Azure AI Document Intelligence TS

MicrosoftOfficialCreated by Microsoft

Skill
Tool integration
Data and AI
MIT
No issues found

From the author

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.

— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a guide for using the @azure-rest/ai-document-intelligence REST SDK in TypeScript. It covers authentication, document analysis using prebuilt or custom models, document classification, and managing models. The SDK supports processing documents via URL or local file buffers, utilizing asynchronous polling to retrieve results from complex document analysis tasks.

What it does

Extracts text, tables, and structured data from various document types.
Supports prebuilt models for invoices, receipts, IDs, tax forms, and more.
Enables building and training custom document models and classifiers.
Provides utilities for asynchronous operation polling and pagination.
Offers robust error handling with type guards for REST responses.

When to use it

When you need to automate data extraction from business documents like invoices or receipts.
When building applications that require document classification or specialized document parsing.
When integrating Azure AI document services into a TypeScript or Node.js environment.
When you need to process documents stored in Azure Blob Storage using custom models.

Advantages

Leverages powerful prebuilt AI models for common document types.
Flexible support for both cloud-hosted and local file-based document processing.
Includes built-in helpers for managing long-running operations and pagination.
Supports custom model training to handle specialized or unique document layouts.

Usage examples

“How do I extract data from an invoice using the Azure Document Intelligence SDK?”: The agent provides a code snippet using the prebuilt-invoice model, showing how to post the document URL and use the getLongRunningPoller to retrieve vendor and total fields.
“Show me how to train a custom document model.”: The agent demonstrates the /documentModels:build endpoint, explaining how to point the service to a container URL containing training data.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/azure-ai-document-intelligence-ts/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip azure-ai-document-intelligence-ts.zip -d .agents/skills

Documentation by Microsoft

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

Files

ATTRIBUTION.mdAdded by AutoGineer1018 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md9.5 KiB

ATTRIBUTION.md

Attribution

This folder is an unmodified copy of the Agent Skill "azure-ai-document-intelligence-ts", distributed by AutoGineer (https://autogineer.com/agent-skills).

Source: https://github.com/microsoft/skills/tree/0696600436a9669184ce47e8d8b2ceac62e4bfac/.github/plugins/azure-sdk-typescript/skills/azure-ai-document-intelligence-ts
Commit: 0696600436a9669184ce47e8d8b2ceac62e4bfac
Created by: Microsoft (https://github.com/microsoft/skills/tree/0696600436a9669184ce47e8d8b2ceac62e4bfac/.github/plugins/azure-sdk-typescript/skills/azure-ai-document-intelligence-ts)
Publisher: Microsoft (https://github.com/microsoft)
Licence: MIT License (https://spdx.org/licenses/MIT.html)
Licence evidence: declared in the frontmatter ("license: MIT")
Retrieved: 2026-11-07

The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.

Files added by AutoGineer

ATTRIBUTION.md: this file, written by AutoGineer
LICENSE: copied from LICENSE

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an API key, Needs Node.js

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

Microsoft

Publisher

Microsoft (Official)

Source

microsoft/skills · .github/plugins/azure-sdk-typescript/skills/azure-ai-document-intelligence-ts · commit 0696600

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-ai-document-intelligence-ts.zip