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/imagen

@eab1642

Generate images using Google Gemini's image generation capabilities. Use this skill when the user needs to create, generate, or produce images for any purpose including UI mockups, icons, illustrations, diagrams, concept art, placeholder images, or visual representations.

Use this Skill: https://skilld.dev/gh/sanjay3290/ai-skills/imagen

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reference.md

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Imagen Skill Reference

Setup

1. Get a Gemini API Key

  1. Go to Google AI Studio
  2. Click "Get API Key"
  3. Create a new API key or use an existing one

2. Set Environment Variable

Windows (PowerShell):

$env:GEMINI_API_KEY = "your-api-key-here"

# To persist across sessions, add to your PowerShell profile:
Add-Content $PROFILE "`n`$env:GEMINI_API_KEY = 'your-api-key-here'"

Windows (CMD):

set GEMINI_API_KEY=your-api-key-here

# To persist, use System Properties > Environment Variables

macOS/Linux:

export GEMINI_API_KEY="your-api-key-here"

# Add to ~/.zshrc or ~/.bashrc to persist
echo 'export GEMINI_API_KEY="your-api-key-here"' >> ~/.zshrc

API Reference

Model

  • Model ID: gemini-3-pro-image-preview (configurable via --model flag or GEMINI_MODEL env var)
  • Endpoint: https://generativelanguage.googleapis.com/v1beta/models/{model}:streamGenerateContent

Image Sizes

Size Description
512 512x512 pixels - Fast, good for icons/thumbnails
1K 1024x1024 pixels - Default, balanced quality/speed
2K 2048x2048 pixels - High resolution, slower

Script Parameters

Python Script (Cross-Platform)

python scripts/generate_image.py <prompt> [output_path] [--size SIZE]
Parameter Required Default Description
prompt Yes - Text description of desired image
output_path No ./generated-image.png Where to save the image
--size No 1K Image size (512, 1K, or 2K)

Environment Variables

Variable Required Default Description
GEMINI_API_KEY Yes - Your Google Gemini API key
IMAGE_SIZE No 1K Image size (512, 1K, or 2K)

Usage Examples

Basic Generation

python scripts/generate_image.py "A serene mountain landscape at dawn"

Custom Output Path

python scripts/generate_image.py "Minimalist logo design" "./assets/logo.png"

High Resolution

python scripts/generate_image.py --size 2K "Detailed portrait" "./high-res.png"

Small/Fast Generation

python scripts/generate_image.py --size 512 "Simple icon" "./icon.png"

Prompt Tips

For Best Results

  1. Be specific: "A red sports car" vs "A cherry red 1967 Mustang convertible"
  2. Include style: "in watercolor style", "photorealistic", "minimalist flat design"
  3. Mention lighting: "golden hour lighting", "soft diffused light", "dramatic shadows"
  4. Specify composition: "close-up", "wide angle", "from above", "centered"

Advanced Prompting Techniques

These techniques produce significantly better results for photorealistic and professional imagery:

Camera & Lens Specifications

Include specific photography parameters for authentic looks:

  • Lens focal length: "85mm f/1.4 lens", "50mm prime", "35mm wide angle"
  • Aperture: "shallow depth of field at f/1.8", "deep focus at f/8"
  • Camera angle: "eye-level shot", "low angle looking up", "3/4 profile view"

Example: "Portrait shot with 85mm f/1.4 lens, shallow depth of field, subject sharp against soft bokeh background"

Lighting Architecture

Specify complete lighting setups for professional results:

  • Three-point lighting: key light, fill light, rim/back light
  • Catchlights: reflections in eyes for portraits
  • Shadow quality: "soft shadows", "dramatic hard shadows", "subtle rim light"

Example: "Professional headshot with three-point lighting setup, soft key light from left, subtle fill light, rim light for hair separation, visible catchlights in eyes"

Film Stock & Era Aesthetics

Reference specific film stocks or eras for authentic period looks:

  • Film stocks: "Kodak Portra 400 color palette", "Fujifilm Pro 400H tones", "Kodak Tri-X grain"
  • Era aesthetics: "1990s disposable camera quality", "early-2000s digital camera look", "1970s Polaroid style"
  • Grain and texture: "subtle film grain", "realistic sensor noise"

Example: "Casual portrait with Kodak Portra 400 color tones, natural film grain, 1990s aesthetic, soft warm highlights"

Facial Consistency (for portraits/people)

When generating or editing images with faces, explicitly state preservation requirements:

  • "Keep the facial features exactly consistent"
  • "Preserve original face structure and proportions"
  • "Do not alter or change the face"
Material & Texture Details

Add realistic texture specifications:

  • Skin: "natural skin texture with visible pores", "subtle skin imperfections"
  • Fabric: "fine wool texture visible", "silk sheen and drape"
  • Surfaces: "brushed metal finish", "weathered wood grain"

Example: "Close-up portrait showing natural skin texture with visible pores, fine fabric detail on collar, realistic hair strands"

Composition Framing

Be precise about framing and subject positioning:

  • Shot types: "chest-up framing", "3/4 body shot", "full body"
  • Positioning: "centered subject", "rule of thirds placement", "mirror selfie angle"
  • Aspect ratio context: "portrait orientation", "landscape format", "square crop"

Example Prompts by Use Case

UI/Frontend:

  • "A modern dashboard UI mockup with dark theme, showing analytics charts"
  • "Clean minimalist app icon for a task management app, rounded square shape"
  • "Hero image for a SaaS landing page, abstract gradient with geometric shapes"

Documentation:

  • "Simple architecture diagram showing microservices connected by arrows"
  • "Flowchart illustrating user authentication process"

Placeholders:

  • "Professional headshot placeholder, silhouette style, neutral gray background"
  • "Product image placeholder, simple box shape with 'Image Coming Soon' text"

Marketing/Creative:

  • "Isometric illustration of a modern office workspace"
  • "Gradient abstract background suitable for presentation slides"

Professional Portraits (using advanced techniques):

  • "Corporate headshot, 85mm f/2.8 lens, three-point studio lighting, navy blue suit, neutral gray backdrop, subtle catchlights, chest-up framing, natural skin texture"
  • "Casual lifestyle portrait, Kodak Portra 400 tones, natural window light, soft shadows, 3/4 body shot, authentic film grain, early-2000s digital aesthetic"

E-commerce & Product Photography:

  • "Product photo of leather watch, 100mm macro lens, soft diffused lighting, visible leather texture and stitching, clean white background, subtle reflection"
  • "Fashion flat-lay, overhead shot, soft natural lighting, fabric texture visible, minimalist composition"

Troubleshooting

"GEMINI_API_KEY not set"

Ensure the environment variable is set in your current shell:

Windows (PowerShell):

echo $env:GEMINI_API_KEY  # Should show your key

macOS/Linux:

echo $GEMINI_API_KEY  # Should show your key

"API request failed with HTTP status 400"

  • Check your prompt for special characters that may break JSON
  • Ensure the prompt isn't empty
  • Verify API key is valid

"API request failed with HTTP status 429"

  • Rate limited - wait a moment and retry
  • Consider upgrading your API quota

"No image data found in response"

  • The model may have refused the prompt (content policy)
  • Try rephrasing the prompt
  • Check if the model returned an error message in the response

Image is corrupted/won't open

  • Ensure Python 3.6+ is installed
  • Check if the full response was received (network issues)
  • Verify output path is writable

Windows-specific issues

  • Make sure Python is in your PATH
  • Use forward slashes or escaped backslashes in paths

API Costs

Check Google AI pricing for current Gemini API costs. Image generation typically costs more than text generation.

Limitations

  • Maximum prompt length varies by model
  • Some content types may be restricted by Google's content policy
  • Generated images are subject to Google's terms of service
  • Rate limits apply based on your API tier

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub16d

    The skill provides a Python script to generate images using the Google Gemini API. It utilizes standard libraries for all network and file system operations, avoiding external dependencies. The skill includes standard instructions for API key management and exhibits no malicious patterns.

  • Socket16d

    No alerts

  • Snyk16d

    Risk: LOW · No issues

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    Score: 93/100 · 2 sections analyzed

Signed by skilld at eab1642. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 weeks ago.

Activeupdated 7 months ago
metadata
{
  "author": "sanjay3290",
  "version": "1.0"
}

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