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azure-ai-foundry-operations-2026

Implement and operate Azure AI Foundry and Microsoft Foundry workloads with explicit identity, deployment, model versioning, safety, and agent-service controls.

Skill by Biomedical OS Team

IndexedMIT★ 36
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Implement and operate Azure AI Foundry and Microsoft Foundry workloads with explicit identity, deployment, model versioning, safety, and agent-service controls. Use when deploying model endpoints, migrating model versions, or setting up production guardrails on Azure.

Use cases: cloud, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/azure-ai-foundry-operations-2026

What's inside

Skill name
azure-ai-foundry-operations-2026
Description
Implement and operate Azure AI Foundry and Microsoft Foundry workloads with explicit identity, deployment, model versioning, safety, and agent-service controls. Use when deploying model endpoints, migrating model versions, or setting up production guardrails on Azure.
License
MIT
Metadata
author: Biomedical OS Team · version: 2026.04
Instructions
26 lines in SKILL.md · view on GitHub

Agent Skills spec issues

  • name: "azure-ai-foundry-operations-2026" does not match folder "Azure_AI_Foundry_Operations_2026"
  • allowed-tools: must be a space-separated string

Files (3)

  • SKILL.md
  • openai.yaml · agents/
  • sources.md · references/

SKILL.md (first lines)

# Azure AI Foundry Operations (2026)

Use this skill when Azure AI Foundry or Microsoft Foundry is the operating surface, not just a generic OpenAI-compatible endpoint.

## Workflow

1. Confirm the service surface first: Azure AI Foundry resource, Azure OpenAI deployment, or Foundry Agent Service.
2. Pin the identity model explicitly: Entra ID, managed identity, or service principal.
3. Pin API versions, deployment names, and region strategy before coding.
4. Enable safety, telemetry, and evaluation controls before broader rollout.
5. Validate region availability, disaster recovery, and data-handling assumptions in staging.

## Guardrails

- Track the Azure AI Foundry to Microsoft Foundry naming transition and document which portal and API surface the team actually uses.
- Keep deployment names and model versions explicit; do not rely on implicit defaults.
- Treat content safety, agent evaluators, and Foundry Agent Service as separate control planes.
- Record identity method, data residency assumptions, and failover region in validation notes.

## Output Requirements

- State the Azure service surface and model deployment strategy.
- State the identity/auth method and secret-handling policy.
- State one safety or evaluation control and one regional failover mechanism.

From mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills-, MIT.

More from mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills-

Signals

Stars
36
Forks
8
Open issues
0
Last commit (this folder)
Apr 20, 2026 (6 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
2026.04
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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azure-ai-foundry-operations-2026 skill. Agent Mart. https://agentmart.dev/skills/mdbabumiamssm-azure-ai-foundry-operations-2026 (last updated 2026-10-24)