Microsoft Foundry Skill
This skill helps developers work with Microsoft Foundry resources, covering model discovery and deployment, RAG (Retrieval-Augmented Generation) applications, AI agent creation, evaluation workflows, and troubleshooting.
Sub-Skills
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 |
| project/create |
Creating a new Azure AI Foundry project for hosting agents and models. Use when onboarding to Foundry or setting up new infrastructure. |
project/create/create-foundry-project.md |
| resource/create |
Creating Azure AI Services multi-service resource (Foundry resource) using Azure CLI. Use when manually provisioning AI Services resources with granular control. |
resource/create/create-foundry-resource.md |
| models/deploy-model |
Unified model deployment with intelligent routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI), and capacity discovery across regions. Routes to sub-skills: preset (quick deploy), customize (full control), capacity (find availability). |
models/deploy-model/SKILL.md |
| agent/create/agent-framework |
Creating AI agents and workflows using Microsoft Agent Framework SDK. Supports single-agent and multi-agent workflow patterns with HTTP server and F5/debug support. |
agent/create/agent-framework/SKILL.md |
| quota |
Managing quotas and capacity for Microsoft Foundry resources. Use when checking quota usage, troubleshooting deployment failures due to insufficient quota, requesting quota increases, or planning capacity. |
quota/quota.md |
| rbac |
Managing RBAC permissions, role assignments, managed identities, and service principals for Microsoft Foundry resources. Use for access control, auditing permissions, and CI/CD setup. |
rbac/rbac.md |
💡 Tip: For a complete onboarding flow: project/create → agent/create → agent/deploy. If the user wants to create AND deploy an agent, start with agent/create which can optionally invoke agent/deploy automatically.
💡 Model Deployment: Use models/deploy-model for all deployment scenarios — it intelligently routes between quick preset deployment, customized deployment with full control, and capacity discovery across regions.
SDK Quick Reference
1---2name: microsoft-foundry-23description: Microsoft Foundry Skill4---5# Microsoft Foundry Skill67This skill helps developers work with Microsoft Foundry resources, covering model discovery and deployment, RAG (Retrieval-Augmented Generation) applications, AI agent creation, evaluation workflows, and troubleshooting.89## Sub-Skills1011This skill includes specialized sub-skills for specific workflows. **Use these instead of the main skill when they match your task:**1213| Sub-Skill | When to Use | Reference |14|-----------|-------------|-----------|15| **project/create** | Creating a new Azure AI Foundry project for hosting agents and models. Use when onboarding to Foundry or setting up new infrastructure. | [project/create/create-foundry-project.md](project/create/create-foundry-project.md) |16| **resource/create** | Creating Azure AI Services multi-service resource (Foundry resource) using Azure CLI. Use when manually provisioning AI Services resources with granular control. | [resource/create/create-foundry-resource.md](resource/create/create-foundry-resource.md) |17| **models/deploy-model** | Unified model deployment with intelligent routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI), and capacity discovery across regions. Routes to sub-skills: `preset` (quick deploy), `customize` (full control), `capacity` (find availability). | [models/deploy-model/SKILL.md](models/deploy-model/SKILL.md) |18| **agent/create/agent-framework** | Creating AI agents and workflows using Microsoft Agent Framework SDK. Supports single-agent and multi-agent workflow patterns with HTTP server and F5/debug support. | [agent/create/agent-framework/SKILL.md](agent/create/agent-framework/SKILL.md) |19| **quota** | Managing quotas and capacity for Microsoft Foundry resources. Use when checking quota usage, troubleshooting deployment failures due to insufficient quota, requesting quota increases, or planning capacity. | [quota/quota.md](quota/quota.md) |20| **rbac** | Managing RBAC permissions, role assignments, managed identities, and service principals for Microsoft Foundry resources. Use for access control, auditing permissions, and CI/CD setup. | [rbac/rbac.md](rbac/rbac.md) |2122> 💡 **Tip:** For a complete onboarding flow: `project/create` → `agent/create` → `agent/deploy`. If the user wants to **create AND deploy** an agent, start with `agent/create` which can optionally invoke `agent/deploy` automatically.2324> 💡 **Model Deployment:** Use `models/deploy-model` for all deployment scenarios — it intelligently routes between quick preset deployment, customized deployment with full control, and capacity discovery across regions.2526## SDK Quick Reference2728- [Python](references/sdk/foundry-sdk-py.md)
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