Official agent skill

Azure AI Document Intelligence Dotnet

by microsoft in microsoft/skills

Azure AI Document Intelligence SDK for .NET. An agent skill from microsoft/skills.

OfficialMITAuto-check passedDocuments & Office

Install Azure AI Document Intelligence Dotnet

skills CLI
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnet --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet .claude/skills/azure-ai-document-intelligence-dotnet && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-ai-document-intelligence-dotnet
GitHub stars
3.1k
Used in
6 other repos
Token cost
~3k tokens
SKILL.md length
304 words
Files
1
Skills in repo
150
Repo updated
First seen
Licence
MIT

At a glance

Azure AI Document Intelligence SDK for .NET. An agent skill from microsoft/skills.

  • Works in 7 steps: Analyze Invoice → Extract Layout (Text, Tables, Structure) → Analyze Receipt → …
  • Invoice processing
  • SKILL.md covers Installation, Environment Variables, Authentication and Client Types, plus 8 more sections
  • Calls dotnet; reaches learn.microsoft.com; needs AZURE_TOKEN_CREDENTIALS and DOCUMENT_INTELLIGENCE_API_KEY

What it does

Azure AI Document Intelligence Dotnet is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Documents & Office, covering Forms and invoices and Schema markup. It works with Azure AI Document Intelligence, Microsoft Azure and .NET. The repository describes itself as: Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents. The licence is MIT.

When your agent uses it

  • Invoice processing
  • Receipt extraction
  • ID document analysis
  • Custom document models

Example prompts

  • “Document Intelligence”
  • “DocumentIntelligenceClient”
  • “form recognizer”
  • “/azure-ai-document-intelligence-dotnet”

Requirements

  • A credential in DOCUMENT_INTELLIGENCE_API_KEY

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Analyze Invoice
  2. Extract Layout (Text, Tables, Structure)
  3. Analyze Receipt
  4. Build Custom Model
  5. Build Document Classifier
  6. Classify Document
  7. Manage Models

What it can do on your machine

Read from SKILL.md and the folder at commit 354361d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • dotnet

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • learn.microsoft.com

    Also links to:

    • nuget.org
    • github.com
    • documentintelligence.ai.azure.com
    • aka.ms

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AZURE_TOKEN_CREDENTIALS
    • DOCUMENT_INTELLIGENCE_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azure AI Document Intelligence Dotnet loads about 3k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 304 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~105
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft/skills at commit 354361d, republished under its MIT licence (© microsoft). 304 words, ~2,972 tokens.

Download SKILL.mdSave it as .claude/skills/azure-ai-document-intelligence-dotnet/SKILL.md (or your agent's skills folder).
name
azure-ai-document-intelligence-dotnet
description
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".
license
MIT
metadata.author
Microsoft
metadata.version
1.0.0
metadata.package
Azure.AI.DocumentIntelligence

Azure.AI.DocumentIntelligence (.NET)

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

Installation

bash
dotnet add package Azure.AI.DocumentIntelligence
dotnet add package Azure.Identity

Current Version: v1.0.0 (GA)

Environment Variables

bash
DOCUMENT_INTELLIGENCE_ENDPOINT=https://<resource-name>.cognitiveservices.azure.com/  # Required: Document Intelligence endpoint
DOCUMENT_INTELLIGENCE_API_KEY=<your-api-key>  # Only required for AzureKeyCredential auth
BLOB_CONTAINER_SAS_URL=https://<storage>.blob.core.windows.net/<container>?<sas-token>  # Optional: blob container SAS URL for training data
AZURE_TOKEN_CREDENTIALS=prod  # Required only if DefaultAzureCredential is used in production

Authentication

Microsoft Entra Token Credential
csharp
using Azure.Identity;
using Azure.AI.DocumentIntelligence;

string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
// Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
var credential = new DefaultAzureCredential(
    DefaultAzureCredential.DefaultEnvironmentVariableName
);
// Or use a specific credential directly in production:
// See https://learn.microsoft.com/dotnet/api/overview/azure/identity-readme?view=azure-dotnet#credential-classes
// var credential = new ManagedIdentityCredential();
var client = new DocumentIntelligenceClient(new Uri(endpoint), credential);

Note: Entra ID requires a custom subdomain (e.g., https://<resource-name>.cognitiveservices.azure.com/), not a regional endpoint.

API Key
csharp
string endpoint = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_ENDPOINT");
string apiKey = Environment.GetEnvironmentVariable("DOCUMENT_INTELLIGENCE_API_KEY");
var client = new DocumentIntelligenceClient(new Uri(endpoint), new AzureKeyCredential(apiKey));

Client Types

ClientPurpose
DocumentIntelligenceClientAnalyze documents, classify documents
DocumentIntelligenceAdministrationClientBuild/manage custom models and classifiers

Prebuilt Models

Model IDDescription
prebuilt-readExtract text, languages, handwriting
prebuilt-layoutExtract text, tables, selection marks, structure
prebuilt-invoiceExtract invoice fields (vendor, items, totals)
prebuilt-receiptExtract receipt fields (merchant, items, total)
prebuilt-idDocumentExtract ID document fields (name, DOB, address)
prebuilt-businessCardExtract business card fields
prebuilt-tax.us.w2Extract W-2 tax form fields
prebuilt-healthInsuranceCard.usExtract health insurance card fields

Core Workflows

1. Analyze Invoice
csharp
using Azure.AI.DocumentIntelligence;

Uri invoiceUri = new Uri("https://example.com/invoice.pdf");

Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-invoice", 
    invoiceUri);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    if (document.Fields.TryGetValue("VendorName", out DocumentField vendorNameField)
        && vendorNameField.FieldType == DocumentFieldType.String)
    {
        string vendorName = vendorNameField.ValueString;
        Console.WriteLine($"Vendor Name: '{vendorName}', confidence: {vendorNameField.Confidence}");
    }

    if (document.Fields.TryGetValue("InvoiceTotal", out DocumentField invoiceTotalField)
        && invoiceTotalField.FieldType == DocumentFieldType.Currency)
    {
        CurrencyValue invoiceTotal = invoiceTotalField.ValueCurrency;
        Console.WriteLine($"Invoice Total: '{invoiceTotal.CurrencySymbol}{invoiceTotal.Amount}'");
    }
    
    // Extract line items
    if (document.Fields.TryGetValue("Items", out DocumentField itemsField)
        && itemsField.FieldType == DocumentFieldType.List)
    {
        foreach (DocumentField item in itemsField.ValueList)
        {
            var itemFields = item.ValueDictionary;
            if (itemFields.TryGetValue("Description", out DocumentField descField))
                Console.WriteLine($"  Item: {descField.ValueString}");
        }
    }
}
2. Extract Layout (Text, Tables, Structure)
csharp
Uri fileUri = new Uri("https://example.com/document.pdf");

Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-layout", 
    fileUri);

AnalyzeResult result = operation.Value;

// Extract text by page
foreach (DocumentPage page in result.Pages)
{
    Console.WriteLine($"Page {page.PageNumber}: {page.Lines.Count} lines, {page.Words.Count} words");
    
    foreach (DocumentLine line in page.Lines)
    {
        Console.WriteLine($"  Line: '{line.Content}'");
    }
}

// Extract tables
foreach (DocumentTable table in result.Tables)
{
    Console.WriteLine($"Table: {table.RowCount} rows x {table.ColumnCount} columns");
    foreach (DocumentTableCell cell in table.Cells)
    {
        Console.WriteLine($"  Cell ({cell.RowIndex}, {cell.ColumnIndex}): {cell.Content}");
    }
}
3. Analyze Receipt
csharp
Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
    WaitUntil.Completed, 
    "prebuilt-receipt", 
    receiptUri);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    if (document.Fields.TryGetValue("MerchantName", out DocumentField merchantField))
        Console.WriteLine($"Merchant: {merchantField.ValueString}");
        
    if (document.Fields.TryGetValue("Total", out DocumentField totalField))
        Console.WriteLine($"Total: {totalField.ValueCurrency.Amount}");
        
    if (document.Fields.TryGetValue("TransactionDate", out DocumentField dateField))
        Console.WriteLine($"Date: {dateField.ValueDate}");
}
4. Build Custom Model
csharp
var adminClient = new DocumentIntelligenceAdministrationClient(
    new Uri(endpoint), 
    new AzureKeyCredential(apiKey));

string modelId = "my-custom-model";
Uri blobContainerUri = new Uri("<blob-container-sas-url>");

var blobSource = new BlobContentSource(blobContainerUri);
var options = new BuildDocumentModelOptions(modelId, DocumentBuildMode.Template, blobSource);

Operation<DocumentModelDetails> operation = await adminClient.BuildDocumentModelAsync(
    WaitUntil.Completed, 
    options);

DocumentModelDetails model = operation.Value;

Console.WriteLine($"Model ID: {model.ModelId}");
Console.WriteLine($"Created: {model.CreatedOn}");

foreach (var docType in model.DocumentTypes)
{
    Console.WriteLine($"Document type: {docType.Key}");
    foreach (var field in docType.Value.FieldSchema)
    {
        Console.WriteLine($"  Field: {field.Key}, Confidence: {docType.Value.FieldConfidence[field.Key]}");
    }
}
5. Build Document Classifier
csharp
string classifierId = "my-classifier";
Uri blobContainerUri = new Uri("<blob-container-sas-url>");

var sourceA = new BlobContentSource(blobContainerUri) { Prefix = "TypeA/train" };
var sourceB = new BlobContentSource(blobContainerUri) { Prefix = "TypeB/train" };

var docTypes = new Dictionary<string, ClassifierDocumentTypeDetails>()
{
    { "TypeA", new ClassifierDocumentTypeDetails(sourceA) },
    { "TypeB", new ClassifierDocumentTypeDetails(sourceB) }
};

var options = new BuildClassifierOptions(classifierId, docTypes);

Operation<DocumentClassifierDetails> operation = await adminClient.BuildClassifierAsync(
    WaitUntil.Completed, 
    options);

DocumentClassifierDetails classifier = operation.Value;
Console.WriteLine($"Classifier ID: {classifier.ClassifierId}");
6. Classify Document
csharp
string classifierId = "my-classifier";
Uri documentUri = new Uri("https://example.com/document.pdf");

var options = new ClassifyDocumentOptions(classifierId, documentUri);

Operation<AnalyzeResult> operation = await client.ClassifyDocumentAsync(
    WaitUntil.Completed, 
    options);

AnalyzeResult result = operation.Value;

foreach (AnalyzedDocument document in result.Documents)
{
    Console.WriteLine($"Document type: {document.DocumentType}, confidence: {document.Confidence}");
}
7. Manage Models
csharp
// Get resource details
DocumentIntelligenceResourceDetails resourceDetails = await adminClient.GetResourceDetailsAsync();
Console.WriteLine($"Custom models: {resourceDetails.CustomDocumentModels.Count}/{resourceDetails.CustomDocumentModels.Limit}");

// Get specific model
DocumentModelDetails model = await adminClient.GetModelAsync("my-model-id");
Console.WriteLine($"Model: {model.ModelId}, Created: {model.CreatedOn}");

// List models
await foreach (DocumentModelDetails modelItem in adminClient.GetModelsAsync())
{
    Console.WriteLine($"Model: {modelItem.ModelId}");
}

// Delete model
await adminClient.DeleteModelAsync("my-model-id");

Key Types Reference

TypeDescription
DocumentIntelligenceClientMain client for analysis
DocumentIntelligenceAdministrationClientModel management
AnalyzeResultResult of document analysis
AnalyzedDocumentSingle document within result
DocumentFieldExtracted field with value and confidence
DocumentFieldTypeString, Date, Number, Currency, etc.
DocumentPagePage info (lines, words, selection marks)
DocumentTableExtracted table with cells
DocumentModelDetailsCustom model metadata
BlobContentSourceTraining data source

Build Modes

ModeUse Case
DocumentBuildMode.TemplateFixed layout documents (forms)
DocumentBuildMode.NeuralVariable layout documents

Best Practices

  1. Use DefaultAzureCredential for production
  2. Reuse client instances — clients are thread-safe
  3. Handle long-running operations — Use WaitUntil.Completed for simplicity
  4. Check field confidence — Always verify Confidence property
  5. Use appropriate model — Prebuilt for common docs, custom for specialized
  6. Use custom subdomain — Required for Entra ID authentication

Error Handling

csharp
using Azure;

try
{
    var operation = await client.AnalyzeDocumentAsync(
        WaitUntil.Completed, 
        "prebuilt-invoice", 
        documentUri);
}
catch (RequestFailedException ex)
{
    Console.WriteLine($"Error: {ex.Status} - {ex.Message}");
}
SDKPurposeInstall
Azure.AI.DocumentIntelligenceDocument analysis (this SDK)dotnet add package Azure.AI.DocumentIntelligence
Azure.AI.FormRecognizerLegacy SDK (deprecated)Use DocumentIntelligence instead

© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet of microsoft/skills.

Open the folder on GitHubat commit 354361d

Used in 6 other repositories

We found 16 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 6 other GitHub owners. This page covers the copy in microsoft/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Azure AI Document Intelligence Dotnet next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure AI Document Intelligence Dotnet compared with similar skills
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Azure AI Document Intelligence Dotnet this skillmicrosoft/skills3.1k6 repos~3kAutomated safety check: PassMIT
Extracting Structured DataGAIK-project/gaik-toolkit100—~3.2kAutomated safety check: PassMIT
Doc ProcessLeoYeAI/openclaw-master-skills2.2k—~5.2kAutomated safety check: NotesMIT
Form Fillingplatonai/Browser41.2k—~1.1kAutomated safety check: PassApache-2.0
Glmocr SDKzai-org/GLM-skills475—~2.7kAutomated safety check: NotesApache-2.0
Veryfi Documents AILeoYeAI/openclaw-master-skills2.2k—~6.1kAutomated safety check: PassMIT

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Questions about Azure AI Document Intelligence Dotnet

What does Azure AI Document Intelligence Dotnet do?

Azure AI Document Intelligence SDK for .NET. An agent skill from microsoft/skills. Azure AI Document Intelligence Dotnet is an agent skill from microsoft/skills, published by the product's own GitHub organization.NET.

When should I use Azure AI Document Intelligence Dotnet?

Azure AI Document Intelligence Dotnet fits situations like: invoice processing; receipt extraction; ID document analysis; custom document models.

How do I install Azure AI Document Intelligence Dotnet in Claude Code?

Run `npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a claude-code`. Or copy the skill folder (.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet in microsoft/skills) into .claude/skills/azure-ai-document-intelligence-dotnet in your project. Claude Code loads it when a task matches its description.

How do I install Azure AI Document Intelligence Dotnet in Codex?

Run `npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a codex`. Or copy the skill folder (.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet in microsoft/skills) into .agents/skills/azure-ai-document-intelligence-dotnet in your project. Codex loads it when a task matches its description.

Can I use Azure AI Document Intelligence Dotnet in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-ai-document-intelligence-dotnet, .gemini/skills/azure-ai-document-intelligence-dotnet, .github/skills/azure-ai-document-intelligence-dotnet and .opencode/skills/azure-ai-document-intelligence-dotnet in your project.

What does Azure AI Document Intelligence Dotnet need to run?

Going by SKILL.md and its folder, Azure AI Document Intelligence Dotnet needs the command-line tools its instructions call (dotnet) and credentials named AZURE_TOKEN_CREDENTIALS and DOCUMENT_INTELLIGENCE_API_KEY. Our summary lists: A credential in DOCUMENT_INTELLIGENCE_API_KEY.

Does Azure AI Document Intelligence Dotnet access the network?

SKILL.md names 5 domains. In commands or code: learn.microsoft.com; the agent is likely to contact it when it follows the instructions. As links in the text: nuget.org, github.com, documentintelligence.ai.azure.com and aka.ms. This is read from the text; nothing was executed.

Is Azure AI Document Intelligence Dotnet safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure AI Document Intelligence Dotnet use?

Azure AI Document Intelligence Dotnet is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure AI Document Intelligence Dotnet use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Azure AI Document Intelligence Dotnet?

Skills that share tags, products or a category with Azure AI Document Intelligence Dotnet: Extracting Structured Data (GAIK-project/gaik-toolkit, 100 stars), Doc Process (LeoYeAI/openclaw-master-skills, 2.2k stars), Form Filling (platonai/Browser4, 1.2k stars) and Glmocr SDK (zai-org/GLM-skills, 475 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure AI Document Intelligence Dotnet?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/skills, which has 3,086 GitHub stars. The repository holds 150 skills in this directory. The repository was last updated on October 6, 2026.

Source: microsoft/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.