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Agent skill

Azure AI Deploy

by timothywarner-org in timothywarner-org/claude-code

Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd.

MITAuto-check: notesDevOps & Cloud

Install Azure AI Deploy

skills CLI
$ npx skills add timothywarner-org/claude-code --skill azure-ai-deploy -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install timothywarner-org/claude-code azure-ai-deploy --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/timothywarner-org/claude-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/azure-ai-deploy .claude/skills/azure-ai-deploy && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-ai-deploy
GitHub stars
224
Token cost
~731 tokens
SKILL.md length
319 words
Files
6
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd.

  • Works in 5 steps: Read the auth pattern first → Scaffold the client and config → Set required environment → …
  • Deploying a Python GenAI service
  • SKILL.md covers When to reach for this, Workflow and Conventions
  • Runs Python scripts from its folder; calls uv; reaches contoso-aoai.openai.azure.com

What it does

Azure AI Deploy is an agent skill from timothywarner-org/claude-code. Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd. Use when deploying a Python GenAI service, wiring an Azure OpenAI client without API keys, provisioning managed identity for Azure compute, running a pre-deploy gate, or building an azure.yaml for a container app. Triggers on "deploy to Azure", "keyless Azure OpenAI", "DefaultAzureCredential", "azd provision", "managed identity", "no API keys in code".

Its SKILL.md is about 730 tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files (for example `resources/references/AZURE-AUTH.md`, `resources/references/DEPLOY-CHECKLIST.md` and `resources/scripts/preflight.py`).

It sits in DevOps & Cloud, covering Deployment. It works with Microsoft Azure, Python and Azure OpenAI. The repository describes itself as: Claude Code and Large-Context Reasoning (O'Reilly Live Learning). The licence is MIT.

When your agent uses it

  • Deploying a Python GenAI service
  • Wiring an Azure OpenAI client without API keys
  • Provisioning managed identity for Azure compute
  • Running a pre-deploy gate

Example prompts

  • “deploy to Azure”
  • “keyless Azure OpenAI”
  • “DefaultAzureCredential”
  • “/azure-ai-deploy”

Requirements

  • Python 3
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Bash, Edit, Write

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Read the auth pattern first
  2. Scaffold the client and config
  3. Set required environment
  4. Run preflight
  5. Work the deploy checklist

What it can do on your machine

Read from SKILL.md and the folder at commit cb80eae. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Bash
    • Edit
    • Write

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • contoso-aoai.openai.azure.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azure AI Deploy loads about 731 tokens when it runs. Until then it costs about 117 tokens; SKILL.md has 319 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~731

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Glob, Grep, Bash, Edit, Write

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from timothywarner-org/claude-code at commit cb80eae, republished under its MIT licence (© timothywarner-org). 319 words, ~731 tokens.

Download SKILL.mdSave it as .claude/skills/azure-ai-deploy/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
azure-ai-deploy
description
Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd. Use when deploying a Python GenAI service, wiring an Azure OpenAI client without API keys, provisioning managed identity for Azure compute, running a pre-deploy gate, or building an azure.yaml for a container app. Triggers on "deploy to Azure", "keyless Azure OpenAI", "DefaultAzureCredential", "azd provision", "managed identity", "no API keys in code".
allowed-tools
Read, Glob, Grep, Bash, Edit, Write

Ship a Python GenAI app to Azure (keyless)

This skill deploys a Python generative-AI service to Azure with no API keys in source. Authentication is via Microsoft Entra ID token (DefaultAzureCredential) locally and managed identity on Azure compute. Deployment runs through azd (Azure Developer CLI), which provisions and deploys in one workflow.

When to reach for this

  • You have a Python GenAI app (chat, RAG, agent) that calls Azure OpenAI and you want it in Azure.
  • You want the keyless pattern so no secret is stored in code, config, or environment.
  • You need a repeatable pre-deploy gate before a live class or a production push.

Workflow

1. Read the auth pattern first

Read resources/references/AZURE-AUTH.md. It covers why keys stay out of code, how DefaultAzureCredential resolves an identity across local and cloud, and which RBAC role the app identity needs on the Azure OpenAI resource.

2. Scaffold the client and config

Copy the templates into the target project and edit for the real service:

  • resources/templates/chat_client.py - keyless Azure OpenAI client. Reads endpoint and deployment from env vars. No key.
  • resources/templates/azure.yaml - minimal azd config for a Python container app.
3. Set required environment

The app reads two values from the process environment, never from hardcoded strings:

  • AZURE_OPENAI_ENDPOINT - the resource endpoint, for example https://contoso-aoai.openai.azure.com/
  • AZURE_OPENAI_DEPLOYMENT - the model deployment name, for example gpt-4o-chat
4. Run preflight
bash
uv run python ${CLAUDE_SKILL_DIR}/resources/scripts/preflight.py

The script verifies both env vars are set and non-empty. It exits non-zero when a value is missing, so it fails a CI step before any provisioning starts.

5. Work the deploy checklist

Read resources/references/DEPLOY-CHECKLIST.md and clear every gate: evals passed, secrets stored in Azure Key Vault, then azd provision followed by azd deploy.

Conventions

  • uv manages Python, not pip. Run scripts with uv run.
  • No key strings. The client uses azure_ad_token_provider, never api_key.
  • Least privilege. Grant the app identity the Cognitive Services OpenAI User role, nothing broader.
  • Azure only. This skill targets Azure services end to end.

© timothywarner-org, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files in .claude/skills/azure-ai-deploy of timothywarner-org/claude-code.

  • SKILL.md
  • resources/references/AZURE-AUTH.md
  • resources/references/DEPLOY-CHECKLIST.md
  • resources/scripts/preflight.py
  • resources/templates/azure.yaml
  • resources/templates/chat_client.py

Open the folder on GitHubat commit cb80eae

Compare with similar skills

Azure AI Deploy next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure AI Deploy compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Azure AI Deploy this skilltimothywarner-org/claude-code224—~731Automated safety check: NotesMIT
Azure Architecture Autopilotgithub/awesome-copilot40k1 repos~1.9kAutomated safety check: PassMIT
Capacitymicrosoft/GitHub-Copilot-for-Azure2551 repos~1.7kAutomated safety check: PassMIT
Deploy Modelmicrosoft/GitHub-Copilot-for-Azure2551 repos~1.8kAutomated safety check: PassMIT
Customizemicrosoft/GitHub-Copilot-for-Azure2551 repos~2.2kAutomated safety check: PassMIT
Presetmicrosoft/GitHub-Copilot-for-Azure2551 repos~1.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Azure AI Deploy

What does Azure AI Deploy do?

Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd. Azure AI Deploy is an agent skill from timothywarner-org/claude-code. Ship a Python generative-AI app to Azure the keyless way, using DefaultAzureCredential and azd.

When should I use Azure AI Deploy?

Azure AI Deploy fits situations like: deploying a Python GenAI service; wiring an Azure OpenAI client without API keys; provisioning managed identity for Azure compute; running a pre-deploy gate.

How do I install Azure AI Deploy in Claude Code?

Run `npx skills add timothywarner-org/claude-code --skill azure-ai-deploy -a claude-code`. Or copy the skill folder (.claude/skills/azure-ai-deploy in timothywarner-org/claude-code) into .claude/skills/azure-ai-deploy in your project. Claude Code loads it when a task matches its description.

How do I install Azure AI Deploy in Codex?

Run `npx skills add timothywarner-org/claude-code --skill azure-ai-deploy -a codex`. Or copy the skill folder (.claude/skills/azure-ai-deploy in timothywarner-org/claude-code) into .agents/skills/azure-ai-deploy in your project. Codex loads it when a task matches its description.

Can I use Azure AI Deploy in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add timothywarner-org/claude-code --skill azure-ai-deploy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-ai-deploy, .gemini/skills/azure-ai-deploy, .github/skills/azure-ai-deploy and .opencode/skills/azure-ai-deploy in your project.

What does Azure AI Deploy need to run?

Going by SKILL.md and its folder, Azure AI Deploy needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Glob, Grep, Bash, Edit, Write.

Does Azure AI Deploy access the network?

SKILL.md names 1 domain. In commands or code: contoso-aoai.openai.azure.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Azure AI Deploy safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Azure AI Deploy use?

Azure AI Deploy is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure AI Deploy use?

About 731 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Azure AI Deploy?

Skills that share tags, products or a category with Azure AI Deploy: Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Capacity (microsoft/GitHub-Copilot-for-Azure, 255 stars), Deploy Model (microsoft/GitHub-Copilot-for-Azure, 255 stars) and Customize (microsoft/GitHub-Copilot-for-Azure, 255 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure AI Deploy?

timothywarner-org (a GitHub organization) maintains it in timothywarner-org/claude-code, which has 224 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on July 20, 2026.

Source: timothywarner-org/claude-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.