Ai Image GeneratorSAFE

Skills for Claude Code CLI such as full stack dev Cloudflare, React, Tailwind v4, and AI integrations.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: ai-image-generator
description: "Generate AI images using Gemini or GPT APIs directly. Covers model selection (Gemini for scenes; GPT Image 2 for text rendering, batch variations, multi-reference compositing; GPT Image 1.5 for transparent icons), the 5-part prompting framework, API calling patterns, multi-turn editing, and quality assurance. Produces photorealistic scenes, icons, illustrations, OG images, posters, infographics, and product shots. Use when building websites that need images, creating marketing assets, or generating visual content. Triggers: 'generate image', 'ai image', 'create hero image', 'make an icon', 'generate illustration', 'create og image', 'poster', 'infographic', 'image variations', 'gpt-image-2', 'ai art', 'image generation'."
allowed-tools:
  - Read
  - Write
  - Bash
  - Glob
  - Grep
compatibility: claude-code-only
---

# AI Image Generator

Generate images using AI APIs (Google Gemini and OpenAI GPT). This skill teaches the prompting patterns and API mechanics for producing professional images directly from Claude Code.

> **Managed alternative**: If you don't want to manage API keys, [ImageBot](https://imagebot.au) provides a managed image generation service with album templates and brand kit support.

## Model Selection

Choose the right model for the job:

| Need | Model | Why |
|------|-------|-----|
| **Photorealistic scenes / stock photos** | Gemini 3.1 Flash Image | Best depth, complexity, environmental context |
| **Final client scenes (higher detail)** | Gemini 3 Pro Image | Higher detail, better style consistency |
| **Text on images** (posters, OG with copy, infographics) | GPT Image 2 | Text rendering actually works — including multi-script |
| **10-variation style exploration** | GPT Image 2 | Native batch — one prompt, 10 variants sharing composition + palette |
| **Multi-reference compositing** (product + lifestyle) | GPT Image 2 | Handles lighting, scale, perspective across references |
| **Transparent icons / logos** | GPT Image 1.5 | Native RGBA alpha — **GPT Image 2 cannot do transparency** |
| **Quick drafts / iteration** | Gemini 2.5 Flash Image | Free tier (~500/day) |

**Rule of thumb**: any image with readable text → GPT Image 2 (unless you need transparency, then GPT 1.5). Otherwise → Gemini.

### Model IDs

| Model | API ID | Provider |
|-------|--------|----------|
| Gemini 3.1 Flash Image | `gemini-3.1-flash-image-preview` | Google AI |
| Gemini 3 Pro Image | `gemini-3-pro-image-preview` | Google AI |
| Gemini 2.5 Flash Image | `gemini-2.5-flash-image` | Google AI |
| GPT Image 2 (default) | `gpt-image-2` | OpenAI |
| GPT Image 2 (ChatGPT-parity output) | `chatgpt-image-latest` | OpenAI |
| GPT Image 1.5 (transparency-only) | `gpt-image-1.5` | OpenAI |

**Verify model IDs before use** — they change frequently:
```bash
curl -s "https://generativelanguage.googleapis.com/v1beta/models?key=$GEMINI_API_KEY" | python3 -c "import sys,json; [print(m['name']) for m in json.load(sys.stdin)['models'] if 'image' in m['name'].lower()]"
```

## GPT Image 2 Specifics

Released 2026-04-22. Three capabilities that change when you'd reach for it.

### 1. Text rendering actually works

Posters, OG images with headlines, infographics with labels, UI mockups, pricing cards. Text is rendered reliably, including non-Latin scripts (Japanese, Korean, Hindi, Bengali). Primary reason to switch from Gemini — Gemini doesn't render readable text at all.

### 2. Multi-variation batching

One prompt, up to 10 images in a single call. Variants share composition and palette but differ in detail. Good for style exploration before committing, A/B options for a client, rapid ideation.

### 3. Multi-reference compositing

Feed reference images alongside your prompt — product shots, lifestyle scenes, logos. The model places the product into the scene with correct lighting, scale, perspective. Enables "product in context" workflows without multi-turn editing.

### Modes

- **Instant** (default, all plans) — generates without a planning pass. Fast, good enough for most cases.
- **Thinking** (Plus/Pro/Business plans) — plans layout before drawing. Use when element counts matter ("3 icons in a row", "5 feature bullets") or text must land in specific regions. Fewer re-rolls on complex compositions.

### Aspect ratios

3:1 ultra-wide through 1:3 ultra-tall, plus 1:1, 3:2, 2:3, 16:9, 9:16. Wider range than other models — useful for website banners (ultra-wide hero) or mobile story formats (ultra-tall).

### Resolution

Up to 2K on the long edge standard. 4K in beta.

### Generation time

**Up to 2 minutes on complex prompts.** Build async UX — don't block on the response. Show progress or spin off and poll.

### Constraints

- **No transparent backgrounds.** Fall back to `gpt-image-1.5` when you need PNG transparency.
- **API Org Verification may be required** before the endpoint fires — enable in your OpenAI account settings if you hit auth errors on first call.

### Pricing (per 1024×1024 image)

| Quality | Cost |
|---------|------|
| Low | $0.006 |
| Medium | $0.053 |
| High | $0.211 |

Token pricing: $5/M text in, $10/M text out, $8/M image in, $30/M image out.

## The 5-Part Prompting Framework

Build prompts in this order for consistent results:

### 1. Image Type
Set the genre: "A photorealistic photograph", "An isometric illustration", "A flat vector icon"

### 2. Subject
Who or what, with specific details: "of a warm, approachable Australian woman in her early 30s, smiling naturally"

### 3. Environment
Setting and spatial relationships: "in a bright modern home with terracotta decor on wooden shelves behind her"

### 4. Technical Specs
Camera and lighting: "Shot at 85mm f/2.0, natural window light, head and shoulders framing"

### 5. Constraints
What to exclude: "Photorealistic, no text, no watermarks, no logos"

### Example (Good vs Bad)

```
BAD — keyword soup:
"professional woman, spa, warm lighting, high quality, 4K"

GOOD — narrative direction:
"A 

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.