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Expert knowledge for Microsoft Foundry Classic (aka Azure AI Foundry classic) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment.
Passed 6 of 12 test cases with the skill, and 2 of 12 without it.
and 9 more in the full report
8 fixed3 passed either way12 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
We need to protect our deployed chat applications against indirect prompt injections and jailbreak attacks in user content. Which safety feature should be configured in content filters, and what is the documentation link?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends enabling Prompt Shields within content filtering configurations. | Passed | Passed |
| Includes the documentation URL https://learn.microsoft.com/en-us/azure/foundry-classic/openai/concepts/content-filter-prompt-shields for Prompt Shields documentation. | Missed | Passed |
The instructions your model reads when the skill loads.
This skill provides expert guidance for Microsoft Foundry Classic. 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.
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 | L37-L46 | Diagnosing and fixing Foundry classic issues: prompt flow compute, deployments/monitoring, private endpoints, Azure OpenAI (incl. fine-tuning), risks & safety alerts, and known portal bugs. |
| Best Practices | L47-L61 | Guidance on designing system/safety messages, managing tokens, latency, throughput, fine-tuning (incl. vision), On Your Data, and evaluating/operating Foundry chat apps. |
| Decision Making | L62-L89 | Model and platform decision guides: choosing Foundry/Azure OpenAI models, regions, deployments, billing and PTU sizing, migrations, lifecycle/retirement, DR, and SDK/endpoint options. |
| Architecture & Design Patterns | L90-L96 | Designing multi-agent architectures, configuring Foundry Agent Service for resilience, and understanding model router behavior, failover, and disaster recovery strategies. |
| Limits & Quotas | L97-L113 | Quotas, rate limits, and regional availability for Foundry Agents, Models, Claude, and Azure OpenAI, plus how to manage, increase, and use dynamic/provisioned throughput and batch limits |
| Security | L114-L158 | Security, privacy, and compliance for Foundry: RBAC/Entra auth, managed networks/Private Link, CMK and storage, Azure Policy guardrails, content filters/PII, and Azure OpenAI/Claude protections |
| Configuration | L159-L209 | Configuring, monitoring, and evaluating Foundry classic agents/models, including networking, storage, compute, Azure OpenAI, RAG, safety, tracing, and continuous quality/usage monitoring. |
| Integrations & Coding Patterns | L210-L307 | Patterns and code for integrating Foundry/Agents with Azure AI Search, Bing, SharePoint, MCP/OpenAPI tools, Azure OpenAI (chat, audio, vision, fine-tuning), and external data/SDKs like LangChain, SK, and RAG. |
| Deployment | L308-L327 | Deploying Foundry hubs/models at scale: regions, deployment types, Bicep/Terraform/CLI, managed and serverless compute, HF models, fine-tunes, evaluations, and region feature support |
| Topic | URL |
|---|---|
| Troubleshoot Prompt Flow compute session issues in Foundry | https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/prompt-flow-troubleshoot |
| Troubleshoot Foundry deployments and monitoring issues | https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/troubleshoot-deploy-and-monitor |
| Troubleshoot Foundry private endpoint connection errors | https://learn.microsoft.com/en-us/azure/foundry-classic/how-to/troubleshoot-secure-connection-project |
| Troubleshoot Azure OpenAI fine-tuning in Foundry classic | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/fine-tuning-troubleshoot |
| Monitor and troubleshoot Risks & Safety in Foundry | https://learn.microsoft.com/en-us/azure/foundry-classic/openai/how-to/risks-safety-monitor |
| Resolve known issues in Microsoft Foundry classic portal | https://learn.microsoft.com/en-us/azure/foundry-classic/reference/foundry-known-issues |
| Topic | URL |
test cases passed, vs 2 / 12 without
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