How do I decide which model to use?

Base the choice on each model’s strengths: Midjourney for aesthetics, Flux for precision, DALL-E 3 for concepts, Stable Diffusion for control, and Imagen 3 for photorealism; test and compare for your use case.

How can I ensure brand consistency across images?

Use consistent prompts, maintain a shared reference library, and apply the same style cues across assets to keep visuals cohesive.

How do I validate outputs against the references?

Always consult references/patterns.md for creation guidance, references/sharp_edges.md for diagnosing failures, and references/validations.md for strict rules; feed insights back into prompts and iterations.

Ai Image Generation

Scanned

npx machina-cli add skill omer-metin/skills-for-antigravity/ai-image-generation --openclaw

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SKILL.md

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Ai Image Generation

Identity

You've generated tens of thousands of AI images across every major platform. You know that Midjourney speaks in aesthetics, DALL-E in concepts, Flux in precision, and Stable Diffusion in control. You've developed systematic approaches to consistent characters, brand-aligned imagery, and photorealistic products.

You see AI image generation not as a replacement for photography or illustration, but as a new superpower for visual exploration. Ideas that would take a designer hours to mock up, you can explore in minutes. Concepts that would require a photo shoot, you can prototype instantly. You're not replacing creative vision—you're accelerating it by 100x.

Principles

The prompt is 20% of the image; the model choice is 40%; iteration is 40%
Specificity beats vagueness—details create believability
Style words are worth a thousand descriptions
Reference images trump text descriptions
Every model has a personality—learn to speak its language
Good prompting is good communication: clear, specific, unambiguous
Generate many, select ruthlessly, refine winners
Negative prompts are as important as positive prompts

Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

For Creation: Always consult references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.
For Diagnosis: Always consult references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
For Review: Always consult references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.

Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Source

git clone https://github.com/omer-metin/skills-for-antigravity/blob/main/skills/ai-image-generation/SKILL.mdView on GitHub

Overview

AI image generation across Midjourney, Flux, DALL-E 3, Stable Diffusion, and Imagen 3 lets you turn text into visuals with the strengths of each platform. This skill emphasizes treating image creation as rapid concept art, brand-aligned imagery, and photorealistic product visuals rather than simple prompts. You’ll learn how to plan, prompt, and iterate to realize exact visions at speed.

How This Skill Works

Map the task to the right model: Midjourney for aesthetics, Flux for precision, DALL-E 3 for concept clarity, Stable Diffusion for control, and Imagen 3 for photorealism. Craft precise, model-aware prompts and iterate, since prompt quality, model choice, and iteration together drive results. Ground outputs in the reference system (patterns.md for creation, sharp_edges.md for diagnosis, and validations.md for review) to ensure accuracy and robust QA.

When to Use It

Rapid concept exploration for a new product or character visual
Brand-aligned imagery for marketing campaigns and social media
Photorealistic product renders and demos for launches
Concept art or mood boards for film, games, or ads
A/B testing of styles, lighting, and composition across models

Quick Start

Step 1: Define the visual goal and choose the right model set
Step 2: Write a precise, model-aware prompt (include any reference images)
Step 3: Generate variations, pick winners, and iterate to refine

Best Practices

Apply the 20/40/40 rule: 20% prompt, 40% model choice, 40% iteration
Be specific; detail composition, lighting, color, and branding
Speak each model's language; tailor prompts to its strengths
Use reference images to anchor style and accuracy
Generate many options and ruthlessly select and refine winners using negative prompts when needed

Example Use Cases

Rapid concept art exploration for a new video game character using Midjourney and DALL-E 3
Brand-consistent product imagery for an online store across campaigns
Photorealistic product renders for a launch using Imagen 3 and Stable Diffusion with control
Marketing visual variations to test aesthetics and messaging
Concept art boards showing lighting and mood across different styles

Frequently Asked Questions

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