Banner Creator Skill
Create banners using AI image generation. Discuss format/style, generate variations, iterate with user feedback, crop to target ratio. Use when user wants to create a banner, header, hero image, cover image, GitHub banner, Twitter header, or readme banner.
MCP get_skill({ skillId: "banner-creator-skill-2e24e496" })Use this skill with your agent
Create a free account and connect via MCP
# Banner Creator Skill
Create professional banners through AI image generation with an iterative design process.
## Prerequisites
**Required API Keys (set in environment):**
- `GEMINI_API_KEY` - Get from [Google AI Studio](https://aistudio.google.com/apikey)
**Required Skills:**
- `nanobanana` - AI image generation (Gemini 3 Pro Image)
## File Output Location
All generated files should be saved to the `.skill-archive` directory:
```
.skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/
```
**Example:**
```
.skill-archive/banner-creator/2026-01-19-opc-banner/
banner-01.png
banner-02.png
...
banner-03-cropped.png
preview.html
```
## Workflow
### Step 1: Discovery & Requirements
Before generating, gather requirements from user:
**Ask about:**
1. **Purpose** - Where will the banner be used?
- GitHub README
- Twitter/X header
- LinkedIn banner
- Website hero
- YouTube channel art
2. **Target ratio/size** - See [references/formats.md](./references/formats.md):
- `2:1` (1280x640) - GitHub README
- `3:1` (1500x500) - Twitter header
- `16:9` (1920x1080) - Website hero
3. **Style preference**:
- Match existing logo/brand?
- Pixel art / 8-bit retro
- Minimalist / flat design
- Gradient / modern
- Illustrated / artistic
4. **Content elements**:
- Brand name / project name?
- Tagline / slogan?
- Logo character to include?
5. **Color preferences**:
- Existing brand colors?
- Let AI decide?
**Wait for user confirmation before proceeding!**
### Step 2: Generate Banner Variations
Generate 20 banner variations using the `nanobanana` skill:
```bash
# Generate single banner
python3 <nanobanana_skill_dir>/scripts/generate.py "{style} banner for {brand}, {description}, {text elements}" \
--ratio 21:9 -o .skill-archive/banner-creator/<date-name>/banner-01.png
# Batch generate 20 banners
python3 <nanobanana_skill_dir>/scripts/batch_generate.py "{style} banner for {brand}, {description}, {text elements}" \
-n 20 --ratio 21:9 -d .skill-archive/banner-creator/<date-name> -p banner
```
**Guidelines:**
- Generate at `21:9` ratio (widest available), crop later to target
- Use batch_generate.py for multiple variations (includes auto-delay)
- Use sequential naming: `banner-01.png`, `banner-02.png`, etc.
**Image Editing (for incorporating existing logo):**
```bash
python3 <nanobanana_skill_dir>/scripts/generate.py "add {logo character} to the left side of the banner" \
-i /path/to/existing-logo.png --ratio 21:9 -o banner-with-logo.png
```
### Step 3: Create HTML Preview
Copy the preview template and open in browser:
```bash
cp <skill_dir>/templates/preview.html .skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/preview.html
```
Then open in default browser:
```bash
open .skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/preview.html
```
**IMPORTANT:** Update the HTML to include the correct number of banners generated.
### Step 4: Iterate with User
Ask user which banners they prefer:
- "Which banners do you like? (e.g., #3, #7, #15)"
- "What do you like about them?"
- "Any changes you'd want?"
Based on feedback:
1. Generate 10-20 more variations of favorite styles
2. Use naming: `banner-{original}-v{n}.png` (e.g., `banner-03-v1.png`)
3. Update HTML preview
4. Repeat until user selects final banner
### Step 5: Crop to Target Ratio
Once user approves a banner, crop to target size:
```bash
python3 <skill_dir>/scripts/crop_banner.py {input.png} {output.png} --ratio 2:1 --width 1280
```
**Common targets:**
- GitHub README: `--ratio 2:1 --width 1280` → 1280x640
- Twitter header: `--ratio 3:1 --width 1500` → 1500x500
- Website hero: `--ratio 16:9 --width 1920` → 1920x1080
### Step 6: Deliver Final Assets
Present final deliverables:
```
## Final Banner Assets
| File | Description | Size |
|------|-------------|------|
| banner-03.png | Original (21:9) | 2016x864 |
| banner-03-cropped.png | GitHub README (2:1) | 1280x640 |
All files saved to: `.skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/`
Copy final banner to user's desired location.
```
## Quick Reference
### Common Prompt Patterns
**With Text:**
```
Wide banner for {brand}, {style} style, featuring "{text}" prominently displayed, {colors}, {scene/elements}
```
**With Character:**
```
Wide banner featuring {character description}, {style} style, {scene}, text "{brand name}" on {position}, {colors}
```
**Abstract/Gradient:**
```
Abstract {style} banner, {colors} gradient, geometric patterns, modern tech feel, text "{brand}" centered
```
**Scene-based:**
```
{Style} illustration banner, {scene description}, {character} in {action}, "{brand}" text overlay, {colors}
```
### Supported Aspect Ratios
Generate at widest ratio, then crop:
- `21:9` - Ultra-wide (recommended for generation)
- `16:9` - Wide
- `3:2` - Standard wide
## References
- [references/formats.md](./references/formats.md) - Common banner sizes by platform
- [examples/opc-banner-creation.md](./examples/opc-banner-creation.md) - Full example conversationRelated Skills
More skills in Design, Media & Creative
Ableton Lom
Ableton Live Object Model (LOM) API reference for Python Remote Scripts and control surface development.
Accessibility Compliance
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
Adobe Illustrator Scripting
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
🎬 AI Cinema Director Skill
Direct high-fidelity cinematic video with AI — translates creative intent into technical cinematographic directives for Veo3, Kling, and Luma video models via muapi.ai
AI Clipping
Turn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.
AI Workflow Builder
Build, run, and visualize multi-step AI generation workflows. The AI architect translates natural language descriptions into connected node graphs — chain image generation, video creation, enhancement, and editing into automated pipelines.
Explore Other Categories
Skills from other categories with shared topics
Nano Banana - AI Image Generation
Generate and edit images using Google Gemini 3 Pro Image (Nano Banana Pro). Supports text-to-image, image editing, various aspect ratios, and high-resolution output (2K/4K). Use when user wants to generate images, create images, use Gemini image generation, or do AI image generation.
Reddit Skill
Search and retrieve content from Reddit. Get posts, comments, subreddit info, and user profiles via the public JSON API. Use when user mentions Reddit, a subreddit, or r/ links.
Skill Name
Clear description of what this skill does and when to use it. Include trigger keywords and contexts inline, e.g. "Use when user wants to X, Y, or Z."