Extracting Structured Data
GAIK-project/gaik-toolkit
Extracts structured data — fields, tables, line items — out of documents into a validated schema using the gaik toolkit, and designs schemas that stay inside provider limits and produce checkable…
Azure AI Document Intelligence SDK for .NET. An agent skill from microsoft/skills.
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnet --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "azure-ai-document-intelligence-dotnet" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet into .claude/skills/azure-ai-document-intelligence-dotnet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-ai-document-intelligence-dotnet", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnetType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnet --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet .agents/skills/azure-ai-document-intelligence-dotnet && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "azure-ai-document-intelligence-dotnet" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet into .agents/skills/azure-ai-document-intelligence-dotnet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-ai-document-intelligence-dotnet", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnet --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet .cursor/skills/azure-ai-document-intelligence-dotnet && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "azure-ai-document-intelligence-dotnet" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet into .cursor/skills/azure-ai-document-intelligence-dotnet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-ai-document-intelligence-dotnet", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/microsoft/skills.git --path .github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnet --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet .gemini/skills/azure-ai-document-intelligence-dotnet && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "azure-ai-document-intelligence-dotnet" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet into .gemini/skills/azure-ai-document-intelligence-dotnet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-ai-document-intelligence-dotnet", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnetInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet .github/skills/azure-ai-document-intelligence-dotnet && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "azure-ai-document-intelligence-dotnet" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet into .github/skills/azure-ai-document-intelligence-dotnet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-ai-document-intelligence-dotnet", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft/skills --skill azure-ai-document-intelligence-dotnet -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/skills azure-ai-document-intelligence-dotnet --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet .opencode/skills/azure-ai-document-intelligence-dotnet && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "azure-ai-document-intelligence-dotnet" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-dotnet/skills/azure-ai-document-intelligence-dotnet into .opencode/skills/azure-ai-document-intelligence-dotnet/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-ai-document-intelligence-dotnet", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
azure-ai-document-intelligence-dotnetAzure 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. 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.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 354361d. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
dotnetFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
learn.microsoft.comAlso links to:
nuget.orggithub.comdocumentintelligence.ai.azure.comaka.msFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
AZURE_TOKEN_CREDENTIALSDOCUMENT_INTELLIGENCE_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from microsoft/skills at commit 354361d, republished under its MIT licence (© microsoft). 304 words, ~2,972 tokens.
.claude/skills/azure-ai-document-intelligence-dotnet/SKILL.md (or your agent's skills folder).Extract text, tables, and structured data from documents using prebuilt and custom models.
dotnet add package Azure.AI.DocumentIntelligence
dotnet add package Azure.IdentityCurrent Version: v1.0.0 (GA)
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 productionusing 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.
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 | Purpose |
|---|---|
DocumentIntelligenceClient | Analyze documents, classify documents |
DocumentIntelligenceAdministrationClient | Build/manage custom models and classifiers |
| Model ID | Description |
|---|---|
prebuilt-read | Extract text, languages, handwriting |
prebuilt-layout | Extract text, tables, selection marks, structure |
prebuilt-invoice | Extract invoice fields (vendor, items, totals) |
prebuilt-receipt | Extract receipt fields (merchant, items, total) |
prebuilt-idDocument | Extract ID document fields (name, DOB, address) |
prebuilt-businessCard | Extract business card fields |
prebuilt-tax.us.w2 | Extract W-2 tax form fields |
prebuilt-healthInsuranceCard.us | Extract health insurance card fields |
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($" Item: {descField.ValueString}");
}
}
}Uri fileUri = new Uri("https://example.com/document.pdf");
Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
WaitUntil.Completed,
"prebuilt-layout",
fileUri);
AnalyzeResult result = operation.Value;
// Extract text by page
foreach (DocumentPage page in result.Pages)
{
Console.WriteLine($"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($" Cell ({cell.RowIndex}, {cell.ColumnIndex}): {cell.Content}");
}
}Operation<AnalyzeResult> operation = await client.AnalyzeDocumentAsync(
WaitUntil.Completed,
"prebuilt-receipt",
receiptUri);
AnalyzeResult result = operation.Value;
foreach (AnalyzedDocument document in result.Documents)
{
if (document.Fields.TryGetValue("MerchantName", out DocumentField merchantField))
Console.WriteLine($"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}");
}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]}");
}
}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($"Classifier ID: {classifier.ClassifierId}");string classifierId = "my-classifier";
Uri documentUri = new Uri("https://example.com/document.pdf");
var options = new ClassifyDocumentOptions(classifierId, documentUri);
Operation<AnalyzeResult> operation = await client.ClassifyDocumentAsync(
WaitUntil.Completed,
options);
AnalyzeResult result = operation.Value;
foreach (AnalyzedDocument document in result.Documents)
{
Console.WriteLine($"Document type: {document.DocumentType}, confidence: {document.Confidence}");
}// 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($"Model: {modelItem.ModelId}");
}
// Delete model
await adminClient.DeleteModelAsync("my-model-id");| Type | Description |
|---|---|
DocumentIntelligenceClient | Main client for analysis |
DocumentIntelligenceAdministrationClient | Model management |
AnalyzeResult | Result of document analysis |
AnalyzedDocument | Single document within result |
DocumentField | Extracted field with value and confidence |
DocumentFieldType | String, Date, Number, Currency, etc. |
DocumentPage | Page info (lines, words, selection marks) |
DocumentTable | Extracted table with cells |
DocumentModelDetails | Custom model metadata |
BlobContentSource | Training data source |
| Mode | Use Case |
|---|---|
DocumentBuildMode.Template | Fixed layout documents (forms) |
DocumentBuildMode.Neural | Variable layout documents |
WaitUntil.Completed for simplicityConfidence propertyusing Azure;
try
{
var operation = await client.AnalyzeDocumentAsync(
WaitUntil.Completed,
"prebuilt-invoice",
documentUri);
}
catch (RequestFailedException ex)
{
Console.WriteLine($"Error: {ex.Status} - {ex.Message}");
}| SDK | Purpose | Install |
|---|---|---|
Azure.AI.DocumentIntelligence | Document analysis (this SDK) | dotnet add package Azure.AI.DocumentIntelligence |
Azure.AI.FormRecognizer | Legacy SDK (deprecated) | Use DocumentIntelligence instead |
| Resource | URL |
|---|---|
| NuGet Package | https://www.nuget.org/packages/Azure.AI.DocumentIntelligence |
| API Reference | https://learn.microsoft.com/dotnet/api/azure.ai.documentintelligence |
| GitHub Samples | https://github.com/Azure/azure-sdk-for-net/tree/main/sdk/documentintelligence/Azure.AI.DocumentIntelligence/samples |
| Document Intelligence Studio | https://documentintelligence.ai.azure.com/ |
| Prebuilt Models | https://aka.ms/azsdk/formrecognizer/models |
© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
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
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.
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Azure AI Document Intelligence Dotnet this skillmicrosoft/skills | 3.1k | 6 repos | ~3k | Automated safety check: Pass | MIT | |
| Extracting Structured DataGAIK-project/gaik-toolkit | 100 | — | ~3.2k | Automated safety check: Pass | MIT | |
| Doc ProcessLeoYeAI/openclaw-master-skills | 2.2k | — | ~5.2k | Automated safety check: Notes | MIT | |
| Form Fillingplatonai/Browser4 | 1.2k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Glmocr SDKzai-org/GLM-skills | 475 | — | ~2.7k | Automated safety check: Notes | Apache-2.0 | |
| Veryfi Documents AILeoYeAI/openclaw-master-skills | 2.2k | — | ~6.1k | Automated safety check: Pass | MIT |
GAIK-project/gaik-toolkit
Extracts structured data — fields, tables, line items — out of documents into a validated schema using the gaik toolkit, and designs schemas that stay inside provider limits and produce checkable…
LeoYeAI/openclaw-master-skills
Document intelligence: categorize, autofill forms, analyze contracts, scan receipts/invoices, analyze bank statements, parse resumes/CVs, scan IDs/passports (MRZ), summarize medical records, redact…
platonai/Browser4
Automatically fills web forms using provided field data and can optionally submit the form.
zai-org/GLM-skills
Trigger when: (1) User wants to extract text, tables, formulas, or structured data from images/PDFs/scanned documents, (2) User mentions "OCR", "文字识别", "文档解析", (3) User has a document (screenshot…
LeoYeAI/openclaw-master-skills
Real-time OCR and data extraction API by Veryfi (https://veryfi.com).
MicrosoftDocs/mcp
Create agent skills for Microsoft technologies using official documentation.
microsoft/skills
Reference for building on Microsoft Foundry with the azure-ai-projects Python SDK: project clients, versioned agents, evaluations, connections, datasets and indexes.
microsoft/skills
Python guidance for the Azure AI Search SDK covering vector, hybrid and semantic search, index management and indexers, with Entra ID authentication preferred over keys.
microsoft/skills
Covers producer, consumer, and checkpoint-store setup for Azure Event Hubs streaming in Python, with Entra ID auth and partition targeting.
microsoft/skills
Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants.
microsoft/skills
Builds podcast-style audio narration from text with Azure OpenAI's GPT Realtime Mini over WebSocket, from a Python FastAPI backend to a React player.
microsoft/skills
Build dark-themed React applications using Tailwind CSS with custom theming, glassmorphism effects, and Framer Motion animations.
Categories
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.
Azure AI Document Intelligence Dotnet fits situations like: invoice processing; receipt extraction; ID document analysis; custom document models.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.