azure-ai-document-intelligence-dotnet
Build .NET Document Intelligence Workflows
Document extraction in .NET requires correct Azure models, authentication, and result handling. This skill provides focused C# workflows for analysis, classification, and custom model management.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "azure-ai-document-intelligence-dotnet" from https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-dotnet.md and its manifest at https://skillstore.io/api/skills/sickn33-azure-ai-document-intelligence-dotnet/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "azure-ai-document-intelligence-dotnet". Analyze an invoice from a URI and list important fields.
Expected outcome:
- Recommended model: prebuilt-invoice.
- Extract VendorName, InvoiceTotal, and Items only after checking each field type.
- Review confidence values before sending results to accounting.
Using "azure-ai-document-intelligence-dotnet". Outline a custom model training workflow for fixed-layout forms.
Expected outcome:
Use the administration client with a Blob Storage SAS source and a unique model identifier. Select template mode and review the completed model schema.
Using "azure-ai-document-intelligence-dotnet". Explain how to classify a document with an existing classifier.
Expected outcome:
Provide the classifier identifier and document URI, wait for completion, then inspect each document type and confidence value.
Security Audit
SafeAll 63 static findings are false positives caused by Markdown code fences, inline code, placeholder URLs, reference links, and documented environment-variable usage. The skill contains no executable scripts, embedded credentials, suspicious network destinations, prompt injection, or intent to exfiltrate data.
Risk Factors
⚙️ External commands (50)
🌐 Network access (11)
🔑 Env variables (2)
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<iframe src="https://skillstore.io/embed/skills/sickn33-azure-ai-document-intelligence-dotnet.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). azure-ai-document-intelligence-dotnet security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-dotnet/audits/5BibTeX citation
@techreport{sickn33-sickn33-azure-ai-document-intelligence-dotnet-2026,
author = {sickn33},
title = {azure-ai-document-intelligence-dotnet security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-dotnet/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "azure-ai-document-intelligence-dotnet security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-azure-ai-document-intelligence-dotnet/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-azure-ai-document-intelligence-dotnet:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Automate invoice intake
Extract vendor names, totals, and line items for an accounting workflow.
Index document archives
Extract page text, tables, and structure for search and downstream processing.
Train specialized document models
Build custom models and classifiers for organization-specific forms and document types.
Try These Prompts
Show me how to configure a .NET console app with Azure AI Document Intelligence using DefaultAzureCredential and environment variables.
Create a C# workflow that analyzes an invoice URI and safely reads vendor, total, and line item fields with confidence checks.
Design a C# routine that extracts page text and tables with prebuilt-layout, including clear handling for failed Azure requests.
Plan an advanced .NET pipeline that builds a custom neural model, creates a classifier, validates confidence, and manages model lifecycle operations.
Best Practices
- Prefer DefaultAzureCredential for production and use a custom Azure resource subdomain.
- Reuse client instances because the Azure SDK clients are thread-safe.
- Check field and classification confidence before accepting extracted values.
Avoid
- Do not embed API keys or SAS tokens in source code.
- Do not treat example URLs as production document locations.
- Do not delete models without confirming the identifier and lifecycle policy.