gemini-image-gen

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Generate images using Google's Gemini API — hero backgrounds, OG images, placeholder photos, textures, and style-matched variants. Uses free-tier models for drafts, paid for finals. No dependencies beyond Python 3. Trigger with 'generate image', 'gemini image', 'make a hero background', 'create placeholder photo', 'generate OG image', 'AI image', or 'need an image for'.

2installs

Sourcejezweb/claude-skills

Added on2026-02-27

NPX Install

npx skill4agent add jezweb/claude-skills gemini-image-gen

SKILL.md Content

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Gemini Image Generator

Generate contextual images for web projects using the Gemini API. Produces hero backgrounds, OG cards, placeholder photos, textures, and style-matched variants.

Setup

API Key: Set

GEMINI_API_KEY

as an environment variable. Get a key from https://aistudio.google.com/apikey if you don't have one.

bash

export GEMINI_API_KEY="your-key-here"

Workflow

Step 1: Understand What's Needed

Gather from the user or project context:

What: hero background, product photo, texture, OG image, placeholder
Style: warm/cool/minimal/luxurious/bold — check project's colour palette (input.css, tailwind config)
Dimensions: hero (1920x1080), OG (1200x630), square (1024x1024), custom
Count: single image or multiple variants to choose from

Step 2: Build the Prompt

Use concrete photography parameters, not abstract adjectives. Read references/prompting-guide.md for the full framework.

Quick rules:

Narrate like directing a photographer
Use camera specs: "85mm f/1.8", "wide angle 24mm"
Use colour anchors from the project palette: "warm terracotta (#C66A52) and cream (#F5F0EB) tones"
Use lighting descriptions: "golden-hour light from the left, 4500K"
Always end with: "No text, no watermarks, no logos, no hands"

Step 3: Generate

bash

python3 plugins/design-assets/skills/gemini-image-gen/scripts/generate-image.py \
  --prompt "Soft-focus atmospheric background, warm gold and cream botanical elements, luxury spa aesthetic, wide landscape" \
  --output public/images/hero.png \
  --model gemini-2.5-flash-image

Multiple variants:

bash

python3 .../generate-image.py --prompt "..." --output public/images/hero.png --count 3
# Produces hero-1.png, hero-2.png, hero-3.png

Style matching from a reference image:

bash

python3 .../generate-image.py \
  --prompt "Same warm lighting and colour palette, but showing a massage treatment room" \
  --reference public/images/existing-hero.jpg \
  --output public/images/services-bg.png \
  --model gemini-3-pro-image-preview

Step 4: Post-Process (Optional)

Use the image-processing skill for resizing, format conversion, or optimisation:

bash

python3 plugins/design-assets/skills/image-processing/scripts/process-image.py \
  optimise public/images/hero.png --output public/images/hero.webp --width 1920

Step 5: Present to User

Show the generated images for review. Read the image files to display them inline if possible, otherwise describe what was generated and let the user open them.

Presets

Starting prompts — enhance with project-specific context (colours, mood, subject):

Preset	Base Prompt
`hero-background`	"Wide atmospheric background, soft-focus, [colour tones], [mood], landscape 1920x1080"
`og-image`	"Clean branded card background, [brand colours], subtle gradient, 1200x630"
`placeholder-photo`	"Professional stock-style photo of [subject], natural lighting, warm tones"
`texture-pattern`	"Subtle repeating texture, [material], seamless tile, muted [colour]"
`product-shot`	"Product photography, [item] on [surface], soft studio lighting, clean background"

Model Selection

Use case	Model	Cost
Drafts, quick placeholders	`gemini-2.5-flash-image`	Free (~500/day)
Final client assets	`gemini-3-pro-image-preview`	~$0.04/image
Style-matched variants	`gemini-3-pro-image-preview` + `--reference`	~$0.04/image

Verify current model IDs if errors occur — they change frequently.

Reference Files

When	Read
Building effective prompts	references/prompting-guide.md

gemini-image-gen

NPX Install

Tags

SKILL.md Content

Gemini Image Generator

Setup

Workflow

Step 1: Understand What's Needed

Step 2: Build the Prompt

Step 3: Generate

Step 4: Post-Process (Optional)

Step 5: Present to User

Presets

Model Selection

Reference Files