Back to skills
SKILL.md
Process Real Estate Photo
ASecurityEnhance and standardize a property listing photo with auto-contrast, sharpening, and consistent sizing.
- 3 stars
- 0 votes
- 0 copies
- 1 view
- Added September 10, 2026
Works with
Security analysis
100/100npx -y skills add iterationlayer/skills --skill process-real-estate-photo --agent claude-codeAre you the author of Process Real Estate Photo?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/iterationlayer-process-real-estate-photo)---
name: process-real-estate-photo
description: Enhance and standardize a property listing photo with auto-contrast, sharpening, and consistent sizing.
---
# Process Real Estate Photo
Real estate agencies and property platforms use this recipe to standardize a listing photo. Upload a property photo and apply auto-contrast, sharpening, and resize operations — ready for an MLS listing with consistent quality.
## APIs Used
Image Transformation (0.5 credits/request)
## Prerequisites
You need an Iteration Layer API key. Get one at [platform.iterationlayer.com](https://platform.iterationlayer.com) during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the [Iteration Layer Integration Guide](https://iterationlayer.com/SKILL.md).
## Implementation
```bash
curl -X POST https://api.iterationlayer.com/image-transformation/v1/transform \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"file": {
"type": "url",
"name": "property-photo.jpg",
"url": "https://example.com/property-photo.jpg"
},
"operations": [
{
"type": "resize",
"width_in_px": 1920,
"height_in_px": 1080,
"fit": "cover"
},
{
"type": "auto_contrast"
},
{
"type": "sharpen",
"sigma": 1.5
},
{
"type": "convert",
"format": "jpeg",
"quality": 90
}
]
}'
```
```typescript
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const result = await client.transformImage({
file: {
type: "url",
name: "property-photo.jpg",
url: "https://example.com/property-photo.jpg",
},
operations: [
{
type: "resize",
width_in_px: 1920,
height_in_px: 1080,
fit: "cover",
},
{ type: "auto_contrast" },
{
type: "sharpen",
sigma: 1.5,
},
{
type: "convert",
format: "jpeg",
quality: 90,
},
],
});
```
```python
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
result = client.transform_image(
file={
"type": "url",
"name": "property-photo.jpg",
"url": "https://example.com/property-photo.jpg",
},
operations=[
{
"type": "resize",
"width_in_px": 1920,
"height_in_px": 1080,
"fit": "cover",
},
{"type": "auto_contrast"},
{
"type": "sharpen",
"sigma": 1.5,
},
{
"type": "convert",
"format": "jpeg",
"quality": 90,
},
],
)
```
```go
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.TransformImage(il.TransformImageRequest{
File: il.FileInput{Type: "url", Name: "property-photo.jpg", Url: "https://example.com/property-photo.jpg"},
Operations: []il.TransformOperation{
il.NewResizeOperation(1920, 1080, "cover"),
{Type: "auto_contrast"},
il.NewSharpenOperation(1.5),
il.NewConvertOperation("jpeg"),
},
})
if err != nil {
panic(err)
}
}
```
```n8n
{
"name": "Process Real Estate Photo",
"nodes": [
{
"parameters": {
"content": "## Process Real Estate Photo\n\nReal estate agencies and property platforms use this recipe to standardize a listing photo. Upload a property photo and apply auto-contrast, sharpening, and resize operations \u2014 ready for an MLS listing with consistent quality.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
200,
40
],
"id": "e100cf30-cc6a-44ec-a68a-8d1d99f15e34",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Transform Image\nResource: **Image Transformation**\n\nConfigure the Image Transformation parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
475,
100
],
"id": "52cd56ec-13de-4bd9-9fcb-354172459662",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
250,
300
],
"id": "b8c9d0e1-f2a3-4b4c-5d6e-8f9a0b1c2d3e",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "imageTransformation",
"fileInputMode": "url",
"fileName": "property-photo.jpg",
"fileUrl": "https://example.com/property-photo.jpg",
"operations": {
"operationValues": [
{
"operationType": "resize",
"widthInPx": 1920,
"heightInPx": 1080,
"fit": "cover"
},
{
"operationType": "auto_contrast"
},
{
"operationType": "sharpen",
"sigma": 1.5
},
{
"operationType": "convert",
"convertFormat": "jpeg",
"quality": 90
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [
500,
300
],
"id": "e1f2a3b4-c5d6-4e7f-8a9b-0c1d2e3f4a5b",
"name": "Transform Image",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Transform Image",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
```
```prompt
Process the real estate photo at [file URL] for a property listing. Use the transform_image tool with a resize operation to 1920x1080 pixels (fit: cover), an auto_contrast operation, a sharpen operation, and a convert operation to JPEG at quality 90.
```
### Response
```json
{
"success": true,
"data": {
"buffer": "iVBORw0KGgoAAAANSUhEUgAA...",
"mime_type": "image/jpeg"
}
}
```
## Links
- [Integration guide](https://iterationlayer.com/SKILL.md)
- [Full documentation](https://iterationlayer.com/docs)
- [OpenAPI spec](https://api.iterationlayer.com/openapi.json)
- [Browse all recipes](https://iterationlayer.com/recipes)
Attribution
Comments
Loading comments…