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Provides expert guidance for Microsoft Foundry Tools (Azure AI/Cognitive Services) including troubleshooting, best practices, architecture, and coding patterns for Content Moderator, Content Understanding, document extraction, and face detection.
How this skill is triggered — by the user, by Claude, or both
Slash command
/azure-agent-skills:microsoft-foundry-toolsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides expert guidance for Microsoft Foundry Tools. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.
This skill provides expert guidance for Microsoft Foundry Tools. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L36-L40 | Troubleshooting steps and FAQs for Content Understanding features, including diagnosing model issues, configuration problems, and resolving common errors in content analysis workflows. |
| Best Practices | L41-L46 | Guidance on improving Content Understanding accuracy, grounding and confidence in document extraction, and migrating from preview to GA Content Understanding APIs. |
| Decision Making | L47-L54 | Guidance on choosing and migrating Azure AI/Foundry document processing and Content Understanding tools, plus estimating and planning their pricing. |
| Architecture & Design Patterns | L55-L59 | Guidance on choosing and configuring deployment options (serverless, managed, custom) for Content Understanding models, including trade-offs, scalability, and integration patterns. |
| Limits & Quotas | L60-L67 | Quotas, limits, and supported languages for Content Moderator image/list APIs and Content Understanding, plus .NET samples showing how to stay within list and usage limits. |
| Security | L68-L72 | Securing Azure Content Understanding analyzers and data: auth options, network isolation, encryption, access control, and best practices for protecting analyzer inputs/outputs. |
| Configuration | L73-L82 | Configuring and customizing Content Understanding analyzers (prebuilt and custom), document layout, face detection, and cross-resource capacity settings. |
| Integrations & Coding Patterns | L83-L97 | Using Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, term lists, multimodal analysis, and consuming Markdown/structured outputs |
| Topic | URL |
|---|---|
| Troubleshoot and answer FAQs for Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/faq |
| Topic | URL |
|---|---|
| Apply best practices for Content Understanding accuracy | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/best-practices |
| Improve document extraction with confidence and grounding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement |
| Topic | URL |
|---|---|
| Choose Azure AI tools for document processing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/choosing-right-ai-tool |
| Choose between Foundry and Content Understanding Studio features | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/foundry-vs-content-understanding-studio |
| Migrate Content Understanding from preview to GA APIs | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/migration-preview-to-ga |
| Estimate and plan Content Understanding pricing | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/pricing-explainer |
| Topic | URL |
|---|---|
| Select model deployment options for Content Understanding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/models-deployments |
| Topic | URL |
|---|---|
| Use Content Moderator image lists within quota limits | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/image-lists-quickstart-dotnet |
| Use supported languages in Content Moderator API | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/language-support |
| Apply Content Moderator .NET samples with list limits | https://learn.microsoft.com/en-us/azure/ai-services/content-moderator/samples-dotnet |
| Content Understanding service quotas and limits reference | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/service-limits |
| Topic | URL |
|---|---|
| Secure Azure Content Understanding analyzers and data | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/concepts/secure-communications |
npx claudepluginhub microsoftdocs/agent-skills --plugin azure-agent-skillsExpert guidance for Azure AI Document Intelligence: troubleshooting, best practices, decision-making, architecture, deployment, security, and coding patterns. Use when working with AnalyzeDocument APIs, custom models, containers, or Logic Apps/Functions.
Queries official Microsoft docs via MCP server or mslearn CLI for concepts, tutorials, configuration options, limits, quotas, best practices on Azure, .NET, M365, Windows, Power Platform.
Governs Azure AI Foundry operations: resource vs project boundaries, RBAC, quota, network isolation, logging, and safe MCP-backed read/write execution.