The system enforces model resolution and credential checks during image generation to ensure consistent workflows. It includes robust error handling and EXTEND.md-driven defaults to manage per-image settings and prevent generation failures.

Is there a way to compare styles and costs across AI image providers before finalizing an output?▼

Comparing styles and costs across AI image providers is achieved through multi-provider orchestration. Teams can generate images from a single prompt across different platforms simultaneously to evaluate results before committing to a final output.

Do I need specific dependencies to run multi-provider image generation scripts?▼

No specific external dependencies are required to run the multi-provider image generation scripts. The system operates independently using internal scripts to manage prompt-driven generation, credential checks, and batch controls across providers.