Skip to content
cccskills
FreePublished on GitHub

extract-property-appraisal

Extract appraised value, property details, and comparable sales from a property appraisal report into structured JSON.

The English summary is being prepared. Showing the original description.

iterationlayer/skills
Works withn8n
See how to install

Files included (1)

  • SKILL.md18.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Extract Property Appraisal

Mortgage lenders, real estate platforms, and appraisal management companies use this recipe to digitize appraisal reports. Upload an appraisal PDF and receive structured JSON with the appraised value, property details, and comparable sales — ready to feed into your loan origination system or valuation database.

APIs Used

Document Extraction (1 credit per page)

Prerequisites

You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.

For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.

Implementation

curl -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "files": [
      {
        "type": "url",
        "name": "appraisal.pdf",
        "url": "https://example.com/appraisals/2026-0042.pdf"
      }
    ],
    "schema": {
      "fields": [
        {
          "name": "subject_address",
          "type": "ADDRESS",
          "description": "Address of the subject property being appraised"
        },
        {
          "name": "appraised_value",
          "type": "CURRENCY_AMOUNT",
          "description": "Final appraised market value of the property"
        },
        {
          "name": "effective_date",
          "type": "DATE",
          "description": "Date of the appraisal"
        },
        {
          "name": "property_type",
          "type": "ENUM",
          "description": "Type of property",
          "values": ["single_family", "condo", "multi_family", "commercial", "land"],
          "max_selected": 1
        },
        {
          "name": "gross_living_area_sqft",
          "type": "INTEGER",
          "description": "Gross living area in square feet"
        },
        {
          "name": "year_built",
          "type": "INTEGER",
          "description": "Year the property was built"
        },
        {
          "name": "bedrooms",
          "type": "INTEGER",
          "description": "Number of bedrooms"
        },
        {
          "name": "bathrooms",
          "type": "DECIMAL",
          "description": "Number of bathrooms",
          "decimal_points": 1
        },
        {
          "name": "comparable_sales",
          "type": "ARRAY",
          "description": "Comparable sales used in the appraisal",
          "fields": [
            {
              "name": "address",
              "type": "ADDRESS",
              "description": "Address of the comparable property"
            },
            {
              "name": "sale_price",
              "type": "CURRENCY_AMOUNT",
              "description": "Sale price of the comparable"
            },
            {
              "name": "sale_date",
              "type": "DATE",
              "description": "Date of the comparable sale"
            },
            {
              "name": "gross_living_area_sqft",
              "type": "INTEGER",
              "description": "Gross living area of the comparable in square feet"
            }
          ]
        }
      ]
    }
  }'

import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });

const result = await client.extractDocument({
  files: [
    {
      type: "url",
      name: "appraisal.pdf",
      url: "https://example.com/appraisals/2026-0042.pdf",
    },
  ],
  schema: {
    fields: [
      {
        name: "subject_address",
        type: "ADDRESS",
        description: "Address of the subject property being appraised",
      },
      {
        name: "appraised_value",
        type: "CURRENCY_AMOUNT",
        description: "Final appraised market value of the property",
      },
      {
        name: "effective_date",
        type: "DATE",
        description: "Date of the appraisal",
      },
      {
        name: "property_type",
        type: "ENUM",
        description: "Type of property",
        values: [
          "single_family",
          "condo",
          "multi_family",
          "commercial",
          "land",
        ],
        max_selected: 1,
      },
      {
        name: "gross_living_area_sqft",
        type: "INTEGER",
        description: "Gross living area in square feet",
      },
      {
        name: "year_built",
        type: "INTEGER",
        description: "Year the property was built",
      },
      {
        name: "bedrooms",
        type: "INTEGER",
        description: "Number of bedrooms",
      },
      {
        name: "bathrooms",
        type: "DECIMAL",
        description: "Number of bathrooms",
        decimal_points: 1,
      },
      {
        name: "comparable_sales",
        type: "ARRAY",
        description: "Comparable sales used in the appraisal",
        fields: [
          {
            name: "address",
            type: "ADDRESS",
            description: "Address of the comparable property",
          },
          {
            name: "sale_price",
            type: "CURRENCY_AMOUNT",
            description: "Sale price of the comparable",
          },
          {
            name: "sale_date",
            type: "DATE",
            description: "Date of the comparable sale",
          },
          {
            name: "gross_living_area_sqft",
            type: "INTEGER",
            description: "Gross living area of the comparable in square feet",
          },
        ],
      },
    ],
  },
});

from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")

result = client.extract_document(
    files=[
        {
            "type": "url",
            "name": "appraisal.pdf",
            "url": "https://example.com/appraisals/2026-0042.pdf",
        }
    ],
    schema={
        "fields": [
            {
                "name": "subject_address",
                "type": "ADDRESS",
                "description": "Address of the subject property being appraised",
            },
            {
                "name": "appraised_value",
                "type": "CURRENCY_AMOUNT",
                "description": "Final appraised market value of the property",
            },
            {
                "name": "effective_date",
                "type": "DATE",
                "description": "Date of the appraisal",
            },
            {
                "name": "property_type",
                "type": "ENUM",
                "description": "Type of property",
                "values": ["single_family", "condo", "multi_family", "commercial", "land"],
                "max_selected": 1,
            },
            {
                "name": "gross_living_area_sqft",
                "type": "INTEGER",
                "description": "Gross living area in square feet",
            },
            {
                "name": "year_built",
                "type": "INTEGER",
                "description": "Year the property was built",
            },
            {
                "name": "bedrooms",
                "type": "INTEGER",
                "description": "Number of bedrooms",
            },
            {
                "name": "bathrooms",
                "type": "DECIMAL",
                "description": "Number of bathrooms",
                "decimal_points": 1,
            },
            {
                "name": "comparable_sales",
                "type": "ARRAY",
                "description": "Comparable sales used in the appraisal",
                "fields": [
                    {
                        "name": "address",
                        "type": "ADDRESS",
                        "description": "Address of the comparable property",
                    },
                    {
                        "name": "sale_price",
                        "type": "CURRENCY_AMOUNT",
                        "description": "Sale price of the comparable",
                    },
                    {
                        "name": "sale_date",
                        "type": "DATE",
                        "description": "Date of the comparable sale",
                    },
                    {
                        "name": "gross_living_area_sqft",
                        "type": "INTEGER",
                        "description": "Gross living area of the comparable in square feet",
                    },
                ],
            },
        ]
    },
)

package main

import il "github.com/iterationlayer/sdk-go"

func main() {
	client := il.NewClient("YOUR_API_KEY")

	result, err := client.ExtractDocument(il.ExtractDocumentRequest{
		Files: []il.FileInput{
			il.FileInput{
				Type: "url",
				Name: "appraisal.pdf",
				Url: "https://example.com/appraisals/2026-0042.pdf",
			},
		},
		Schema: il.ExtractionSchema{
			Fields: []any{
				il.AddressFieldConfig{
					Name: "subject_address",
					Type: "ADDRESS",
					Description: "Address of the subject property being appraised",
				},
				il.CurrencyAmountFieldConfig{
					Name: "appraised_value",
					Type: "CURRENCY_AMOUNT",
					Description: "Final appraised market value of the property",
				},
				il.DateFieldConfig{
					Name: "effective_date",
					Type: "DATE",
					Description: "Date of the appraisal",
				},
				il.EnumFieldConfig{
					Name: "property_type",
					Type: "ENUM",
					Description: "Type of property",
					Values: []string{"single_family", "condo", "multi_family", "commercial", "land"},
					MaxSelected: 1,
				},
				il.IntegerFieldConfig{
					Name: "gross_living_area_sqft",
					Type: "INTEGER",
					Description: "Gross living area in square feet",
				},
				il.IntegerFieldConfig{
					Name: "year_built",
					Type: "INTEGER",
					Description: "Year the property was built",
				},
				il.IntegerFieldConfig{
					Name: "bedrooms",
					Type: "INTEGER",
					Description: "Number of bedrooms",
				},
				il.DecimalFieldConfig{
					Name: "bathrooms",
					Type: "DECIMAL",
					Description: "Number of bathrooms",
				},
				il.ArrayFieldConfig{
					Name: "comparable_sales",
					Type: "ARRAY",
					Description: "Comparable sales used in the appraisal",
					Fields: []any{
						il.AddressFieldConfig{
							Name: "address",
							Type: "ADDRESS",
							Description: "Address of the comparable property",
						},
						il.CurrencyAmountFieldConfig{
							Name: "sale_price",
							Type: "CURRENCY_AMOUNT",
							Description: "Sale price of the comparable",
						},
						il.DateFieldConfig{
							Name: "sale_date",
							Type: "DATE",
							Description: "Date of the comparable sale",
						},
						il.IntegerFieldConfig{
							Name: "gross_living_area_sqft",
							Type: "INTEGER",
							Description: "Gross living area of the comparable in square feet",
						},
					},
				},
			},
		},
	})
	if err != nil {
		panic(err)
	}

	_ = result
}

{
  "name": "Extract Property Appraisal",
  "nodes": [
    {
      "parameters": {
        "content": "## Extract Property Appraisal\n\nMortgage lenders, real estate platforms, and appraisal management companies use this recipe to digitize appraisal reports. Upload an appraisal PDF and receive structured JSON with the appraised value, property details, and comparable sales \u2014 ready to feed into your loan origination system or valuation database.\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": "18c9143e-4361-4a50-952b-dda14da53749",
      "name": "Overview"
    },
    {
      "parameters": {
        "content": "### Step 1: Extract Data\nResource: **Document Extraction**\n\nConfigure the Document Extraction parameters below, then connect your credentials.",
        "height": 160,
        "width": 300,
        "color": 6
      },
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        475,
        100
      ],
      "id": "163e4817-e901-4199-b290-9f0674a62a3d",
      "name": "Step 1 Note"
    },
    {
      "parameters": {},
      "type": "n8n-nodes-base.manualTrigger",
      "typeVersion": 1,
      "position": [
        250,
        300
      ],
      "id": "e7f8a9b0-c1d2-3456-efab-567890123efa",
      "name": "Manual Trigger"
    },
    {
      "parameters": {
        "resource": "documentExtraction",
        "schemaInputMode": "rawJson",
        "schemaJson": "{\"fields\":[{\"name\":\"subject_address\",\"type\":\"ADDRESS\",\"description\":\"Address of the subject property being appraised\"},{\"name\":\"appraised_value\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Final appraised market value of the property\"},{\"name\":\"effective_date\",\"type\":\"DATE\",\"description\":\"Date of the appraisal\"},{\"name\":\"property_type\",\"type\":\"ENUM\",\"description\":\"Type of property\",\"values\":[\"single_family\",\"condo\",\"multi_family\",\"commercial\",\"land\"],\"max_selected\":1},{\"name\":\"gross_living_area_sqft\",\"type\":\"INTEGER\",\"description\":\"Gross living area in square feet\"},{\"name\":\"year_built\",\"type\":\"INTEGER\",\"description\":\"Year the property was built\"},{\"name\":\"bedrooms\",\"type\":\"INTEGER\",\"description\":\"Number of bedrooms\"},{\"name\":\"bathrooms\",\"type\":\"DECIMAL\",\"description\":\"Number of bathrooms\",\"decimal_points\":1},{\"name\":\"comparable_sales\",\"type\":\"ARRAY\",\"description\":\"Comparable sales used in the appraisal\",\"fields\":[{\"name\":\"address\",\"type\":\"ADDRESS\",\"description\":\"Address of the comparable property\"},{\"name\":\"sale_price\",\"type\":\"CURRENCY_AMOUNT\",\"description\":\"Sale price of the comparable\"},{\"name\":\"sale_date\",\"type\":\"DATE\",\"description\":\"Date of the comparable sale\"},{\"name\":\"gross_living_area_sqft\",\"type\":\"INTEGER\",\"description\":\"Gross living area of the comparable in square feet\"}]}]}",
        "files": {
          "fileValues": [
            {
              "fileInputMode": "url",
              "fileName": "appraisal.pdf",
              "fileUrl": "https://example.com/appraisals/2026-0042.pdf"
            }
          ]
        }
      },
      "type": "n8n-nodes-iterationlayer.iterationLayer",
      "typeVersion": 1,
      "position": [
        500,
        300
      ],
      "id": "f8a9b0c1-d2e3-4567-fabc-678901234fab",
      "name": "Extract Data",
      "credentials": {
        "iterationLayerApi": {
          "id": "1",
          "name": "Iteration Layer API"
        }
      }
    }
  ],
  "connections": {
    "Manual Trigger": {
      "main": [
        [
          {
            "node": "Extract Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}

Extract property appraisal data from the file at [file URL]. Use the extract_document tool with these fields:

- subject_address (ADDRESS): Address of the subject property being appraised
- appraised_value (CURRENCY_AMOUNT): Final appraised market value
- effective_date (DATE): Date of the appraisal
- property_type (ENUM): Type of property (single_family, condo, multi_family, commercial, land)
- gross_living_area_sqft (INTEGER): Gross living area in square feet
- year_built (INTEGER): Year the property was built
- bedrooms (INTEGER): Number of bedrooms
- bathrooms (DECIMAL): Number of bathrooms
- comparable_sales (ARRAY): Each with address (ADDRESS), sale_price (CURRENCY_AMOUNT), sale_date (DATE), gross_living_area_sqft (INTEGER)

Response

{
  "success": true,
  "data": {
    "subject_address": {
      "value": {
        "street": "412 Ridgewood Lane",
        "city": "Denver",
        "region": "CO",
        "postal_code": "80203",
        "country": "US"
      },
      "confidence": 0.98,
      "citations": ["412 Ridgewood Lane, Denver, CO 80203"]
    },
    "appraised_value": {
      "value": { "amount": "685000.00", "currency": "USD" },
      "confidence": 0.97,
      "citations": ["Market Value Opinion: $685,000"]
    },
    "effective_date": {
      "value": "2026-03-15",
      "confidence": 0.99,
      "citations": ["Effective Date: March 15, 2026"]
    },
    "property_type": {
      "value": ["single_family"],
      "confidence": 0.99,
      "citations": ["Single Family Residence"]
    },
    "gross_living_area_sqft": {
      "value": 2140,
      "confidence": 0.97,
      "citations": ["GLA: 2,140 sq ft"]
    },
    "year_built": {
      "value": 1998,
      "confidence": 0.99,
      "citations": ["Year Built: 1998"]
    },
    "bedrooms": {
      "value": 4,
      "confidence": 0.99,
      "citations": ["Bedrooms: 4"]
    },
    "bathrooms": {
      "value": 2.5,
      "confidence": 0.98,
      "citations": ["Bathrooms: 2.5"]
    },
    "comparable_sales": {
      "value": [
        {
          "address": {
            "value": {
              "street": "388 Ridgewood Lane",
              "city": "Denver",
              "region": "CO",
              "postal_code": "80203",
              "country": "US"
            },
            "confidence": 0.96,
            "citations": ["388 Ridgewood Lane, Denver, CO 80203"]
          },
          "sale_price": {
            "value": { "amount": "672000.00", "currency": "USD" },
            "confidence": 0.97,
            "citations": ["Sale Price: $672,000"]
          },
          "sale_date": {
            "value": "2026-01-20",
            "confidence": 0.98,
            "citations": ["Date of Sale: 01/20/2026"]
          },
          "gross_living_area_sqft": {
            "value": 2090,
            "confidence": 0.96,
            "citations": ["GLA: 2,090"]
          }
        }
      ],
      "confidence": 0.96,
      "citations": []
    }
  }
}

Links

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

compress-image-for-email

Free

Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.

The English summary is being prepared. Showing the original description.

iterationlayer/skills4Updated Jun 9, 2026

compress-image-to-target-size

Free

Compress an image to fit within a specific file size in bytes using quality-first compression.

The English summary is being prepared. Showing the original description.

iterationlayer/skills4Updated Jun 9, 2026

convert-contract-to-markdown

Free

Convert a contract PDF to clean markdown for clause extraction or LLM analysis.

The English summary is being prepared. Showing the original description.

iterationlayer/skills4Updated Jun 9, 2026

convert-document-for-knowledge-base

Free

Convert external documents — specs, contracts, reports — to markdown for knowledge base ingestion.

The English summary is being prepared. Showing the original description.

iterationlayer/skills4Updated Jun 9, 2026

convert-document-for-rag-ingestion

Free

Convert a document to clean markdown suitable for chunking and embedding in a RAG pipeline.

The English summary is being prepared. Showing the original description.

iterationlayer/skills4Updated Jun 9, 2026

convert-image-format

Free

Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.

The English summary is being prepared. Showing the original description.

iterationlayer/skills4Updated Jun 9, 2026

See all skills by iterationlayer

Report a problem with this skill