AI Image Generation

This is the core execution skill for AI image generation. It handles the actual generation work — model selection, prompt construction, API calls, iteration, and quality verification.

Use this skill when: You need to generate any image and want optimal quality. Route here from: ai-creative-workflow, ai-creative-strategist, or direct requests.

Why This Skill Exists

The problem: Most people waste time and money on AI image generation because they:

Use the wrong model for the job
Write vague prompts that produce generic results
Generate once and hope for the best
Don't know how to iterate effectively

The solution: A systematic approach that:

Uses the right model (Nano Banana Pro via Glif for speed + quality)
Constructs prompts with proven structure
Builds in iteration as the default workflow
Knows when to stop and when to keep refining

Model Selection

Primary: Nano Banana Pro via Glif (DEFAULT)

Why: Fastest high-quality generation available. ~20 seconds vs ~3 minutes for comparable quality.

Model	Glif ID	Speed	Quality
🍌 Nano Banana Pro Text 2 Image	`cmi7ne4p40000kz04yup2nxgh`	~20sec	Excellent

Use the
run_glif
MCP tool:

Glif: 🍌 Nano Banana Pro Text 2 Image
ID: cmi7ne4p40000kz04yup2nxgh
Inputs: ["Your prompt here"]

Do NOT use: imagen-3, DALL-E, Flux, or direct Replicate API calls unless specifically requested.

When to Use Alternatives

IF user specifically requests a different model:
    use requested model

ELIF need text rendering (logos, quotes, announcements):
    use Recraft v3 or Ideogram v3 (route to ai-typography)

ELIF need image-to-video:
    generate image first, then route to ai-video-generation

ELIF need people/lifestyle imagery:
    still use Nano Banana Pro (handles people well)

ELSE:
    Nano Banana Pro via Glif  // DEFAULT

Prompt Construction

The Formula

[SUBJECT] + [SETTING/CONTEXT] + [STYLE] + [LIGHTING] + [QUALITY BOOSTERS]

Each element serves a purpose:

SUBJECT — What you're generating (be specific)
SETTING — Where/context (grounds the image)
STYLE — Visual aesthetic (photography, illustration, etc.)
LIGHTING — Mood and dimension (often overlooked, always important)
QUALITY BOOSTERS — Technical terms that elevate output

Subject Specificity

Bad: "A coffee cup" Good: "Artisan ceramic coffee cup with latte art, steam rising"

Bad: "A laptop" Good: "Silver MacBook Pro on oak desk, screen showing code editor"

Bad: "A person working" Good: "Woman in her 30s, focused expression, typing on laptop in bright modern office"

The more specific your subject, the less the model has to guess.

Setting/Context Options

Studio/Clean:

on pure white background
against dark charcoal gradient
floating in negative space
on seamless backdrop

Environmental:

in modern minimalist office
on rustic wooden table
in cozy coffee shop
against urban cityscape

Abstract:

with geometric patterns
surrounded by abstract shapes
with dynamic particle effects
in surreal dreamscape

Style Presets

Photography Styles:

professional product photography
lifestyle photography
editorial fashion photography
documentary photography style
portrait photography
macro photography
aerial/drone photography

Illustration Styles:

digital illustration
watercolor illustration
vector art style
hand-drawn sketch style
3D rendered
isometric illustration
flat design

Artistic Styles:

cinematic
surrealist
minimalist
maximalist
retro/vintage
futuristic
organic/natural

Lighting Presets

Lighting is the most underused prompt element. It dramatically affects mood and quality.

Studio Lighting:

professional studio lighting
three-point lighting setup
single dramatic spotlight
soft diffused lighting
rim lighting

Natural Lighting:

soft natural daylight
golden hour light
overcast diffused light
harsh midday sun
blue hour

Dramatic Lighting:

high contrast dramatic lighting
moody low-key lighting
backlit silhouette
chiaroscuro lighting
neon accent lighting

Specific Directions:

key light from upper left
side lighting from right
overhead soft box
underlighting (dramatic)

Quality Boosters

Add these to elevate output quality:

Technical Quality:

ultra-detailed
high resolution
sharp focus
professional quality
8k resolution

Professional Context:

commercial photography
award-winning
magazine quality
advertising campaign
editorial quality

Specific Techniques:

shallow depth of field
bokeh background
lens flare
motion blur
long exposure

Complete Prompt Examples

Product Hero Shot

Premium wireless headphones floating against dark charcoal gradient,
professional product photography, single dramatic spotlight from upper left,
subtle rim lighting on edges, metallic surface reflections,
ultra-detailed, commercial advertising quality, negative space on right for text

Lifestyle Scene

Young professional woman enjoying morning coffee in bright modern apartment,
natural window light streaming in, cozy weekend aesthetic,
lifestyle photography, warm tones, genuine relaxed expression,
shallow depth of field, editorial quality

Food Photography

Gourmet burger with melted cheese and fresh vegetables on rustic wooden board,
professional food photography, soft diffused overhead lighting,
steam rising, appetizing presentation, shallow depth of field,
restaurant menu quality, warm inviting tones

Tech/SaaS

Modern dashboard interface on large monitor in minimalist home office,
clean UI design visible on screen, soft ambient lighting,
tech product photography, contemporary workspace aesthetic,
shallow depth of field on screen, professional quality

Abstract/Conceptual

Abstract representation of data flow and connectivity,
glowing particles forming network patterns against deep blue gradient,
futuristic technology aesthetic, dynamic motion blur,
cinematic quality, vibrant cyan and purple accent colors

Aspect Ratio Guide

Use Case	Ratio	Pixels	Notes
Square (Instagram, LinkedIn)	1:1	1024×1024	Most versatile
Landscape (Hero banners, YouTube)	16:9	1280×720	Web standard
Portrait tall (Instagram feed)	4:5	1024×1280	Better feed presence
Stories/TikTok	9:16	1080×1920	Vertical mobile
Pinterest	2:3	1000×1500	Optimal for pins
Wide cinematic	21:9	2560×1080	Dramatic headers

Default: 1:1 unless platform-specific requirement is known.

Execution Workflow

Step 1: Clarify Requirements

Before generating, know:

□ What is the subject? (be specific)
□ What style/aesthetic?
□ What platform/use case?
□ What aspect ratio?
□ Any must-have elements?
□ Any must-avoid elements?

Step 2: Construct Prompt

Use the formula:

[SUBJECT] + [SETTING] + [STYLE] + [LIGHTING] + [QUALITY BOOSTERS]

Step 3: Generate First Draft

Glif: 🍌 Nano Banana Pro Text 2 Image
ID: cmi7ne4p40000kz04yup2nxgh
Inputs: ["[constructed prompt]"]

Step 4: Present for Feedback

markdown

## Image Generated

**Prompt:** [prompt used]
**Aspect Ratio:** [ratio]

**Image URL:** [URL]

**Quick Assessment:**
- Subject accuracy: ✓/✗
- Style match: ✓/✗
- Composition: ✓/✗
- Quality: ✓/✗

**Feedback?**
- What works?
- What should change?
- Ready to approve or iterate?

Step 5: Iterate Based on Feedback

Common iteration patterns:

"Too dark" → Add "bright" "well-lit" "high key lighting"
"Too busy" → Add "minimal" "clean" "simple composition"
"Wrong style" → Be more explicit about style reference
"Missing element" → Add specific element to prompt
"Wrong mood" → Adjust lighting and color descriptors

Step 6: Approve or Continue

If approved → Deliver final image
If needs changes → Return to Step 5
If fundamentally wrong → Return to Step 2 with new prompt approach

Iteration Strategies

When It's Close But Not Right

Problem: Almost right but something's off Strategy: Make targeted prompt adjustments

Original: "Coffee cup on table"
Iteration 1: "Coffee cup on table, warmer tones" (if too cool)
Iteration 2: "Coffee cup on table, warmer tones, more steam" (if missing element)

When It's Completely Wrong

Problem: Output doesn't match intent at all Strategy: Rewrite prompt from scratch with more specificity

Don't iterate on a bad foundation. Start fresh with better prompt construction.

When Quality Is Low

Problem: Image looks AI-generated or low quality Strategy: Add quality boosters and professional context

Add: "ultra-detailed, professional photography, commercial quality"
Add: "8k resolution, sharp focus, magazine quality"

When Composition Is Wrong

Problem: Elements in wrong places, bad framing Strategy: Be explicit about composition

Add: "subject centered in frame"
Add: "negative space on left for text"
Add: "rule of thirds composition"
Add: "close-up shot" or "wide establishing shot"

Quality Checklist

Before delivering, verify:

Technical Quality

Resolution is sufficient for intended use
No obvious AI artifacts (weird fingers, melted text, etc.)
Sharp focus on main subject
Appropriate for intended platform

Compositional Quality

Subject is clear and prominent
Composition supports intended use (text space if needed)
Lighting creates appropriate mood
Colors are cohesive

Brief Alignment

Matches requested subject
Matches requested style
Matches requested mood/tone
Usable for intended platform

Common Issues & Solutions

Issue	Cause	Solution
Generic/stock photo feel	Vague prompt	Add specific details, unique elements
Wrong style	Style not specified	Be explicit: "product photography style" not just "photo"
Poor lighting	No lighting direction	Add specific lighting: "dramatic spotlight from upper left"
Cluttered composition	Too many elements	Add "minimal" "clean" "simple composition"
AI artifacts	Model limitations	Regenerate, or note area to avoid
Wrong aspect ratio	Default used	Specify ratio in request
Doesn't match brand	No style reference	Add brand color/style keywords
Text rendering issues	Wrong model	Route to ai-typography for text-heavy graphics

Output Format

Standard Output

markdown

## Image Generated

**Subject:** [what was generated]
**Style:** [style used]
**Aspect Ratio:** [ratio]

**Image URL:** [URL]

**Prompt Used:**
> [full prompt for reference]

**Quality Check:**
- ✓ Subject accurate
- ✓ Style matches
- ✓ Composition works
- ✓ Quality sufficient

**Options:**
- [ ] Approve and use
- [ ] Iterate (specify changes)
- [ ] Generate variant
- [ ] Try different approach

With Iteration Context

markdown

## Image Generated (Iteration 2)

**Changes from v1:** [what changed]
**Image URL:** [URL]

**Comparison:**
- v1: [issue]
- v2: [improvement]

**Feedback needed?**

Handoff Protocols

Receiving from ai-creative-workflow

yaml

Receive:
  subject: "[what to generate]"
  style: "[aesthetic direction]"
  platform: "[intended use]"
  aspect_ratio: "[ratio]"
  constraints: "[any limitations]"

Returning to Workflow

yaml

Return:
  status: "complete" | "needs_iteration" | "needs_different_approach"
  deliverables:
    - url: "[image URL]"
      aspect_ratio: "[ratio]"
      prompt_used: "[prompt]"
  feedback_needed: "[any questions]"

Routing to Video

yaml

Route to ai-video-generation:
  image_url: "[approved image URL]"
  aspect_ratio: "[ratio]"
  animation_intent: "[what motion is needed]"

Integration with Creative Pipeline

IMAGE GENERATION PIPELINE

┌─────────────────────────────────────────┐
│  Request arrives (direct or routed)     │
│  → Clarify requirements                 │
│  → Construct prompt                     │
└─────────────────────────────────────────┘
                    │
                    ▼
┌─────────────────────────────────────────┐
│  ai-image-generation (THIS SKILL)       │
│  → Generate with Nano Banana Pro/Glif   │
│  → Present for feedback                 │
│  → Iterate as needed                    │
│  → Quality check                        │
└─────────────────────────────────────────┘
                    │
        ┌───────────┴───────────┐
        ▼                       ▼
┌──────────────────┐   ┌──────────────────┐
│  Static Delivery │   │  Route to Video  │
│  → Final image   │   │  → ai-video-     │
│    delivered     │   │    generation    │
└──────────────────┘   └──────────────────┘

Speed vs Quality Decision

QUICK DRAFT (concept testing):
    → Nano Banana Pro via Glif (~20 sec)
    → Good enough to evaluate concept
    → Iterate quickly

PRODUCTION QUALITY (final delivery):
    → Nano Banana Pro via Glif (~20 sec)
    → Already production quality
    → Most cases don't need more

MAXIMUM QUALITY (premium needs):
    → Direct Replicate API call to specialized model
    → Only if Glif output insufficient
    → Rare — Nano Banana Pro handles most needs

Default to Glif. It's fast AND high quality. Only go elsewhere if specific need arises.

Tips from Experience

What Works

Specificity beats creativity — "Red 2024 Tesla Model 3" beats "cool car"
Lighting is underrated — Always specify lighting direction/type
Negative space matters — Mention if you need room for text
Iterate fast — Don't overthink first prompt, generate and refine
Quality boosters work — "Professional photography, ultra-detailed" actually helps

What Doesn't Work

Vague prompts — "Something cool" produces nothing useful
Too many elements — Keep focused, don't cram everything in
Ignoring aspect ratio — Always match to intended platform
Single generation — Plan for iteration, don't expect perfection first try
Wrong model for text — Nano Banana Pro struggles with text rendering

The 80/20

80% of good results come from:

Specific subject description
Clear style direction
Explicit lighting
Appropriate aspect ratio

Get these four right, and you'll get good results.

ai-image-generation

NPX Install

Tags

SKILL.md Content

AI Image Generation

Why This Skill Exists

Model Selection

Primary: Nano Banana Pro via Glif (DEFAULT)

When to Use Alternatives

Prompt Construction

The Formula

Subject Specificity

Setting/Context Options

Style Presets

Lighting Presets

Quality Boosters

Complete Prompt Examples

Product Hero Shot

Lifestyle Scene

Food Photography

Tech/SaaS

Abstract/Conceptual

Aspect Ratio Guide

Execution Workflow

Step 1: Clarify Requirements

Step 2: Construct Prompt

Step 3: Generate First Draft

Step 4: Present for Feedback

Step 5: Iterate Based on Feedback

Step 6: Approve or Continue

Iteration Strategies

When It's Close But Not Right

When It's Completely Wrong

When Quality Is Low

When Composition Is Wrong

Quality Checklist

Technical Quality

Compositional Quality

Brief Alignment

Common Issues & Solutions

Output Format

Standard Output

With Iteration Context

Handoff Protocols

Receiving from ai-creative-workflow

Returning to Workflow

Routing to Video

Integration with Creative Pipeline

Speed vs Quality Decision

Tips from Experience

What Works

What Doesn't Work

The 80/20