Azure Ai Document Intelligence Ts
Azure Ai Document Intelligence Ts is an data AI skill with a core value of Extract text, tables, and structured data from documents using Azure Document Intelligence (@azure-rest/ai-document-intelligence). It
helps developers solve real-world problems in the data domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
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 cu...
Quick Facts
mkdir -p ./skills/azure-ai-document-intelligence-ts && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-ai-document-intelligence-ts/SKILL.md -o ./skills/azure-ai-document-intelligence-ts/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# 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/identityEnvironment Variables
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource>.cognitiveservices.azure.com
DOCUMENT_INTELLIGENCE_API_KEY=<api-key>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 } from "@azure/identity";
const client = DocumentIntelligence(
process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,
new DefaultAzureCredential()
);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, initialRespons🎯 Best For
- Technical writers
- API documentation teams
- UI designers
- Product designers
- Claude users
💡 Use Cases
- Generating JSDoc/TSDoc comments
- Writing README files for new projects
- Generating component mockups
- Creating design system tokens
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Azure Ai Document Intelligence Ts to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does it follow my documentation style?
Most documentation skills respect existing style. Provide a style guide or example in your prompt.
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
How do I install Azure Ai Document Intelligence Ts?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-ai-document-intelligence-ts/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Auto-generating without reviewing
AI documentation can contain inaccuracies. Always verify technical accuracy.
Skipping usability testing
AI-generated designs should be validated with real users before development.
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.