/microsoft-foundry

name: microsoft-foundry
description: "Deploy, evaluate, fine-tune, and manage Foundry agents end-to-end with azd: hosted agent scaffold/run/deploy, prompt agent create, batch eval, continuous eval, prompt optimizer, Agent Optimizer scaffold, agent.yaml, dataset curation from traces, model fine-tuning (SFT/DPO/RFT). USE FOR: azd ai agent, azd provision/deploy, deploy agent, hosted agent, create agent, add tool to agent, invoke agent, evaluate agent, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, agent optimizer, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, AI Services, create Foundry resource, provision, knowledge index, customize deployment, onboard, availability, fine-tune, SFT, DPO, RFT, training-data, grader, distillation, fine-tuned model, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare)."
license: MIT
metadata:
  author: Microsoft
  version: "1.2.4"

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

Follow each applicable subsection below before starting its corresponding action or workflow.

Dependency Check and Setup

**MANDATORY:** As the first step after this skill loads, run the dependency check and setup script below from this skill's root and wait for it to finish before continuing. The script checks first and installs only missing dependencies; it does not reinstall dependencies that are already available.

**You MUST complete this check before reading or entering any sub-skill, workflow, or workflow-specific reference.**

./scripts/check-and-setup-dependencies.sh     # macOS / Linux
./scripts/check-and-setup-dependencies.ps1    # Windows (pwsh)

Strictly follow the script output for subsequent actions.

Workflow Guidance

**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.

Foundry MCP

**MANDATORY:** Before using Foundry MCP operations, call the Azure MCP `foundry` tool and inspect the available Foundry MCP tools and related parameters. Treat this as the discovery/help step for MCP-based workflows.

azd

**MANDATORY:** Before executing ANY azd command, you MUST read [azd-guidance](foundry-agent/azd-guidance/azd-guidance.md) and strictly follow the shared rules defined in it, especially the `AZURE_DEV_USER_AGENT` setting rules.

Sub-Skills

This skill includes specialized sub-skills for specific workflows. **When a sub-skill matches the task, strictly follow its workflow:**

| Sub-Skill | When to Use | Reference | |-----------|-------------|-----------| | **deploy** | Deploy hosted agents to Foundry, smoke-test a deployment, create or update prompt agents, and manage agent versions and multi-environment deploys. | [deploy](foundry-agent/deploy/deploy.md) | | **cicd** | Set up a CI/CD deployment pipeline for a Foundry agent. | [cicd](foundry-agent/cicd/cicd.md) | | **invoke** | Send messages to an agent, single or multi-turn conversations | [invoke](foundry-agent/invoke/invoke.md) | | **routine** | Schedule or event-trigger Foundry agents with routines; use `azd` for CRUD, enable/disable, manual dispatch, and viewing past runs, or define routines in `azure.yaml`. | [routine](foundry-agent/routine/routine.md) | | **invocations-ws** | Build, deploy, and connect to hosted agents that speak the `invocations_ws` duplex WebSocket protocol — voice agents, real-time streams, and signaling for out-of-band media transports. | [invocations-ws](foundry-agent/invocations-ws/invocations-ws.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 (quick start)** | Create a new hosted Foundry agent from scratch end-to-end — scaffold, provision or use an existing Foundry project, deploy, and smoke-test. Do not use for any work on existing code. For anything not covered by the quickstart, use **create**. | [create/quick-start-hosted.md](foundry-agent/create/quick-start-hosted.md) | | **create** | Use when the standard end-to-end happy path (quick start) doesn't fit. Create a new Foundry agent, update code of an existing agent, continue development of an existing agent, wire connections at scaffold time, use advanced setup or A2A (Agent2Agent), or recover from a failed quickstart run. | [create](foundry-agent/create/create-hosted.md) | | **agent-optimizer** | Make existing Python hosted-agent code optimization-ready, configure eval.yaml, run Agent Optimizer jobs, apply candidates locally, and deploy through azd after review. | [agent-optimizer](foundry-agent/agent-optimizer/agent-optimizer.md) | | **eval-datasets** | Harvest production traces into evaluation datasets, manage dataset versions and splits, track evaluation metrics over time, detect regressions, and