El Bruno

⚠️ This blog post was created with the help of AI tools. Yes, I used a bit of magic from language models to organize my thoughts and automate the boring parts, but the geeky fun and the 🤖 in C# are 100% mine.

Hi!

Two weeks ago, I shipped t2i — a terminal-first CLI for text-to-image generation. Today I’m excited to announce two major additions that make t2i even more powerful:

1. GPT-Image-1.5 and GPT-Image-2 support — Microsoft’s DALL-E 3 and next-gen models via Azure OpenAI
2. AI agent skill integration — Teach GitHub Copilot and Claude Code to use t2i automatically

TL;DR

• New models: GPT-Image-1.5 (DALL-E 3) and GPT-Image-2 (next-gen) now available via Azure OpenAI
• Skill integration: Run t2i init to teach GitHub Copilot and Claude Code how to generate images autonomously
• Updated providers: Now supporting 5 cloud models (FLUX.2 Pro, FLUX.2 Flex, MAI-Image-2, GPT-Image-1.5, GPT-Image-2)
• Version: Available in t2i v0.16.0+ via dotnet tool update --global ElBruno.Text2Image.Cli

🤖 Part 1: AI Agent Skills — The Biggest Feature

This is the feature I’m most excited about: teaching AI agents how to use t2i automatically

What Are Skills?

Skills are packages of functionality that AI coding agents can discover and invoke on their own. By installing a skill file, you enable agents like GitHub Copilot and Claude Code to:

• Generate images directly within your development workflow
• Automate batch creation based on natural language requests
• Integrate image generation into CI/CD pipelines and automation scripts

Skills work by placing metadata files in well-known directories (.github/skills/ for Copilot, .claude/skills/ for Claude Code) that agents scan during initialization. Once installed, these agents understand:

• Which t2i commands exist and when to use each one
• How to set up secrets safely (env vars first, never commit keys)
• The full provider list and which one to default to
• Common workflows: first-time setup, single image, batch loops

How to Set It Up

Install the cli tool locally, setup the tool and from any repository:

t2i init

That’s it. This command writes skill metadata to:

• .github/skills/t2i/SKILL.md (for GitHub Copilot)
• .claude/skills/t2i/SKILL.md (for Claude Code)

Want only one target?

t2i init --target github   # GitHub Copilot only
t2i init --target claude   # Claude Code only

The skill files include:

• Tool overview and capabilities
• Command syntax with examples
• Provider configuration instructions
• Best practices and troubleshooting tips

Real-World Example: GitHub Copilot

After running t2i init --target github, you can interact with Copilot naturally:

You: “Generate a futuristic cityscape with neon lights and save it as hero.png”

Copilot: Automatically invokes:

t2i "futuristic cityscape with neon lights, cyberpunk style, volumetric fog" \
  --provider foundry-flux2 \
  --width 1792 \
  --height 1024 \
  --output hero.png

You: “Create a series of social media images for our product launch — abstract tech theme”

Copilot: Automatically invokes:

t2i "abstract tech background with circuit patterns" --output social-1.png
t2i "geometric tech shapes with gradient colors" --output social-2.png
t2i "digital network visualization, modern style" --output social-3.png

No need to remember the exact syntax or provider flags — Copilot handles it.

Real-World Example: Claude Code

After running t2i init --target claude, Claude can drive t2i based on your requests:

You: “I need an image of a sunset over mountains for the landing page, wide format”

Claude: Automatically invokes:

t2i "sunset over mountains, warm golden hour colors, panoramic view" \
  --provider foundry-flux2 \
  --width 1792 \
  --height 1024 \
  --output landing-hero.png

You: “Generate icon placeholders: home, settings, profile — all square, simple line art”

Claude: Automatically invokes multiple commands:

t2i "home icon, simple line art, minimalist, 512x512" --out icon-home.png
t2i "settings icon, simple line art, minimalist, 512x512" --out icon-settings.png
t2i "profile icon, simple line art, minimalist, 512x512" --out icon-profile.png

Why This Matters

Before skills, you had to:

1. Remember t2i syntax
2. Look up provider names
3. Check configuration flags
4. Write your own automation scripts

With skills installed, AI agents become your image generation assistant:

• They know the syntax
• They pick the right provider
• They handle dimensions and output paths
• They batch generate when appropriate

This is especially powerful in CI/CD scenarios. Imagine a GitHub Actions workflow where Copilot autonomously generates marketing assets, social media images, or documentation screenshots based on a simple prompt list.

Configure providers first

Before your AI agent can use t2i, ensure at least one provider is configured:

t2i config   # Interactive setup

Use environment variables in CI/CD

For automated workflows, configure via env vars:

# GitHub Actions example
- name: Generate images
  env:
    T2I_FOUNDRY_FLUX2_ENDPOINT: ${{ secrets.FOUNDRY_ENDPOINT }}
    T2I_FOUNDRY_FLUX2_APIKEY: ${{ secrets.FOUNDRY_APIKEY }}
  run: |
    dotnet tool install --global ElBruno.Text2Image.Cli
    t2i init
    t2i "hero image for landing page" --provider foundry-flux2 --out assets/hero.png

Update skills after CLI upgrades

When you update t2i, refresh the skill metadata:

dotnet tool update --global ElBruno.Text2Image.Cli
t2i init   # Regenerates skill files with latest docs

More Details

For the complete skill integration guide, including troubleshooting, advanced customization, and platform-specific instructions, see:

→ docs/skill-integration.md

🎨 Part 2: GPT-Image Models — More Choices

Now for the second big update: GPT-Image-1.5 and GPT-Image-2 support.

These are Microsoft’s image generation models available via Azure OpenAI Service. Both are based on OpenAI technology but deployed in Azure for enterprise-grade reliability, compliance, and control.

GPT-Image-1.5 (DALL-E 3)

What it is: Azure OpenAI’s implementation of OpenAI’s DALL-E 3 model.

Best for:

• Natural language prompts — Excellent at understanding complex, conversational descriptions
• Photorealistic images — Great for realistic scenes, portraits, and product photography
• Text rendering — Better at including readable text in images (though still not perfect)
• Enterprise compliance — Deployed in your Azure region with full data residency

Supported sizes:

• 1024×1024 (square)
• 1792×1024 (landscape)
• 1024×1792 (portrait)

Example use cases:

• Marketing visuals with text overlays
• Product mockups and packaging designs
• Editorial illustrations for blog posts
• Social media graphics

GPT-Image-2 (Next-Gen)

What it is: Microsoft’s next-generation image model — more advanced than DALL-E 3.

Best for:

• High-quality artistic images — Improved coherence and style consistency
• Complex compositions — Better at multi-object scenes with detailed relationships
• Stylized rendering — Excels at specific art styles (watercolor, oil painting, digital art)
• Prompt adherence — Follows instructions more accurately, especially for abstract concepts

Supported sizes:

• 1024×1024 (square)
• 1792×1024 (landscape)
• 1024×1792 (portrait)

Example use cases:

• Concept art and game design
• Artistic book cover designs
• Abstract and stylized illustrations
• Character design and visual development

How to Use Them

Both models use the Azure OpenAI Service, so you need:

1. An Azure subscription
2. An Azure OpenAI resource
3. A deployment of gpt-image-1.5 or gpt-image-2
4. Your endpoint URL and API key

Quick Setup (GPT-Image-1.5)

# Interactive setup wizard
t2i config set foundry-gpt-image-1p5

The wizard prompts for:

• Endpoint URL (e.g., https://my-resource.openai.azure.com/)
• API Key (from Azure Portal)
• Deployment name (e.g., gpt-image-15)

Then generate:

t2i "an impressionist painting of a garden in spring" \
  --provider foundry-gpt-image-1p5

Quick Setup (GPT-Image-2)

# Interactive setup wizard
t2i config set foundry-gpt-image-2

Then generate:

t2i "a sci-fi space station orbiting a ringed planet, digital art" \
  --provider foundry-gpt-image-2

PowerShell Examples

# GPT-Image-1.5: Photorealistic product shot
t2i "professional product photo of a smartwatch on marble, studio lighting" `
  --provider foundry-gpt-image-1p5 `
  --width 1792 `
  --height 1024 `
  --output product-hero.png
# GPT-Image-2: Abstract art for website header
t2i "abstract geometric patterns with vibrant gradients, modern tech aesthetic" `
  --provider foundry-gpt-image-2 `
  --output header-bg.png

Bash Examples

# GPT-Image-1.5: Editorial illustration
t2i "a serene lake at sunrise with mountains in the distance, photorealistic" \
  --provider foundry-gpt-image-1p5 \
  --width 1792 \
  --height 1024 \
  --output editorial.png
# GPT-Image-2: Character concept art
t2i "character concept art of a futuristic knight, armor with neon accents, digital painting" \
  --provider foundry-gpt-image-2 \
  --width 1024 \
  --height 1792 \
  --output character.png

Switching Models

You can set a default provider in your config:

# Use GPT-Image-2 as default
t2i config set default-provider foundry-gpt-image-2
# Now this uses GPT-Image-2
t2i "your prompt here"

Or specify per-command:

# Compare outputs from different models
t2i "a cyberpunk cityscape" --provider foundry-flux2 --output flux-city.png
t2i "a cyberpunk cityscape" --provider foundry-gpt-image-2 --output gpt-city.png

Complete Provider List

Here’s the full lineup after this update:

How to choose:

📊 Model Comparison

Here’s a quick comparison to help you choose:

Performance notes:

• FLUX.2 and MAI models use asynchronous polling (submit → poll → retrieve)
• GPT-Image models use synchronous API (submit → wait → receive)
• First request may be slower due to model warm-up
• Batch jobs benefit from parallel requests

🔄 Migration Guide

If you’re already using t2i with FLUX.2 or MAI-Image-2, upgrading is straightforward.

Step 1: Update the CLI

dotnet tool update --global ElBruno.Text2Image.Cli

Verify:

t2i --version
# Should show v0.16.0 or later

Step 2: List New Providers

t2i providers

You should see:

• foundry-gpt-image-1p5 — GPT-Image-1.5 / DALL-E 3
• foundry-gpt-image-2 — GPT-Image-2 (Next-Gen)

Step 3: Configure GPT Models (Optional)

If you want to use GPT-Image models:

t2i config set foundry-gpt-image-1p5   # Configure GPT-Image-1.5
t2i config set foundry-gpt-image-2     # Configure GPT-Image-2

Step 4: Update Skill Files

If you previously ran t2i init, refresh your skill metadata:

t2i init --force   # Overwrites existing skill files

This ensures GitHub Copilot and Claude Code know about the new models.

Step 5: Test

t2i doctor

Check that all providers show as “configured” and “healthy.”

🚀 What’s Next

This release adds major capabilities, but there’s more coming:

v0.17.0+ (Q2 2026):

• Local inference edition — CPU, CUDA, DirectML providers (no cloud required)
• Model marketplace — Download and manage local ONNX models
• Batch API — Submit multiple prompts in one call
• Image-to-image — Use existing images as input for variations

Community-requested features:

• Negative prompts — Specify what not to include
• Style presets — Quick templates (e.g., --style cinematic)
• Config profiles — Switch between dev/prod configurations
• Web UI — Optional browser-based interface

Want to influence the roadmap? File a feature request:

→ github.com/elbruno/ElBruno.Text2Image/issues

📚 Links & Resources

Documentation:

• CLI Tool Reference
• Skill Integration Guide
• GPT-Image-1.5 Setup Guide

Installation:

• NuGet Package
• GitHub Releases

Community:

• GitHub Repository
• Report Issues

Model: GPT-Image-2
Size: 1792×1024 (landscape)
Generation time: ~9.2 seconds
Cost: ~$0.15

This demonstrates GPT-Image-2’s ability to understand abstract concepts (a terminal “emitting” images) and render them with artistic style.

Questions? Feature requests? Found a bug?

→ github.com/elbruno/ElBruno.Text2Image/issues