home / skills / resciencelab / opc-skills / banner-creator
This skill helps you create professional banners with AI, iterating designs and cropping to target ratios for GitHub, Twitter, or website headers.
npx playbooks add skill resciencelab/opc-skills --skill banner-creatorReview the files below or copy the command above to add this skill to your agents.
---
name: banner-creator
description: 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.
---
# 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 conversation
This skill creates professional banners using AI image generation and an iterative design process. It guides discovery, produces many variations, previews results in HTML, and crops the chosen design to target ratios. All outputs are organized into a dated .skill-archive folder for easy delivery.
I first gather purpose, target ratio/size, style, content elements, and color preferences. Then I generate a batch of wide (21:9) AI images, create an HTML preview, iterate on favored options with additional variations, and finally crop the approved banner to the requested target ratio and resolution. Generated files are saved under .skill-archive/banner-creator/<yyyy-mm-dd-summaryname>/ for review and delivery.
How many variations should I generate initially?
Start with 10–20 wide variations to explore styles; then iterate 10–20 more on favorites until you converge.
Why generate at 21:9 first instead of the target ratio?
Generating ultra-wide gives more compositional room and ensures important elements remain after cropping to specific platform ratios.