Azure AI Document Intelligence Ts Agent Skill

Extract text, tables, and structured data from documents using Azure Document Intelligence (@azure-rest/ai-document-intelligence). Use when processing invoices, receipts, IDs, forms, or building custom document models.

2k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

149 d ago

last touched

this folder, not the whole repository

Install

one command, takes just this skill from the repository

npx skills add https://github.com/microsoft/skills --skill azure-ai-document-intelligence-ts

The instruction itself

19 sections, as written by the author

Azure Document Intelligence REST SDK for TypeScript

Extract text, tables, and structured data from documents using prebuilt and custom models.

Installation

npm install @azure-rest/ai-document-intelligence @azure/identity

Environment Variables

DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource>.cognitiveservices.azure.com
DOCUMENT_INTELLIGENCE_API_KEY=<api-key>
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication

Important: This is a REST client. DocumentIntelligence is a function, not a class.

DefaultAzureCredential

import DocumentIntelligence from "@azure-rest/ai-document-intelligence";
import { DefaultAzureCredential, ManagedIdentityCredential } from "@azure/identity";

// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
const credential = new DefaultAzureCredential({requiredEnvVars: ["AZURE_TOKEN_CREDENTIALS"]});
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/javascript/api/overview/azure/identity-readme?view=azure-node-latest#credential-classes
// const credential = new ManagedIdentityCredential();

const client = DocumentIntelligence(
  process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,
  credential
);

API Key

import DocumentIntelligence from "@azure-rest/ai-document-intelligence";

const client = DocumentIntelligence(
  process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,
  { key: process.env.DOCUMENT_INTELLIGENCE_API_KEY! }
);

Analyze Document (URL)

import DocumentIntelligence, {
  isUnexpected,
  getLongRunningPoller,
  AnalyzeOperationOutput
} from "@azure-rest/ai-document-intelligence";

const initialResponse = await client
  .path("/documentModels/{modelId}:analyze", "prebuilt-layout")
  .post({
    contentType: "application/json",
    body: {
      urlSource: "https://example.com/document.pdf"
    },
    queryParameters: { locale: "en-US" }
  });

if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

const poller = getLongRunningPoller(client, initialResponse);
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;

console.log("Pages:", result.analyzeResult?.pages?.length);
console.log("Tables:", result.analyzeResult?.tables?.length);

Analyze Document (Local File)

import { readFile } from "node:fs/promises";

const fileBuffer = await readFile("./document.pdf");
const base64Source = fileBuffer.toString("base64");

const initialResponse = await client
  .path("/documentModels/{modelId}:analyze", "prebuilt-invoice")
  .post({
    contentType: "application/json",
    body: { base64Source }
  });

if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

const poller = getLongRunningPoller(client, initialResponse);
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;

Prebuilt Models

| Model ID | Description |

|----------|-------------|

| prebuilt-read | OCR - text and language extraction |

| prebuilt-layout | Text, tables, selection marks, structure |

| prebuilt-invoice | Invoice fields |

| prebuilt-receipt | Receipt fields |

| prebuilt-idDocument | ID document fields |

| prebuilt-tax.us.w2 | W-2 tax form fields |

| prebuilt-healthInsuranceCard.us | Health insurance card fields |

| prebuilt-contract | Contract fields |

| prebuilt-bankStatement.us | Bank statement fields |

Extract Invoice Fields

const initialResponse = await client
  .path("/documentModels/{modelId}:analyze", "prebuilt-invoice")
  .post({
    contentType: "application/json",
    body: { urlSource: invoiceUrl }
  });

if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

const poller = getLongRunningPoller(client, initialResponse);
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;

const invoice = result.analyzeResult?.documents?.[0];
if (invoice) {
  console.log("Vendor:", invoice.fields?.VendorName?.content);
  console.log("Total:", invoice.fields?.InvoiceTotal?.content);
  console.log("Due Date:", invoice.fields?.DueDate?.content);
}

Extract Receipt Fields

const initialResponse = await client
  .path("/documentModels/{modelId}:analyze", "prebuilt-receipt")
  .post({
    contentType: "application/json",
    body: { urlSource: receiptUrl }
  });

const poller = getLongRunningPoller(client, initialResponse);
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;

const receipt = result.analyzeResult?.documents?.[0];
if (receipt) {
  console.log("Merchant:", receipt.fields?.MerchantName?.content);
  console.log("Total:", receipt.fields?.Total?.content);
  
  for (const item of receipt.fields?.Items?.values || []) {
    console.log("Item:", item.properties?.Description?.content);
    console.log("Price:", item.properties?.TotalPrice?.content);
  }
}

List Document Models

import DocumentIntelligence, { isUnexpected, paginate } from "@azure-rest/ai-document-intelligence";

const response = await client.path("/documentModels").get();

if (isUnexpected(response)) {
  throw response.body.error;
}

for await (const model of paginate(client, response)) {
  console.log(model.modelId);
}

Build Custom Model

const initialResponse = await client.path("/documentModels:build").post({
  body: {
    modelId: "my-custom-model",
    description: "Custom model for purchase orders",
    buildMode: "template",  // or "neural"
    azureBlobSource: {
      containerUrl: process.env.TRAINING_CONTAINER_SAS_URL!,
      prefix: "training-data/"
    }
  }
});

if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

const poller = getLongRunningPoller(client, initialResponse);
const result = await poller.pollUntilDone();
console.log("Model built:", result.body);

Build Document Classifier

import { DocumentClassifierBuildOperationDetailsOutput } from "@azure-rest/ai-document-intelligence";

const containerSasUrl = process.env.TRAINING_CONTAINER_SAS_URL!;

const initialResponse = await client.path("/documentClassifiers:build").post({
  body: {
    classifierId: "my-classifier",
    description: "Invoice vs Receipt classifier",
    docTypes: {
      invoices: {
        azureBlobSource: { containerUrl: containerSasUrl, prefix: "invoices/" }
      },
      receipts: {
        azureBlobSource: { containerUrl: containerSasUrl, prefix: "receipts/" }
      }
    }
  }
});

if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

const poller = getLongRunningPoller(client, initialResponse);
const result = (await poller.pollUntilDone()).body as DocumentClassifierBuildOperationDetailsOutput;
console.log("Classifier:", result.result?.classifierId);

Classify Document

const initialResponse = await client
  .path("/documentClassifiers/{classifierId}:analyze", "my-classifier")
  .post({
    contentType: "application/json",
    body: { urlSource: documentUrl },
    queryParameters: { split: "auto" }
  });

if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

const poller = getLongRunningPoller(client, initialResponse);
const result = await poller.pollUntilDone();
console.log("Classification:", result.body.analyzeResult?.documents);

Get Service Info

const response = await client.path("/info").get();

if (isUnexpected(response)) {
  throw response.body.error;
}

console.log("Custom model limit:", response.body.customDocumentModels.limit);
console.log("Custom model count:", response.body.customDocumentModels.count);

Polling Pattern

import DocumentIntelligence, {
  isUnexpected,
  getLongRunningPoller,
  AnalyzeOperationOutput
} from "@azure-rest/ai-document-intelligence";

// 1. Start operation
const initialResponse = await client
  .path("/documentModels/{modelId}:analyze", "prebuilt-layout")
  .post({ contentType: "application/json", body: { urlSource } });

// 2. Check for errors
if (isUnexpected(initialResponse)) {
  throw initialResponse.body.error;
}

// 3. Create poller
const poller = getLongRunningPoller(client, initialResponse);

// 4. Optional: Monitor progress
poller.onProgress((state) => {
  console.log("Status:", state.status);
});

// 5. Wait for completion
const result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;

Key Types

import DocumentIntelligence, {
  isUnexpected,
  getLongRunningPoller,
  paginate,
  parseResultIdFromResponse,
  AnalyzeOperationOutput,
  DocumentClassifierBuildOperationDetailsOutput
} from "@azure-rest/ai-document-intelligence";

Best Practices

Use getLongRunningPoller() - Document analysis is async, always poll for results
Check isUnexpected() - Type guard for proper error handling
Choose the right model - Use prebuilt models when possible, custom for specialized docs
Handle confidence scores - Fields have confidence values, set thresholds for your use case
Use pagination - Use paginate() helper for listing models
Prefer neural mode - For custom models, neural handles more variation than template

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How to use it

Copy the folder

Take microsoft/azure-ai-document-intelligence-ts from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npm. Without those the skill loads but fails at the first command.