Skills extract-rental-applications-to-spreadsheet
Extract applicant details from rental application PDFs and generate a side-by-side XLSX for comparing income, employment, and move-in dates.
install
source · Clone the upstream repo
git clone https://github.com/iterationlayer/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/iterationlayer/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/extract-rental-applications-to-spreadsheet" ~/.claude/skills/iterationlayer-skills-extract-rental-applications-to-spreadsheet && rm -rf "$T"
manifest:
skills/extract-rental-applications-to-spreadsheet/SKILL.mdsource content
Extract Rental Applications to Spreadsheet
Property managers and landlords use this recipe to compare rental applicants side by side without manually reading each PDF. Pass multiple application files, extract the key fields, and get a clean XLSX ready for shortlisting before scheduling viewings.
APIs Used
Document Extraction (1 credit per page), Sheet Generation (2 credits/request)
Prerequisites
You need an Iteration Layer API key. Get one at platform.iterationlayer.com — free trial credits included, no credit card required.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
Implementation
# Step 1: Extract data from all rental applications EXTRACTION=$(curl -s -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": "application-chen.pdf", "url": "https://example.com/applications/application-chen.pdf" }, { "type": "url", "name": "application-okafor.pdf", "url": "https://example.com/applications/application-okafor.pdf" }, { "type": "url", "name": "application-petrov.pdf", "url": "https://example.com/applications/application-petrov.pdf" } ], "schema": { "fields": [ { "name": "applications", "type": "ARRAY", "description": "One entry per rental application", "fields": [ { "name": "applicant_name", "type": "TEXT", "description": "Full name of applicant" }, { "name": "email", "type": "EMAIL", "description": "Applicant email address" }, { "name": "monthly_income", "type": "CURRENCY_AMOUNT", "description": "Stated monthly income" }, { "name": "currency", "type": "CURRENCY_CODE", "description": "Income currency" }, { "name": "employer", "type": "TEXT", "description": "Current employer name" }, { "name": "employment_status", "type": "ENUM", "description": "Employment status", "values": ["Full-time", "Part-time", "Self-employed", "Unemployed", "Retired"] }, { "name": "desired_move_in_date", "type": "DATE", "description": "Requested move-in date" }, { "name": "has_pets", "type": "BOOLEAN", "description": "Whether the applicant has pets" } ] } } ] } }') # Step 2: Generate the applicant comparison spreadsheet curl -X POST https://api.iterationlayer.com/sheet-generation/v1/generate \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "format": "xlsx", "styles": { "header": { "font_family": "Helvetica", "font_size_in_pt": 11, "is_bold": true, "background_color": "#4A5568", "font_color": "#FFFFFF" }, "body": { "font_family": "Helvetica", "font_size_in_pt": 11, "font_color": "#1A1A1A" } }, "sheets": [ { "name": "Rental Applications — 14 Birchwood Lane", "columns": [ { "name": "Applicant", "width": 22 }, { "name": "Email", "width": 28 }, { "name": "Employment", "width": 16 }, { "name": "Employer", "width": 22 }, { "name": "Monthly Income", "width": 16 }, { "name": "Currency", "width": 10 }, { "name": "Move-in Date", "width": 14 }, { "name": "Pets", "width": 8 } ], "rows": [ [ { "value": "Wei Chen" }, { "value": "wei.chen@gmail.com" }, { "value": "Full-time" }, { "value": "Meridian Software Ltd." }, { "value": 6800, "format": "currency" }, { "value": "USD" }, { "value": "2026-05-01", "format": "date" }, { "value": "No" } ], [ { "value": "Amara Okafor" }, { "value": "amara.okafor@consultio.co" }, { "value": "Self-employed" }, { "value": "Okafor Consulting" }, { "value": 9200, "format": "currency" }, { "value": "USD" }, { "value": "2026-04-15", "format": "date" }, { "value": "Yes" } ], [ { "value": "Dmitri Petrov" }, { "value": "d.petrov@healthcarenet.org" }, { "value": "Full-time" }, { "value": "Riverside General Hospital" }, { "value": 5400, "format": "currency" }, { "value": "USD" }, { "value": "2026-05-15", "format": "date" }, { "value": "No" } ] ] } ] }'
import { IterationLayer } from "iterationlayer"; const client = new IterationLayer({ apiKey: "YOUR_API_KEY" }); // Step 1: Extract data from all rental applications const extraction = await client.extract({ files: [ { type: "url", name: "application-chen.pdf", url: "https://example.com/applications/application-chen.pdf", }, { type: "url", name: "application-okafor.pdf", url: "https://example.com/applications/application-okafor.pdf", }, { type: "url", name: "application-petrov.pdf", url: "https://example.com/applications/application-petrov.pdf", }, ], schema: { fields: [ { name: "applications", type: "ARRAY", description: "One entry per rental application", fields: [ { name: "applicant_name", type: "TEXT", description: "Full name of applicant", }, { name: "email", type: "EMAIL", description: "Applicant email address", }, { name: "monthly_income", type: "CURRENCY_AMOUNT", description: "Stated monthly income", }, { name: "currency", type: "CURRENCY_CODE", description: "Income currency", }, { name: "employer", type: "TEXT", description: "Current employer name", }, { name: "employment_status", type: "ENUM", description: "Employment status", values: [ "Full-time", "Part-time", "Self-employed", "Unemployed", "Retired", ], }, { name: "desired_move_in_date", type: "DATE", description: "Requested move-in date", }, { name: "has_pets", type: "BOOLEAN", description: "Whether the applicant has pets", }, ], }, ], }, }); const applications = extraction["applications"].value as Array< Record<string, { value: unknown }> >; // Step 2: Generate the applicant comparison spreadsheet const sheet = await client.generateSheet({ format: "xlsx", styles: { header: { font_family: "Helvetica", font_size_in_pt: 11, is_bold: true, background_color: "#4A5568", font_color: "#FFFFFF", }, body: { font_family: "Helvetica", font_size_in_pt: 11, font_color: "#1A1A1A", }, }, sheets: [ { name: "Rental Applications — 14 Birchwood Lane", columns: [ { name: "Applicant", width: 22 }, { name: "Email", width: 28 }, { name: "Employment", width: 16 }, { name: "Employer", width: 22 }, { name: "Monthly Income", width: 16 }, { name: "Currency", width: 10 }, { name: "Move-in Date", width: 14 }, { name: "Pets", width: 8 }, ], rows: applications.map((application) => [ { value: application["applicant_name"].value }, { value: application["email"].value }, { value: application["employment_status"].value }, { value: application["employer"].value }, { value: (application["monthly_income"].value as { amount: string }) .amount, format: "currency", }, { value: application["currency"].value }, { value: application["desired_move_in_date"].value, format: "date" }, { value: application["has_pets"].value ? "Yes" : "No" }, ]), }, ], });
from iterationlayer import IterationLayer client = IterationLayer(api_key="YOUR_API_KEY") # Step 1: Extract data from all rental applications extraction = client.extract( files=[ { "type": "url", "name": "application-chen.pdf", "url": "https://example.com/applications/application-chen.pdf", }, { "type": "url", "name": "application-okafor.pdf", "url": "https://example.com/applications/application-okafor.pdf", }, { "type": "url", "name": "application-petrov.pdf", "url": "https://example.com/applications/application-petrov.pdf", }, ], schema={ "fields": [ { "name": "applications", "type": "ARRAY", "description": "One entry per rental application", "fields": [ {"name": "applicant_name", "type": "TEXT", "description": "Full name of applicant"}, {"name": "email", "type": "EMAIL", "description": "Applicant email address"}, {"name": "monthly_income", "type": "CURRENCY_AMOUNT", "description": "Stated monthly income"}, {"name": "currency", "type": "CURRENCY_CODE", "description": "Income currency"}, {"name": "employer", "type": "TEXT", "description": "Current employer name"}, { "name": "employment_status", "type": "ENUM", "description": "Employment status", "values": ["Full-time", "Part-time", "Self-employed", "Unemployed", "Retired"], }, {"name": "desired_move_in_date", "type": "DATE", "description": "Requested move-in date"}, {"name": "has_pets", "type": "BOOLEAN", "description": "Whether the applicant has pets"}, ] }, } ] }, ) applications = extraction["applications"]["value"] # Step 2: Generate the applicant comparison spreadsheet sheet = client.generate_sheet( format="xlsx", styles={ "header": { "font_family": "Helvetica", "font_size_in_pt": 11, "is_bold": True, "background_color": "#4A5568", "font_color": "#FFFFFF", }, "body": { "font_family": "Helvetica", "font_size_in_pt": 11, "font_color": "#1A1A1A", }, }, sheets=[ { "name": "Rental Applications — 14 Birchwood Lane", "columns": [ {"name": "Applicant", "width": 22}, {"name": "Email", "width": 28}, {"name": "Employment", "width": 16}, {"name": "Employer", "width": 22}, {"name": "Monthly Income", "width": 16}, {"name": "Currency", "width": 10}, {"name": "Move-in Date", "width": 14}, {"name": "Pets", "width": 8}, ], "rows": [ [ {"value": app["applicant_name"]["value"]}, {"value": app["email"]["value"]}, {"value": app["employment_status"]["value"]}, {"value": app["employer"]["value"]}, {"value": app["monthly_income"]["value"]["amount"], "format": "currency"}, {"value": app["currency"]["value"]}, {"value": app["desired_move_in_date"]["value"], "format": "date"}, {"value": "Yes" if app["has_pets"]["value"] else "No"}, ] for app in applications ], } ], )
package main import ( "fmt" il "github.com/iterationlayer/sdk-go" ) func main() { client := il.NewClient("YOUR_API_KEY") // Step 1: Extract data from all rental applications extraction, err := client.Extract(il.ExtractRequest{ Files: []il.FileInput{ il.NewFileFromURL( "application-chen.pdf", "https://example.com/applications/application-chen.pdf", ), il.NewFileFromURL( "application-okafor.pdf", "https://example.com/applications/application-okafor.pdf", ), il.NewFileFromURL( "application-petrov.pdf", "https://example.com/applications/application-petrov.pdf", ), }, Schema: il.ExtractionSchema{ "applications": il.NewArrayFieldConfig( "applications", "One entry per rental application", []il.FieldConfig{ il.NewTextFieldConfig("applicant_name", "Full name of applicant"), il.NewEmailFieldConfig("email", "Applicant email address"), il.NewCurrencyAmountFieldConfig("monthly_income", "Stated monthly income"), il.NewCurrencyCodeFieldConfig("currency", "Income currency"), il.NewTextFieldConfig("employer", "Current employer name"), il.NewEnumFieldConfig("employment_status", "Employment status", []string{ "Full-time", "Part-time", "Self-employed", "Unemployed", "Retired", }), il.NewDateFieldConfig("desired_move_in_date", "Requested move-in date"), il.NewBooleanFieldConfig("has_pets", "Whether the applicant has pets"), }, ), }, }) if err != nil { panic(err) } rawApplications, _ := (*extraction)["applications"].Value.([]interface{}) sheetRows := make([]il.SheetRow, 0, len(rawApplications)) for _, rawApplication := range rawApplications { application, _ := rawApplication.(map[string]interface{}) getSV := func(key string) string { if field, ok := application[key].(map[string]interface{}); ok { return fmt.Sprintf("%v", field["value"]) } return "" } monthlyIncome := "" if field, ok := application["monthly_income"].(map[string]interface{}); ok { if amountMap, ok := field["value"].(map[string]interface{}); ok { monthlyIncome = fmt.Sprintf("%v", amountMap["amount"]) } } hasPets := "No" if field, ok := application["has_pets"].(map[string]interface{}); ok { if field["value"] == true { hasPets = "Yes" } } sheetRows = append(sheetRows, il.SheetRow{ {Value: getSV("applicant_name")}, {Value: getSV("email")}, {Value: getSV("employment_status")}, {Value: getSV("employer")}, {Value: monthlyIncome, Format: "currency"}, {Value: getSV("currency")}, {Value: getSV("desired_move_in_date"), Format: "date"}, {Value: hasPets}, }) } // Step 2: Generate the applicant comparison spreadsheet result, err := client.GenerateSheet(il.GenerateSheetRequest{ Format: "xlsx", Styles: &il.SheetStyles{ Header: &il.CellStyle{ FontFamily: "Helvetica", FontSizeInPt: 11, IsBold: true, BackgroundColor: "#4A5568", FontColor: "#FFFFFF", }, Body: &il.CellStyle{ FontFamily: "Helvetica", FontSizeInPt: 11, FontColor: "#1A1A1A", }, }, Sheets: []il.Sheet{ { Name: "Rental Applications — 14 Birchwood Lane", Columns: []il.SheetColumn{ {Name: "Applicant", Width: 22}, {Name: "Email", Width: 28}, {Name: "Employment", Width: 16}, {Name: "Employer", Width: 22}, {Name: "Monthly Income", Width: 16}, {Name: "Currency", Width: 10}, {Name: "Move-in Date", Width: 14}, {Name: "Pets", Width: 8}, }, Rows: sheetRows, }, }, }) if err != nil { panic(err) } _ = result }
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Extract rental application data from the files at [file URL 1], [file URL 2], and [file URL 3], then generate an applicant comparison spreadsheet. Use the extract_document tool with these fields: - applications (ARRAY): One entry per rental application, each with: - applicant_name (TEXT): Full name of applicant - email (EMAIL): Applicant email address - monthly_income (CURRENCY_AMOUNT): Stated monthly income - currency (CURRENCY_CODE): Income currency - employer (TEXT): Current employer name - employment_status (ENUM): Employment status (Full-time, Part-time, Self-employed, Unemployed, Retired) - desired_move_in_date (DATE): Requested move-in date - has_pets (BOOLEAN): Whether the applicant has pets Then use the generate_sheet tool to create an XLSX applicant comparison spreadsheet with the extracted rows.
Response
{ "success": true, "data": { "buffer": "UEsDBBQAAAAIAA...", "mime_type": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" } }