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Expert knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment.
Passed 5 of 11 test cases with the skill, and 5 of 11 without it.
3 fixed6 passed either way9 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am setting up a containerized hosted agent in Microsoft Foundry and need to create the declaration file for agent metadata, tools, and runtime specs. Should I put my tool definitions and environment variables into docker-compose.yml or use the specialized agent manifest schema?
| Checked | Without skill | With skill |
|---|---|---|
| The response recommends using agent.yaml for defining hosted agent configuration. | Missed | Passed |
| The response explains specifying tools within the agent manifest file. | Passed | Passed |
The instructions your model reads when the skill loads.
This skill provides expert guidance for Microsoft Foundry. 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-L49 | Diagnosing and fixing Foundry agent issues: health checks, publishing to Copilot/Teams, auth errors, data loss recovery, evaluation/observability, Azure OpenAI HTTP/webhook errors, and known workarounds. |
| Best Practices | L50-L72 | Best practices for building, operating, and optimizing Foundry agents and Azure OpenAI (voice, tools, routing, prompts, safety, HA, performance, monitoring, fine-tuning, and recovery). |
| Decision Making | L73-L121 | Planning and decision guides for models, agents, networking, costs, migrations, lifecycle/retirement, regions (incl. Gov), and choosing the right Foundry capabilities, SDKs, and integrations |
| Architecture & Design Patterns | L122-L131 | Designing scalable, resilient Foundry agents: networking in BYO VNets, runtime/component choices, data isolation, shared sessions, auto-trigger routines, and toolbox search patterns. |
| Limits & Quotas | L132-L154 | Quotas, limits, and cost controls for agents, models, vector/durable stores, AI Gateway, Azure OpenAI, rate/TPM caps, sessions/timeouts, and region-specific capacity. |
| Security | L155-L208 | Security, identity, and governance for Foundry: auth/RBAC, Entra, networking, isolation, guardrails, data privacy, trace control, and secure integration of agents, tools, and MCP servers. |
| Configuration | L209-L306 | Configuring Microsoft Foundry agents, projects, models, networking, storage, security, monitoring, evaluations, and tooling (azd, Claude, Azure OpenAI) for deployment and operations |
| Integrations & Coding Patterns | L307-L403 | Patterns and APIs for integrating Foundry agents and models with tools, MCP, voice/telephony, search, evaluations, OpenTelemetry, Azure OpenAI/Responses, and external frameworks like LangChain. |
| Deployment | L404-L431 | Deploying and operating Foundry agents and models: infrastructure (azd, Bicep, Terraform), CI/CD, regional/DR setup, container/registry config, evaluations, and healthcare/open-source model deployments. |
test cases passed, vs 5 / 11 without
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