
Microsoft Foundry
Deploy, invoke, evaluate, and troubleshoot Microsoft Foundry agents with Docker, ACR, and observability workflows.
Install
npx skills add https://github.com/microsoft/azure-skills --skill microsoft-foundryWhat is this skill?
- End-to-end Foundry agent deploy, invoke, observe, and trace workflows.
- Sub-skills for batch eval, continuous monitoring, and prompt optimization.
- Integrates with Azure MCP foundry tools for resource discovery.
Adoption & trust: 377k installs on skills.sh; 1.2k GitHub stars; 2/3 security scanners passed (skills.sh audits).
Recommended Skills
Azure Aimicrosoft/azure-skills
Azure Hosted Copilot Sdkmicrosoft/azure-skills
Lark Eventlarksuite/cli
Running Claude Code Via Litellm Copilotxixu-me/skills
Setup Matt Pocock Skillsmattpocock/skills
Codex Petagentspace-so/runcomfy-agent-skills
Journey fit
Common Questions / FAQ
Is Microsoft Foundry safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.
SKILL.md
READMESKILL.md - Microsoft Foundry
# Microsoft Foundry Skill This skill helps developers work with Microsoft Foundry resources, covering model discovery and deployment, complete dev lifecycle of AI agent, evaluation workflows, and troubleshooting. ## Pre-Execution Requirements > **MANDATORY: Before executing ANY workflow, you MUST first call the Azure MCP `foundry` tool and inspect the available Foundry MCP tools and related parameters.** Treat this initial `foundry` call as a discovery/help step. For this skill, Azure MCP `foundry` is the required entry point for Foundry-related MCP operations. ## Sub-Skills > **MANDATORY: Before executing ANY workflow-specific steps, you MUST read the corresponding sub-skill document.** Do not call workflow-specific MCP tools for a workflow without reading its skill document. This applies even if you already know the MCP tool parameters — the skill document contains required workflow steps, pre-checks, and validation logic that must be followed. This rule applies on every new user message that triggers a different workflow, even if the skill is already loaded. This skill includes specialized sub-skills for specific workflows. **Use these instead of the main skill when they match your task:** | Sub-Skill | When to Use | Reference | |-----------|-------------|-----------| | **deploy** | Containerize, build, push to ACR, create/update/clone agent deployments | [deploy](foundry-agent/deploy/deploy.md) | | **invoke** | Send messages to an agent, single or multi-turn conversations | [invoke](foundry-agent/invoke/invoke.md) | | **observe** | Evaluate agent quality, run batch evals, analyze failures, optimize prompts, improve agent instructions, compare versions, set up CI/CD monitoring, and enable continuous production evaluation | [observe](foundry-agent/observe/observe.md) | | **trace** | Query traces, analyze latency/failures, correlate eval results to specific responses via App Insights `customEvents` | [trace](foundry-agent/trace/trace.md) | | **troubleshoot** | View hosted agent logs, query telemetry, diagnose failures | [troubleshoot](foundry-agent/troubleshoot/troubleshoot.md) | | **create** | Create new hosted agent applications. Supports Microsoft Agent Framework, LangGraph, or custom frameworks in Python or C#, across `responses` or `invocations` protocols. | [create](foundry-agent/create/create-hosted.md) | | **faos-optimize** | Convert existing Python agent code to a FAOS (Foundry Agent Optimization Service) optimization-ready version by wiring evaluator-targeted instructions/model/temperature knobs, then stop for review before deployment. | [faos-optimize](foundry-agent/faos-optimize/faos-optimize.md) | | **eval-datasets** | Harvest production traces into evaluation datasets, manage dataset versions and splits, track evaluation metrics over time, detect regressions, and maintain full lineage from trace to de