Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/timothywarner-org/claude-code/azure-ai-deploynpx skills add timothywarner-org/claude-code --skill azure-ai-deploygit clone --depth 1 https://github.com/timothywarner-org/claude-codeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/timothywarner-org/claude-code/azure-ai-deploy)<a href="https://agentmods.dev/skills/timothywarner-org/claude-code/azure-ai-deploy"><img src="https://agentmods.dev/badge/skills/timothywarner-org/claude-code/azure-ai-deploy.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00107 | $0.00701 |
| Opus 5 | $0.00053 | $0.00351 |
| Sonnet 5 | $0.00021 | $0.00140 |
| Haiku 4.5 | $0.00011 | $0.00070 |
Grade A, and why
azure-ai-deploy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 examplehttps://contoso-aoai.openai.azure.com/AZURE_OPENAI_DEPLOYMENT- the model deployment name, for examplegpt-4o-chat
4. Run preflight
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.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 55 lines · 107 tokens per session scan A 2d7e70b8d319
azure-ai-deploy is a skill published in the GitHub repository timothywarner-org/claude-code (223 stars, last pushed 1mo ago), licensed MIT. It adds 107 tokens to every session and 701 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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