suitedaces
Registry indexed
image-gen
Generate and edit images using the Gemini API. Text-to-image, image editing, multi-turn iteration, 4K resolution, search grounding.
Registry indexed
Generate and edit images using the Gemini API. Text-to-image, image editing, multi-turn iteration, 4K resolution, search grounding.
Generate and edit images using the Gemini API. Text-to-image, image editing, multi-turn iteration, 4K resolution, search grounding.
Source documentation, not instructions for this website. Review permissions before running any commands.
Generate and edit images via Gemini's native image generation API using curl.
| Model | ID | Best for |
|---|---|---|
| Nano Banana | gemini-2.5-flash-image | Fast, high-volume, low-latency |
| Nano Banana Pro | gemini-3-pro-image-preview | Pro asset production, complex prompts, accurate text rendering, 4K |
Default to gemini-2.5-flash-image unless the user asks for high quality, 4K, search grounding, or text-heavy images.
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "YOUR PROMPT HERE"}]}]
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
Read the output image file to show it to the user.
Encode an existing image as base64 and send it alongside a text prompt:
BASE64_IMG=$(base64 -i input.png)
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d "{
\"contents\": [{
\"parts\": [
{\"text\": \"YOUR EDIT PROMPT HERE\"},
{\"inline_data\": {\"mime_type\": \"image/png\", \"data\": \"$BASE64_IMG\"}}
]
}]
}" | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
When using gemini-3-pro-image-preview, you can set aspect ratio and resolution:
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "YOUR PROMPT HERE"}]}],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "2K"
}
}
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9
1K (default), 2K, 4K — must be uppercase K.
Generate images based on real-time info (weather, news, etc.):
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "YOUR PROMPT HERE"}]}],
"tools": [{"google_search": {}}],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"]
}
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
The API returns JSON with parts that can contain text and/or image data. Extract text and image separately:
# save full response
RESPONSE=$(curl -s -X POST ... )
# extract text (if any)
echo "$RESPONSE" | jq -r '.candidates[0].content.parts[] | select(.text) | .text'
# extract and save image
echo "$RESPONSE" | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
inlineData, check for error messages in the JSONname: image-gen
description: "Generate and edit images using the Gemini API. Text-to-image, image editing, multi-turn iteration, 4K resolution, search grounding."
metadata:
{ "requires": { "bins": ["curl", "jq"], "env": ["GEMINI_API_KEY"] } }---
name: image-gen
description: "Generate and edit images using the Gemini API. Text-to-image, image editing, multi-turn iteration, 4K resolution, search grounding."
metadata:
{ "requires": { "bins": ["curl", "jq"], "env": ["GEMINI_API_KEY"] } }
---
# Image Generation Skill
Generate and edit images via Gemini's native image generation API using `curl`.
## Models
| Model | ID | Best for |
|-------|----|----------|
| Nano Banana | `gemini-2.5-flash-image` | Fast, high-volume, low-latency |
| Nano Banana Pro | `gemini-3-pro-image-preview` | Pro asset production, complex prompts, accurate text rendering, 4K |
Default to `gemini-2.5-flash-image` unless the user asks for high quality, 4K, search grounding, or text-heavy images.
## Text-to-Image
```bash
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "YOUR PROMPT HERE"}]}]
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
```
Read the output image file to show it to the user.
## Image Editing (image + text → image)
Encode an existing image as base64 and send it alongside a text prompt:
```bash
BASE64_IMG=$(base64 -i input.png)
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-image:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d "{
\"contents\": [{
\"parts\": [
{\"text\": \"YOUR EDIT PROMPT HERE\"},
{\"inline_data\": {\"mime_type\": \"image/png\", \"data\": \"$BASE64_IMG\"}}
]
}]
}" | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
```
## Pro Model Options
When using `gemini-3-pro-image-preview`, you can set aspect ratio and resolution:
```bash
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "YOUR PROMPT HERE"}]}],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "2K"
}
}
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
```
### Aspect Ratios
`1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`, `21:9`
### Resolutions (Pro only)
`1K` (default), `2K`, `4K` — must be uppercase K.
## Search Grounding (Pro only)
Generate images based on real-time info (weather, news, etc.):
```bash
curl -s -X POST \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "YOUR PROMPT HERE"}]}],
"tools": [{"google_search": {}}],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"]
}
}' | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
```
## Handling Responses
The API returns JSON with parts that can contain text and/or image data. Extract text and image separately:
```bash
# save full response
RESPONSE=$(curl -s -X POST ... )
# extract text (if any)
echo "$RESPONSE" | jq -r '.candidates[0].content.parts[] | select(.text) | .text'
# extract and save image
echo "$RESPONSE" | jq -r '.candidates[0].content.parts[] | select(.inlineData) | .inlineData.data' | base64 -D > output.png
```
## Workflow
1. Understand what the user wants to generate or edit
2. Pick the right model (flash for speed, pro for quality/text/4K)
3. Write a detailed, descriptive prompt — more detail = better results
4. Run the curl command, save the image
5. Read the image file to display it inline
6. If the user wants edits, use the image editing flow with the previous output as input
## Tips
- Prompts should be descriptive and specific — style, composition, lighting, mood
- For image editing, describe what to change, not what to keep
- Pro model has a "thinking" mode — may take longer but produces better results
- All generated images include a SynthID watermark
- Pro supports up to 14 reference images in a single request (up to 6 objects + 5 humans)
- If the response has no `inlineData`, check for error messages in the JSON
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
70/100
Strong
Trust
57/100
Do not auto-install
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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"skill": {
"slug": "suitedaces-image-gen",
"name": "image-gen",
"description": "Generate and edit images using the Gemini API. Text-to-image, image editing, multi-turn iteration, 4K resolution, search grounding.",
"category": "research",
"url": "https://www.openagentskill.com/skills/suitedaces-image-gen",
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},
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"license": "MIT",
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"The base64 decode flag is platform-specific: macOS uses -D, Linux uses -d. The skill uses -D, which will fail on Linux systems.",
"Financial research output is not financial advice; require human review before any live investment decision.",
"Quality score needs review",
"Permission surface needs review: secrets or environment access, shell or command execution",
"Stars/forks activity: 243 stars, 34 forks; issue activity unavailable in current metadata",
"Dependency/runtime risk: command execution surface, credential or environment access",
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"No explicit error handling for API failures (e.g., rate limits, invalid prompts, missing API key). The skill assumes successful responses and does not guide the agent on how to detect or recover from errors.",
"Financial research output is not financial advice; require human review before any live investment decision.",
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}Listing source
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Audit
75/100
Needs review
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.