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Expert knowledge for Azure Content Understanding in Foundry Tools development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns.
3 of 22 test cases passed with the skill.
Tokens, turns and time describe resource use, not a dollar price.
Lift withheld: 4 comparable cases; this report requires 8.
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This skill provides expert guidance for Azure Content Understanding in 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 | Using diagnostics from the Content Understanding REST API to investigate failures, interpret error codes, and troubleshoot processing or configuration issues. |
| Best Practices | L41-L46 | Improving Content Understanding accuracy using layout, labels, and feedback, plus using confidence scores and grounding to validate and refine document analysis results. |
| Decision Making | L47-L55 | Guidance on choosing Azure AI/Foundry tools, model deployments, and Studio vs Foundry; migrating Content Understanding from preview to GA; and estimating/optimizing pricing. |
| Architecture & Design Patterns | L56-L62 | Guidance on when to use agentic mode, how to design RAG-based document solutions, and how to build RPA workflows using Azure Content Understanding. |
| Limits & Quotas | L63-L68 | Guidance on safe use of synchronous Content Understanding calls plus detailed quotas, rate limits, and throughput constraints for Foundry Tools. |
| Security | L69-L74 | Configuring security for Content Understanding: setting guardrails on analyzer outputs, securing analyzers and data, access control, and safe handling of sensitive content. |
| Configuration | L75-L88 | Configuring and customizing Content Understanding analyzers, classifiers, workflows, and audiovisual/Markdown outputs, including creating, copying, and managing custom analyzers and Foundry resources. |
| Integrations & Coding Patterns | L89-L94 | Patterns and code samples for calling Content Understanding via REST/SDKs, integrating with Microsoft Agent Framework/LangChain, and implementing agentic workflows. |
| Topic | URL |
|---|---|
| Use diagnostics from Content Understanding REST API | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/how-to/retrieve-diagnostics |
| 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 analysis with confidence and grounding | https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/document/analyzer-improvement |
| Topic | URL |
test cases passed with the skill
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