Expert knowledge for Azure AI Document Intelligence development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing custom models, calling AnalyzeDocument APIs, running containers/offline, or migrating to v4.0, and other Azure AI Document Intelligence related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Search (use azure-cognitive-search), Azure AI C…
Expert knowledge for Azure AI Document Intelligence development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment.
Use when designing custom models, calling AnalyzeDocument APIs, running containers/offline, or migrating to v4.0, and other Azure AI Document Intelligence related development tasks.
Not for Azure AI Vision (use azure-ai-vision), Azure AI Search (use azure-cognitive-search), Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer).
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LicenseLICENSE
Default branchmain
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Skill metadata
Parsed from SKILL.md frontmatter.
CompatibilityRequires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
More metadata
generated_at
2026-08-31
generator
docs2skills/1.0.0
Package contents
Files included with this skill beyond the listing page.
skill mdSKILL.md10,649 B
docsSUMMARY.md623 B
History
First seen on skills.sh
First recorded snapshot · 165 installs
SKILL.md
Azure AI Document Intelligence Skill
This skill provides expert guidance for Azure AI Document Intelligence. Covers troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
How to Use This Skill
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use readfile with the specified lines. For categories with file links (e.g., [security.md](security.md)), use readfile on the linked reference file
IMPORTANT for Agent: If metadata.generatedat is more than 3 months old, suggest the user pull the latest version from the repository. If mcpmicrosoftdocs tools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
Preferred: Use mcpmicrosoftdocs:microsoftdocs_fetch with query string from=learn-agent-skill. Returns Markdown.
Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.
Category Index
Category
Lines
Description
Troubleshooting
L36-L42
Diagnosing latency, understanding and fixing Document Intelligence API error codes, and handling known service issues and limitations.
Best Practices
L43-L54
Guidance on designing, training, labeling, composing, and maintaining custom/classification/template models to maximize Document Intelligence accuracy and confidence
Decision Making
L55-L61
Choosing the right Document Intelligence model, estimating and optimizing usage/costs, and planning or executing migration to v4.0 from earlier versions.
Limits & Quotas
L62-L71
Capacity limits, quotas, scaling with add-ons and batch analysis, container image tags, and supported OCR languages/locales and prebuilt model language coverage.
Security
L72-L79
Securing Document Intelligence resources: creating SAS tokens, configuring data-at-rest encryption with customer-managed keys, and using managed identities and VNETs for secure access.
Configuration
L80-L84
How to configure and run Azure Document Intelligence in containers, including environment settings, networking, storage, licensing, and deployment options for on-premises or hybrid scenarios.
Integrations & Coding Patterns
L85-L94
Using Document Intelligence APIs/SDKs, interpreting AnalyzeDocument/Markdown outputs, and integrating with Azure Functions or Logic Apps for end-to-end document processing workflows
Deployment
L95-L101
Running Document Intelligence in Docker/offline, deploying the labeling tool, and setting up resilient, disaster‑ready deployments for models and services