本文へ移動
cccskills
無料GitHub で公開

extract-fleet-vehicle-registration

Extract vehicle identification, owner details, registration dates, and technical specifications from vehicle registration documents.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md14.1 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Extract Fleet Vehicle Registration Data

Fleet management agencies use this recipe to digitize vehicle registration documents — extracting VIN numbers, registration dates, insurance details, and technical specs for centralized fleet databases.

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": "vehicle-registration-FL-4821.pdf",
        "url": "https://example.com/fleet/registration-FL-4821.pdf"
      }
    ],
    "schema": {
      "fields": [
        {
          "name": "license_plate",
          "type": "TEXT",
          "description": "Vehicle license plate number"
        },
        {
          "name": "vin",
          "type": "TEXT",
          "description": "Vehicle Identification Number (VIN)"
        },
        {
          "name": "make",
          "type": "TEXT",
          "description": "Vehicle manufacturer"
        },
        {
          "name": "model",
          "type": "TEXT",
          "description": "Vehicle model"
        },
        {
          "name": "year",
          "type": "INTEGER",
          "description": "Model year"
        },
        {
          "name": "body_type",
          "type": "TEXT",
          "description": "Body type, e.g. van, truck, sedan"
        },
        {
          "name": "fuel_type",
          "type": "TEXT",
          "description": "Fuel type, e.g. diesel, electric, petrol"
        },
        {
          "name": "registered_owner",
          "type": "TEXT",
          "description": "Registered owner name or company"
        },
        {
          "name": "registration_date",
          "type": "DATE",
          "description": "Date of first registration"
        },
        {
          "name": "registration_expiry",
          "type": "DATE",
          "description": "Registration expiry date"
        },
        {
          "name": "gross_vehicle_weight",
          "type": "TEXT",
          "description": "Maximum gross vehicle weight"
        },
        {
          "name": "emission_class",
          "type": "TEXT",
          "description": "Emission standard class"
        }
      ]
    }
  }'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });

const result = await client.extractDocument({
  files: [
    {
      type: "url",
      name: "vehicle-registration-FL-4821.pdf",
      url: "https://example.com/fleet/registration-FL-4821.pdf",
    },
  ],
  schema: {
    fields: [
      { name: "license_plate", type: "TEXT", description: "Vehicle license plate number" },
      { name: "vin", type: "TEXT", description: "Vehicle Identification Number (VIN)" },
      { name: "make", type: "TEXT", description: "Vehicle manufacturer" },
      { name: "model", type: "TEXT", description: "Vehicle model" },
      { name: "year", type: "INTEGER", description: "Model year" },
      { name: "body_type", type: "TEXT", description: "Body type, e.g. van, truck, sedan" },
      { name: "fuel_type", type: "TEXT", description: "Fuel type, e.g. diesel, electric, petrol" },
      { name: "registered_owner", type: "TEXT", description: "Registered owner name or company" },
      { name: "registration_date", type: "DATE", description: "Date of first registration" },
      { name: "registration_expiry", type: "DATE", description: "Registration expiry date" },
      { name: "gross_vehicle_weight", type: "TEXT", description: "Maximum gross vehicle weight" },
      { name: "emission_class", type: "TEXT", description: "Emission standard class" },
    ],
  },
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")

result = client.extract_document(
    files=[
        {
            "type": "url",
            "name": "vehicle-registration-FL-4821.pdf",
            "url": "https://example.com/fleet/registration-FL-4821.pdf",
        }
    ],
    schema={
        "fields": [
            {"name": "license_plate", "type": "TEXT", "description": "Vehicle license plate number"},
            {"name": "vin", "type": "TEXT", "description": "Vehicle Identification Number (VIN)"},
            {"name": "make", "type": "TEXT", "description": "Vehicle manufacturer"},
            {"name": "model", "type": "TEXT", "description": "Vehicle model"},
            {"name": "year", "type": "INTEGER", "description": "Model year"},
            {"name": "body_type", "type": "TEXT", "description": "Body type, e.g. van, truck, sedan"},
            {"name": "fuel_type", "type": "TEXT", "description": "Fuel type, e.g. diesel, electric, petrol"},
            {"name": "registered_owner", "type": "TEXT", "description": "Registered owner name or company"},
            {"name": "registration_date", "type": "DATE", "description": "Date of first registration"},
            {"name": "registration_expiry", "type": "DATE", "description": "Registration expiry date"},
            {"name": "gross_vehicle_weight", "type": "TEXT", "description": "Maximum gross vehicle weight"},
            {"name": "emission_class", "type": "TEXT", "description": "Emission standard class"},
        ]
    },
)
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: "vehicle-registration-FL-4821.pdf",
				Url: "https://example.com/fleet/registration-FL-4821.pdf",
			},
		},
		Schema: il.ExtractionSchema{
			Fields: []any{
				il.TextFieldConfig{
					Name: "license_plate",
					Type: "TEXT",
					Description: "Vehicle license plate number",
				},
				il.TextFieldConfig{
					Name: "vin",
					Type: "TEXT",
					Description: "Vehicle Identification Number (VIN)",
				},
				il.TextFieldConfig{
					Name: "make",
					Type: "TEXT",
					Description: "Vehicle manufacturer",
				},
				il.TextFieldConfig{
					Name: "model",
					Type: "TEXT",
					Description: "Vehicle model",
				},
				il.IntegerFieldConfig{
					Name: "year",
					Type: "INTEGER",
					Description: "Model year",
				},
				il.TextFieldConfig{
					Name: "body_type",
					Type: "TEXT",
					Description: "Body type, e.g. van, truck, sedan",
				},
				il.TextFieldConfig{
					Name: "fuel_type",
					Type: "TEXT",
					Description: "Fuel type, e.g. diesel, electric, petrol",
				},
				il.TextFieldConfig{
					Name: "registered_owner",
					Type: "TEXT",
					Description: "Registered owner name or company",
				},
				il.DateFieldConfig{
					Name: "registration_date",
					Type: "DATE",
					Description: "Date of first registration",
				},
				il.DateFieldConfig{
					Name: "registration_expiry",
					Type: "DATE",
					Description: "Registration expiry date",
				},
				il.TextFieldConfig{
					Name: "gross_vehicle_weight",
					Type: "TEXT",
					Description: "Maximum gross vehicle weight",
				},
				il.TextFieldConfig{
					Name: "emission_class",
					Type: "TEXT",
					Description: "Emission standard class",
				},
			},
		},
	})
	if err != nil {
		panic(err)
	}

	_ = result
}
{
  "name": "Extract fleet vehicle registration data in Iteration Layer",
  "nodes": [
    {
      "parameters": {
        "content": "## Extract Fleet Vehicle Registration Data\n\nFleet management agencies use this recipe to digitize vehicle registration documents — extracting VIN numbers, registration dates, insurance details, and technical specs for centralized fleet databases.\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": "b8c9d0e1-f2a3-4567-bcde-567890123401",
      "name": "Overview"
    },
    {
      "parameters": {
        "content": "### Step 1: Extract Registration 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": "b8c9d0e1-f2a3-4567-bcde-567890123402",
      "name": "Step 1 Note"
    },
    {
      "parameters": {},
      "type": "n8n-nodes-base.manualTrigger",
      "typeVersion": 1,
      "position": [
        250,
        300
      ],
      "id": "b8c9d0e1-f2a3-4567-bcde-567890123403",
      "name": "Manual Trigger"
    },
    {
      "parameters": {
        "resource": "documentExtraction",
        "schemaInputMode": "rawJson",
        "schemaJson": "{\"fields\":[{\"name\":\"license_plate\",\"type\":\"TEXT\",\"description\":\"Vehicle license plate number\"},{\"name\":\"vin\",\"type\":\"TEXT\",\"description\":\"Vehicle Identification Number (VIN)\"},{\"name\":\"make\",\"type\":\"TEXT\",\"description\":\"Vehicle manufacturer\"},{\"name\":\"model\",\"type\":\"TEXT\",\"description\":\"Vehicle model\"},{\"name\":\"year\",\"type\":\"INTEGER\",\"description\":\"Model year\"},{\"name\":\"body_type\",\"type\":\"TEXT\",\"description\":\"Body type\"},{\"name\":\"fuel_type\",\"type\":\"TEXT\",\"description\":\"Fuel type\"},{\"name\":\"registered_owner\",\"type\":\"TEXT\",\"description\":\"Registered owner name or company\"},{\"name\":\"registration_date\",\"type\":\"DATE\",\"description\":\"Date of first registration\"},{\"name\":\"registration_expiry\",\"type\":\"DATE\",\"description\":\"Registration expiry date\"},{\"name\":\"gross_vehicle_weight\",\"type\":\"TEXT\",\"description\":\"Maximum gross vehicle weight\"},{\"name\":\"emission_class\",\"type\":\"TEXT\",\"description\":\"Emission standard class\"}]}",
        "files": {
          "fileValues": [
            {
              "fileInputMode": "url",
              "fileName": "vehicle-registration-FL-4821.pdf",
              "fileUrl": "https://example.com/fleet/registration-FL-4821.pdf"
            }
          ]
        }
      },
      "type": "n8n-nodes-iterationlayer.iterationLayer",
      "typeVersion": 1,
      "position": [
        500,
        300
      ],
      "id": "b8c9d0e1-f2a3-4567-bcde-567890123404",
      "name": "Extract Registration Data",
      "credentials": {
        "iterationLayerApi": {
          "id": "1",
          "name": "Iteration Layer API"
        }
      }
    }
  ],
  "connections": {
    "Manual Trigger": {
      "main": [
        [
          {
            "node": "Extract Registration Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}
Extract fleet vehicle registration data from the file at [file URL]. Use the extract_document tool with these fields:

- license_plate (TEXT): Vehicle license plate number
- vin (TEXT): Vehicle Identification Number (VIN)
- make (TEXT): Vehicle manufacturer
- model (TEXT): Vehicle model
- year (INTEGER): Model year
- body_type (TEXT): Body type, e.g. van, truck, sedan
- fuel_type (TEXT): Fuel type, e.g. diesel, electric, petrol
- registered_owner (TEXT): Registered owner name or company
- registration_date (DATE): Date of first registration
- registration_expiry (DATE): Registration expiry date
- gross_vehicle_weight (TEXT): Maximum gross vehicle weight
- emission_class (TEXT): Emission standard class

Response

{
  "success": true,
  "data": {
    "license_plate": {
      "value": "MI-4821-KZ",
      "confidence": 0.99,
      "citations": [
        "Targa: MI-4821-KZ"
      ]
    },
    "vin": {
      "value": "WVGZZZ5NZYW048291",
      "confidence": 0.98,
      "citations": [
        "Telaio: WVGZZZ5NZYW048291"
      ]
    },
    "make": {
      "value": "Iveco",
      "confidence": 0.99,
      "citations": [
        "Marca: Iveco"
      ]
    },
    "model": {
      "value": "Daily 35S14",
      "confidence": 0.97,
      "citations": [
        "Modello: Daily 35S14"
      ]
    },
    "year": {
      "value": 2024,
      "confidence": 0.98,
      "citations": [
        "Anno: 2024"
      ]
    },
    "body_type": {
      "value": "Van",
      "confidence": 0.96,
      "citations": [
        "Carrozzeria: Furgone"
      ]
    },
    "fuel_type": {
      "value": "Diesel",
      "confidence": 0.99,
      "citations": [
        "Alimentazione: Gasolio"
      ]
    },
    "registered_owner": {
      "value": "Veloce Logistics S.r.l.",
      "confidence": 0.98,
      "citations": [
        "Intestatario: Veloce Logistics S.r.l."
      ]
    },
    "registration_date": {
      "value": "2024-06-12",
      "confidence": 0.97,
      "citations": [
        "Data immatricolazione: 12/06/2024"
      ]
    },
    "registration_expiry": {
      "value": "2026-06-12",
      "confidence": 0.96,
      "citations": [
        "Scadenza revisione: 12/06/2026"
      ]
    },
    "gross_vehicle_weight": {
      "value": "3,500 kg",
      "confidence": 0.97,
      "citations": [
        "Massa complessiva: 3.500 kg"
      ]
    },
    "emission_class": {
      "value": "Euro 6d",
      "confidence": 0.95,
      "citations": [
        "Classe emissioni: Euro 6d"
      ]
    }
  }
}

Links

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

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

日本語の概要は準備中です。原文の説明を表示しています。

iterationlayer/skills42026年6月9日 更新

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

日本語の概要は準備中です。原文の説明を表示しています。

iterationlayer/skills42026年6月9日 更新

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

日本語の概要は準備中です。原文の説明を表示しています。

iterationlayer/skills42026年6月9日 更新

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

日本語の概要は準備中です。原文の説明を表示しています。

iterationlayer/skills42026年6月9日 更新

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

日本語の概要は準備中です。原文の説明を表示しています。

iterationlayer/skills42026年6月9日 更新

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

日本語の概要は準備中です。原文の説明を表示しています。

iterationlayer/skills42026年6月9日 更新

iterationlayer のスキルをすべて見る

このスキルの問題を報告する