name: microsoft-foundry-tools
description: Expert knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Content Moderator, Content Safety, Content Understanding analyzers, REST/.NET APIs, or document extraction workloads, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).
compatibility: Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata:
generated_at: "2026-06-28"
generator: "docs2skills/1.0.0"
Microsoft Foundry Tools 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.
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
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 | 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-L55 | Guidance for choosing and migrating between Azure AI/Foundry content tools (Content Moderator, Content Safety, Content Understanding), including feature comparisons and pricing/usage planning. |
| Architecture & Design Patterns | L56-L60 | Guidance on choosing and configuring deployment options (serverless, managed, custom) for Content Understanding models, including trade-offs, scalability, and integration patterns. |
| Limits & Quotas | L61-L68 | 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 | L69-L73 | Securing Azure Content Understanding analyzers and data: auth options, network isolation, encryption, access control, and best practices for protecting analyzer inputs/outputs. |
| Configuration | L74-L83 | Configuring and customizing Content Understanding analyzers (prebuilt and custom), document layout, face detection, and cross-resource capacity settings. |
| Integrations & Coding Patterns | L84-L98 | Using Content Moderator and Content Understanding via REST/.NET: text/image/video moderation, term lists, multimodal analysis, and consuming Markdown/structured outputs |
Troubleshooting
Best Practices
Decision Making
Architecture & Design Patterns
Limits & Quotas
Security
Configuration
Integrations & Coding Patterns