AI Image Generation

---

name: AI Image Generation slug: image-generation version: 1.0.3 homepage: https://clawic.com/skills/image-generation description: Create AI images with GPT Image, Gemini Nano Banana, FLUX, Imagen, and top providers using prompt engineering, style control, and smart editing. changelog: Updated for 2026 with benchmark-backed model selection and clearer guidance for modern image generation stacks. metadata: {"clawdbot":{"emoji":"🎨","requires":{"bins":[],"env.optional":["OPENAI_API_KEY","GEMINI_API_KEY","BFL_API_KEY","GOOGLE_CLOUD_PROJECT","REPLICATE_API_TOKEN","LEONARDO_API_KEY","IDEOGRAM_API_KEY"],"config":["~/image-generation/"]},"os":["linux","darwin","win32"]}}

Setup

On first use, read setup.md.

When to Use

User needs AI-generated visuals, edits, or consistent image sets. Use this skill to pick the right model, write stronger prompts, and avoid outdated model choices.

Architecture

User preferences persist in ~/image-generation/. See memory-template.md for setup.

~/image-generation/
├── memory.md      # Preferred providers, project context, winning recipes
└── history.md     # Optional generation log

Quick Reference

Core Rules

1. Resolve aliases to official model IDs first

Community names shift quickly. Before calling an API, map the nickname to the provider model ID.

2. Pick models by task, not by hype

3. Use benchmark tables as dated snapshots

Benchmarks drift weekly. Use benchmarks-2026.md as a starting point, then recheck current rankings when quality is critical.

4. Draft cheap, finish expensive

Start with 1-4 low-cost drafts, pick one, then upscale or rerender only the winner.

5. Keep a fallback chain

If the preferred model is unavailable, fallback by tier:

1. same provider lower tier, 2) cross-provider equivalent, 3) local/open model.

6. Treat DALL-E as legacy

OpenAI lists DALL-E 2/3 as legacy. Do not use them as default for new projects.

Common Traps

• Using vendor nicknames as model IDs -> API errors and wasted retries
• Assuming "Nano Banana Pro" or "FLUX 2" are universal IDs -> provider mismatch
• Copying old DALL-E prompt habits -> weaker output vs modern GPT/Gemini image models
• Comparing text-to-image and image-editing scores as if they were the same benchmark
• Optimizing every draft at max quality -> cost spikes without quality gain

Security & Privacy

Data that leaves your machine:

• Prompt text
• Reference images when editing or style matching

Data that stays local:

• Provider preferences in ~/image-generation/memory.md
• Optional local history file

This skill does NOT:

• Store API keys
• Upload files outside chosen provider requests
• Persist generated images unless user asks to save them

External Endpoints

No other data is sent externally.

Migration

If upgrading from a previous version, read migration.md before updating local memory structure.

Trust

This skill may send prompts and reference images to third-party AI providers. Only install if you trust those providers with your content.

Related Skills

Install with clawhub install <slug> if user confirms:

• image-edit - Specialized inpainting, outpainting, and mask workflows
• video-generation - Convert image concepts into video pipelines
• colors - Build palettes for visual consistency across assets
• ffmpeg - Post-process image sequences and exports

Feedback

• If useful: clawhub star image-generation
• Stay updated: clawhub sync