azure-document-intelligence

# Azure AI Document Intelligence Skill

This skill provides expert guidance for Azure AI Document Intelligence. Covers troubleshooting, best practices, decision making, architecture & design patterns, 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 `read_file` with the specified lines. For categories with file links (e.g., `[security.md](security.md)`), use `read_file` on the linked reference file

> **IMPORTANT for Agent**: If `metadata.generated_at` is more than 3 months old, suggest the user pull the latest version from the repository. If `mcp_microsoftdocs` tools are not available, suggest the user install it: [Installation Guide](https://github.com/MicrosoftDocs/mcp/blob/main/README.md)

This skill requires **network access** to fetch documentation content:
- **Preferred**: Use `mcp_microsoftdocs:microsoft_docs_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 | L37-L43 | Diagnosing and fixing Document Intelligence issues: latency/performance problems, service error codes and meanings, and known Foundry-specific bugs and workarounds. |
| Best Practices | L44-L54 | Improving custom model accuracy and confidence, labeling and table-tagging best practices, training/classification workflows, and managing the full Document Intelligence model lifecycle |
| Decision Making | L55-L60 | Choosing the right Document Intelligence model for your scenario and guidance on upgrading or migrating between different API versions and features. |
| Architecture & Design Patterns | L61-L65 | Guidance on designing disaster recovery, redundancy, and failover strategies for Azure AI Document Intelligence models and deployments. |
| Limits & Quotas | L66-L75 | Quotas, capacity add-ons, throttling behavior, batch scaling, and language/OCR support limits for Document Intelligence (service, custom, and prebuilt models). |
| Security | L76-L83 | Securing Document Intelligence: creating SAS tokens, configuring data-at-rest encryption, and using managed identities and VNets to lock down access to resources. |
| Configuration | L84-L89 | Configuring Document Intelligence containers and building, training, and composing custom models for tailored document processing workflows. |
| Integrations & Coding Patterns | L90-L99 | Using SDKs/REST to call Document Intelligence, handle AnalyzeDocument/Markdown outputs, and integrate with apps, Azure Functions, and Logic Apps for end‑to‑end document workflows |
| Deployment | L100-L106 | Deploying Document Intelligence via Docker/containers, including image tags, offline/disconnected setups, and installing/running the service and sample labeling tool. |

### Troubleshooting
| Topic | URL |
|-------|-----|
| Troubleshoot Azure Document Intelligence latency issues | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/concept/troubleshoot-latency?view=doc-intel-4.0.0 |
| Interpret and resolve Document Intelligence error codes | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/resolve-errors?view=doc-intel-4.0.0 |
| Resolve known Azure Document Intelligence Foundry issues | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/reference/known-issues?view=doc-intel-4.0.0 |

### Best Practices
| Topic | URL |
|-------|-----|
| Improve Document Intelligence accuracy and confidence scores | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/concept/accuracy-confidence?view=doc-intel-4.0.0 |
| Train custom document classification models | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/build-a-custom-classifier?view=doc-intel-4.0.0 |
| Build and train custom Document Intelligence models | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/build-a-custom-model?view=doc-intel-4.0.0 |
| Use labeling tips to optimize Document Intelligence custom models | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/train/custom-label-tips?view=doc-intel-4.0.0 |
| Apply best practices for labeling Document Intelligence training data | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/train/custom-labels?view=doc-intel-4.0.0 |
| Manage Azure Document Intelligence custom model lifecycle | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/train/custom-lifecycle?view=doc-intel-4.0.0 |
| Use supervised table tags for custom template models | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/v21/supervised-table-tags?view=doc-intel-2.1.0 |

### Decision Making
| Topic | URL |
|-------|-----|
| Select the right Azure Document Intelligence model | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/concept/choose-model-feature?view=doc-intel-4.0.0 |
| Decide and migrate between Document Intelligence API versions | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/versioning/migration-guide-overview?view=doc-intel-4.0.0 |

### Architecture & Design Patterns
| Topic | URL |
|-------|-----|
| Design disaster recovery for Document Intelligence models | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/how-to-guides/disaster-recovery?view=doc-intel-4.0.0 |

### Limits & Quotas
| Topic | URL |
|-------|-----|
| Increase Document Intelligence capacity with add-ons | https://learn.microsoft.com/en-us/azure/ai-services/document-intelligen