image-gen

Generate and refine images from text prompts with JSON metadata.

19|1|Updated Mar 26, 2024
One-click install
npx skills add https://github.com/LocalSymmetry/lofn --skill image-gen-localsymmetry
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: image-gen
Source: https://github.com/LocalSymmetry/lofn/tree/main/skills/image-gen
Command: npx skills add https://github.com/LocalSymmetry/lofn --skill image-gen-localsymmetry

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill removes the friction of creating, editing, and refining images across multiple providers, so you can move from a concept to a finished visual asset without stitching together separate tools.

Core Features & Use Cases

  • Prompt-to-image generation with FAL Flux Pro 1.1 Ultra for high-quality compositions, especially portrait-oriented outputs.
  • Image editing and refinement with Gemini nano-banana 2 or Flux Kontext to fix hands, faces, clothing, consistency, and other visual details while preserving style.
  • Workflow automation with a full generation pipeline, fallback behavior, and JSON sidecar metadata for reproducible outputs.
  • Use case: Create a social media poster from a prompt, refine anatomy and details, and export a final image ready to share.

Quick Start

Use the image-gen skill to generate a 9:16 solarpunk garden city image and save it as ./images/garden.png.

Frequently Asked Questions about image-gen

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

FAQPage Schema
How do I generate and refine high-quality images from text prompts?▼

To generate and refine images from text prompts, use a pipeline that supports multi-provider generation, image editing, aspect-ratio control, and JSON metadata output. This enables iterative corrections for visual details like hands and faces while preserving style.

Can I fix anatomy and visual details in generated images without altering the style?▼

Yes, you can fix anatomy, faces, clothing, and consistency in generated images without altering the style. Image editing and refinement models like Gemini nano-banana 2 or Flux Kontext handle these fast corrections while preserving the original composition.

What is the best way to automate a prompt-to-image generation workflow with fallback handling?▼

The best way to automate a prompt-to-image generation workflow is to use a pipeline with built-in fallback behavior and JSON sidecar metadata output. This ensures reproducible outputs and continuous generation even if a primary provider fails.

Does this image generation approach work well for portrait and social media posters?▼

Yes, this approach works well for portrait and social media posters. It applies to portrait-oriented outputs and social media workflows, using FAL Flux Pro 1.1 Ultra for high-quality compositions tailored to specific aspect ratios like 9:16.

What are the limitations of using Flux and Gemini for image editing?▼

Limitations of using Flux and Gemini for image editing include dependency on multi-provider availability and the need for fallback handling. Complex iterative edits may require multiple correction cycles to achieve desired visual consistency and detail accuracy.