무료GitHub에 공개

extract-w-4-data

Extract structured fields from w-4 documents.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills

연동 도구n8n

설치 방법 보기

포함된 파일(1)

SKILL.md13.2 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Extract W-4 Data

Tax and finance teams use this recipe to extract W-4 fields from official forms into structured JSON for review, routing, and downstream filing preparation.

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": "w-4.pdf",
      "url": "https://example.com/documents/w-4-sample.pdf"
    }
  ],
  "schema": {
    "fields": [
      {
        "name": "employee_name",
        "type": "TEXT",
        "description": "Employee full name"
      },
      {
        "name": "social_security_number",
        "type": "TEXT",
        "description": "Employee Social Security number"
      },
      {
        "name": "address",
        "type": "ADDRESS",
        "description": "Employee address"
      },
      {
        "name": "filing_status",
        "type": "TEXT",
        "description": "Selected filing status"
      },
      {
        "name": "dependents_amount",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 3 dependent and other credits amount"
      },
      {
        "name": "other_income",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(a) other income"
      },
      {
        "name": "deductions",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(b) deductions"
      },
      {
        "name": "extra_withholding",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(c) extra withholding"
      },
      {
        "name": "is_signed",
        "type": "BOOLEAN",
        "description": "Whether the employee signature is present"
      },
      {
        "name": "signature_date",
        "type": "DATE",
        "description": "Date signed"
      }
    ]
  }
}'

import { IterationLayer } from "iterationlayer";

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

const result = await client.extractDocument({
  "files": [
    {
      "type": "url",
      "name": "w-4.pdf",
      "url": "https://example.com/documents/w-4-sample.pdf"
    }
  ],
  "schema": {
    "fields": [
      {
        "name": "employee_name",
        "type": "TEXT",
        "description": "Employee full name"
      },
      {
        "name": "social_security_number",
        "type": "TEXT",
        "description": "Employee Social Security number"
      },
      {
        "name": "address",
        "type": "ADDRESS",
        "description": "Employee address"
      },
      {
        "name": "filing_status",
        "type": "TEXT",
        "description": "Selected filing status"
      },
      {
        "name": "dependents_amount",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 3 dependent and other credits amount"
      },
      {
        "name": "other_income",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(a) other income"
      },
      {
        "name": "deductions",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(b) deductions"
      },
      {
        "name": "extra_withholding",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(c) extra withholding"
      },
      {
        "name": "is_signed",
        "type": "BOOLEAN",
        "description": "Whether the employee signature is present"
      },
      {
        "name": "signature_date",
        "type": "DATE",
        "description": "Date signed"
      }
    ]
  }
});

from iterationlayer import IterationLayer

client = IterationLayer(api_key="YOUR_API_KEY")

result = client.extract_document(**{
  "files": [
    {
      "type": "url",
      "name": "w-4.pdf",
      "url": "https://example.com/documents/w-4-sample.pdf"
    }
  ],
  "schema": {
    "fields": [
      {
        "name": "employee_name",
        "type": "TEXT",
        "description": "Employee full name"
      },
      {
        "name": "social_security_number",
        "type": "TEXT",
        "description": "Employee Social Security number"
      },
      {
        "name": "address",
        "type": "ADDRESS",
        "description": "Employee address"
      },
      {
        "name": "filing_status",
        "type": "TEXT",
        "description": "Selected filing status"
      },
      {
        "name": "dependents_amount",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 3 dependent and other credits amount"
      },
      {
        "name": "other_income",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(a) other income"
      },
      {
        "name": "deductions",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(b) deductions"
      },
      {
        "name": "extra_withholding",
        "type": "CURRENCY_AMOUNT",
        "description": "Step 4(c) extra withholding"
      },
      {
        "name": "is_signed",
        "type": "BOOLEAN",
        "description": "Whether the employee signature is present"
      },
      {
        "name": "signature_date",
        "type": "DATE",
        "description": "Date signed"
      }
    ]
  }
})

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: "w-4.pdf",
				Url: "https://example.com/documents/w-4-sample.pdf",
			},
		},
		Schema: il.ExtractionSchema{
			Fields: []any{
				il.TextFieldConfig{
					Name: "employee_name",
					Type: "TEXT",
					Description: "Employee full name",
				},
				il.TextFieldConfig{
					Name: "social_security_number",
					Type: "TEXT",
					Description: "Employee Social Security number",
				},
				il.AddressFieldConfig{
					Name: "address",
					Type: "ADDRESS",
					Description: "Employee address",
				},
				il.TextFieldConfig{
					Name: "filing_status",
					Type: "TEXT",
					Description: "Selected filing status",
				},
				il.CurrencyAmountFieldConfig{
					Name: "dependents_amount",
					Type: "CURRENCY_AMOUNT",
					Description: "Step 3 dependent and other credits amount",
				},
				il.CurrencyAmountFieldConfig{
					Name: "other_income",
					Type: "CURRENCY_AMOUNT",
					Description: "Step 4(a) other income",
				},
				il.CurrencyAmountFieldConfig{
					Name: "deductions",
					Type: "CURRENCY_AMOUNT",
					Description: "Step 4(b) deductions",
				},
				il.CurrencyAmountFieldConfig{
					Name: "extra_withholding",
					Type: "CURRENCY_AMOUNT",
					Description: "Step 4(c) extra withholding",
				},
				il.BooleanFieldConfig{
					Name: "is_signed",
					Type: "BOOLEAN",
					Description: "Whether the employee signature is present",
				},
				il.DateFieldConfig{
					Name: "signature_date",
					Type: "DATE",
					Description: "Date signed",
				},
			},
		},
	})
	if err != nil {
		panic(err)
	}

	_ = result
}

{
  "name": "Extract W-4 Data",
  "nodes": [
    {
      "parameters": {
        "content": "## Extract W-4 Data\n\nTax and finance teams use this recipe to extract W-4 fields from official forms into structured JSON for review, routing, and downstream filing preparation.\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": "extract-w-4-data-overview",
      "name": "Overview"
    },
    {
      "parameters": {},
      "type": "n8n-nodes-base.manualTrigger",
      "typeVersion": 1,
      "position": [
        250,
        300
      ],
      "id": "extract-w-4-data-trigger",
      "name": "Manual Trigger"
    },
    {
      "parameters": {
        "resource": "documentExtraction",
        "schemaInputMode": "rawJson",
        "schemaJson": "{\n  \"fields\": [\n    {\n      \"name\": \"employee_name\",\n      \"type\": \"TEXT\",\n      \"description\": \"Employee full name\"\n    },\n    {\n      \"name\": \"social_security_number\",\n      \"type\": \"TEXT\",\n      \"description\": \"Employee Social Security number\"\n    },\n    {\n      \"name\": \"address\",\n      \"type\": \"ADDRESS\",\n      \"description\": \"Employee address\"\n    },\n    {\n      \"name\": \"filing_status\",\n      \"type\": \"TEXT\",\n      \"description\": \"Selected filing status\"\n    },\n    {\n      \"name\": \"dependents_amount\",\n      \"type\": \"CURRENCY_AMOUNT\",\n      \"description\": \"Step 3 dependent and other credits amount\"\n    },\n    {\n      \"name\": \"other_income\",\n      \"type\": \"CURRENCY_AMOUNT\",\n      \"description\": \"Step 4(a) other income\"\n    },\n    {\n      \"name\": \"deductions\",\n      \"type\": \"CURRENCY_AMOUNT\",\n      \"description\": \"Step 4(b) deductions\"\n    },\n    {\n      \"name\": \"extra_withholding\",\n      \"type\": \"CURRENCY_AMOUNT\",\n      \"description\": \"Step 4(c) extra withholding\"\n    },\n    {\n      \"name\": \"is_signed\",\n      \"type\": \"BOOLEAN\",\n      \"description\": \"Whether the employee signature is present\"\n    },\n    {\n      \"name\": \"signature_date\",\n      \"type\": \"DATE\",\n      \"description\": \"Date signed\"\n    }\n  ]\n}",
        "files": {
          "fileValues": [
            {
              "fileInputMode": "url",
              "fileName": "w-4.pdf",
              "fileUrl": "https://example.com/documents/w-4-sample.pdf"
            }
          ]
        }
      },
      "type": "n8n-nodes-iterationlayer.iterationLayer",
      "typeVersion": 1,
      "position": [
        500,
        300
      ],
      "id": "extract-w-4-data-extract",
      "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 w-4 data from the file at [file URL]. Use the extract_document tool with these fields:

- employee_name (TEXT): Employee full name
- social_security_number (TEXT): Employee Social Security number
- address (ADDRESS): Employee address
- filing_status (TEXT): Selected filing status
- dependents_amount (CURRENCY_AMOUNT): Step 3 dependent and other credits amount
- other_income (CURRENCY_AMOUNT): Step 4(a) other income
- deductions (CURRENCY_AMOUNT): Step 4(b) deductions
- extra_withholding (CURRENCY_AMOUNT): Step 4(c) extra withholding
- is_signed (BOOLEAN): Whether the employee signature is present
- signature_date (DATE): Date signed

Response

{
  "success": true,
  "data": {
    "employee_name": {
      "value": "Employee Name",
      "confidence": 0.97,
      "citations": [
        "EMPLOYEE NAME"
      ]
    },
    "social_security_number": {
      "value": "Social Security Number",
      "confidence": 0.97,
      "citations": [
        "SOCIAL SECURITY NUMBER"
      ]
    },
    "address": {
      "value": {
        "street": "100 Market Street",
        "city": "Berlin",
        "postal_code": "10115",
        "country": "DE"
      },
      "confidence": 0.97,
      "citations": [
        "ADDRESS"
      ]
    },
    "filing_status": {
      "value": "Filing Status",
      "confidence": 0.97,
      "citations": [
        "FILING STATUS"
      ]
    },
    "dependents_amount": {
      "value": {
        "amount": "1234.56",
        "currency": "USD"
      },
      "confidence": 0.97,
      "citations": [
        "$1,234.56"
      ]
    },
    "other_income": {
      "value": {
        "amount": "1234.56",
        "currency": "USD"
      },
      "confidence": 0.97,
      "citations": [
        "$1,234.56"
      ]
    },
    "deductions": {
      "value": {
        "amount": "1234.56",
        "currency": "USD"
      },
      "confidence": 0.97,
      "citations": [
        "$1,234.56"
      ]
    },
    "extra_withholding": {
      "value": {
        "amount": "1234.56",
        "currency": "USD"
      },
      "confidence": 0.97,
      "citations": [
        "$1,234.56"
      ]
    },
    "is_signed": {
      "value": true,
      "confidence": 0.97,
      "citations": [
        "IS SIGNED"
      ]
    },
    "signature_date": {
      "value": "2026-04-15",
      "confidence": 0.97,
      "citations": [
        "15 Apr 2026"
      ]
    }
  }
}

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

같은 저장소의 스킬

compress-image-for-email

무료

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills42026년 6월 9일 업데이트

compress-image-to-target-size

무료

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills42026년 6월 9일 업데이트

convert-contract-to-markdown

무료

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills42026년 6월 9일 업데이트

convert-document-for-knowledge-base

무료

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills42026년 6월 9일 업데이트

convert-document-for-rag-ingestion

무료

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills42026년 6월 9일 업데이트

convert-image-format

무료

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

iterationlayer/skills42026년 6월 9일 업데이트

iterationlayer의 스킬 모두 보기

이 스킬의 문제 신고

설치

명령으로 설치

npx skills add https://github.com/iterationlayer/skills --skill extract-w-4-data

터미널에 붙여 넣고 실행합니다(Node.js 필요). Claude Code, Codex 등 설치할 에이전트를 고를 수 있습니다.

에이전트에게 부탁하기

다음 Agent Skill을 설치해 주세요.
https://github.com/iterationlayer/skills/tree/main/skills/extract-w-4-data

먼저 SKILL.md와 첨부 파일의 내용을 확인해 수상한 처리(외부 전송, 인증 정보 읽기 등)가 없는지 확인한 뒤 Claude Code는 ~/.claude/skills/extract-w-4-data/, Codex는 ~/.agents/skills/extract-w-4-data/ 에 배치해 주세요.

이 문장을 그대로 Claude Code나 Codex에 보내면 내용을 확인한 뒤 설치해 줍니다.

GitHub에서 소스 보기

저장소: iterationlayer/skills
스타: 4
포크: 0
카테고리: 데이터·AI
라이선스: MIT
원문 언어: 영어
최종 업데이트: 2026년 6월 9일

스킬은 에이전트를 위한 지시와 스크립트의 묶음입니다. cccskills는 내용의 안전성을 보증하지 않습니다. 설치하기 전에 내용을 확인하세요.

포함된 파일(1)

SKILL.md(원문)

Extract W-4 Data

APIs Used

Prerequisites

Implementation

Response

Links

리뷰

댓글

같은 저장소의 스킬

compress-image-for-email

compress-image-to-target-size

convert-contract-to-markdown

convert-document-for-knowledge-base

convert-document-for-rag-ingestion

convert-image-format