Dev & Engineering ✓ Microsoft · Official microsoft-foundryazureazdmodel-fine-tuningagent-evaluationrbacmcp

Microsoft Foundry Agent Skill

Manage the Microsoft Foundry agent lifecycle with azd and Foundry MCP—from scaffolding and deployment to evaluation and optimization.

FollowSkills review · FSRS-2.0
Not recommended
47/ 100 5-point scale 2.4 / 5
Trust12 / 25 · 2.4/5

The evidence requires Foundry MCP discovery, mandatory workflow-document reads, scoped workspace resolution, and user prompts for missing configuration. It does not clearly specify per-operation permissions, sensitive-data handling, confirmation of external effects, rollback, or complete data-flow disclosure, so points are deducted. No red-line risk is evident.

Reliability7 / 20 · 1.8/5

The evidence provides workflow routing, prechecks, context-resolution rules, and some failure guidance. However, key sub-skills, scripts, and MCP parameters are not fully supplied, and static review cannot reproduce deployment, evaluation, or troubleshooting paths, so points are deducted.

Adaptability9 / 15 · 3.0/5

USE FOR/DO NOT USE FOR boundaries, workflow tables, and multiple Foundry scenarios provide a reasonably clear audience and trigger surface. The scope is very broad, trigger precision and non-fit limits depend on unavailable sub-skills, and there is no evidence for Chinese support or mainland-China network reachability, so points are deducted.

Convention9 / 15 · 3.0/5

The evidence includes YAML metadata, MIT licensing, a version, layered sub-skills, installation guidance, examples, and limitation notes. The finetuning sub-skill has version 0.0.0-placeholder, while changelog, maintenance ownership, update path, and documentation consistency are incomplete, so points are deducted.

Effectiveness6 / 15 · 2.0/5

The evidence covers core lifecycle tasks from resource creation through deployment, invocation, evaluation, fine-tuning, and troubleshooting, with commands, formats, and error guidance. No directly usable output or execution result for this skill's key paths is supplied, so environment adaptation and review burden remain material.

Verifiability4 / 10 · 2.0/5

The repository context includes real CI workflows and test code, but the supplied material does not establish coverage of this microsoft-foundry skill's key paths and provides no third-party execution results or independent corroboration. Static calibration therefore supports only limited credit.

Evidence confidence:Low Reviewed Jul 20, 2026 Reviewed revision 9ccaf7c3704a
Before you use it
  • This assessment is static only; no MCP tools, azd, Azure CLI, scripts, or deployment workflows were executed.
  • Before use, verify every linked sub-skill, script, MCP parameter, permission scope, cost impact, data residency requirement, and rollback plan.
  • The fine-tuning documentation contains version 0.0.0-placeholder, and some capabilities may require preview access or feature flags; do not treat examples as production validation.
  • No evidence was supplied for Chinese-language support or reachability from mainland-China networks.
See the full review method →

What it does & when to use it

This language-agnostic router skill is the Microsoft Foundry entry point in the Microsoft Agent Skills repository. It maps requests to specialized workflows for agent development, infrastructure, model deployment, evaluation, monitoring, permissions, networking, troubleshooting, and fine-tuning. It requires Azure tooling, Foundry MCP access, and local project context such as azure.yaml or .foundry metadata for many workflows. It is a strong fit for teams operating Microsoft Foundry workloads, but not a general Azure deployment or Azure Functions skill.

Reads azure.yaml, azd environment values, .foundry metadata, and eval.yaml when configuration context is needed; discovers available Foundry MCP operations through the Azure MCP foundry tool; routes requests to sub-skills for deployment, invocation, evaluation, tracing, troubleshooting, project and resource creation, model deployment, quota, RBAC, private networking, or fine-tuning; uses or guides azd, Azure CLI, and Foundry MCP workflows for agent scaffolding, deployment, invocation, evaluation, continuous monitoring, prompt optimization, model customization, and resource configuration; and maintains applicable .foundry metadata, dataset, evaluator, suite, and result caches.

  1. An Azure developer needs to scaffold, deploy, and smoke-test a new Microsoft Foundry hosted agent.
  2. An engineering team has existing agent code and needs to deploy or redeploy it with azd and verify the resulting version.
  3. An AI team wants batch evaluation, continuous production evaluation, prompt optimization, or evaluation datasets generated from production traces.
  4. A platform engineer needs model deployment, regional capacity or quota guidance, or help diagnosing a Foundry deployment failure.
  5. An Azure administrator needs Foundry project setup, RBAC, managed identity, service-principal, or network-isolation guidance.
  6. A model engineer needs SFT, DPO, or RFT workflows covering training data, graders, checkpoints, deployment, and evaluation.

Pros & cons

Pros
  • Covers the Foundry agent lifecycle from creation and deployment through invocation, evaluation, optimization, and troubleshooting.
  • Includes infrastructure and operations topics such as model deployment, quota, RBAC, private networking, and fine-tuning.
  • Provides explicit intent-routing rules, anti-triggers, and workflow-specific pre-execution requirements.
  • MIT licensed, with repository-level testing and evaluation automation described in the README.
Limitations
  • It is a router skill, so many concrete procedures depend on sub-skill documents not included in the supplied material.
  • It explicitly depends on Azure CLI, azd, MCP, and Foundry project context, so it is not a general-purpose agent skill for non-Azure environments.
  • The source does not establish that every platform, region, model, or preview feature is validated.
  • The README’s test-coverage summary describes the repository collection and does not prove independent coverage for this specific skill.

How to install

From the target Agent configuration environment, run npx skills add microsoft/skills and select the needed skills in the wizard. Skills are installed into the selected Agent directory, such as .github/skills/ for GitHub Copilot. The collection can also be installed by copying a specific skill directory or by installing the azure-skills plugin through Copilot CLI. The supplied source does not document a separate installer command for selecting only .github/plugins/azure-skills/skills/microsoft-foundry/.

How to use

In a coding Agent with Azure, azd, Foundry MCP, and the target project configured, make a concrete request such as “create and deploy a Microsoft Foundry hosted agent” or “evaluate and optimize this Foundry agent’s prompt.” The skill first discovers Foundry MCP tools, then requires the matching workflow document to be read before execution. The supplied source does not provide complete commands, credential setup, or parameter examples for every sub-skill.

FAQ

Is this a general Azure deployment skill?
No. The SKILL.md excludes general Azure deployment and Azure preparation, as well as Azure Functions and App Service, and directs those requests elsewhere.
What permissions or credentials are required?
The source shows workflows involving Foundry resources, RBAC, role assignments, managed identities, and service principals, but it does not define one minimum permission set. Requirements vary by workflow.
Can it work with private-network Foundry projects?
It includes a private-network sub-skill for network-isolation questions and VNet-isolated deployment. However, the source states that Foundry MCP tools cannot reach a VNet-isolated project.
Does it support model fine-tuning?
Yes. It covers SFT, DPO, and RFT workflows, including training data, graders, checkpoints, deployment, and evaluation. Detailed procedures are not included in the supplied main SKILL.md.

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