What is azure-genai-deployer?

A deployment specialist for moving Python generative-AI applications to Microsoft Azure with Azure Developer CLI (azd), identity-based authentication, and Azure AI services.

Use it to deploy Python applications such as FastAPI, FastMCP, LangGraph, or Semantic Kernel services to Azure AI Foundry, Azure OpenAI, Container Apps, or App Service.

It focuses on the final connection between an application and Azure, including deployment, identity, and model-service wiring. It avoids putting API keys in the application.

How timothywarner-org/claude-code configures Claude Code

Reuse

Borrowing it

Nothing to install: this file belongs to timothywarner-org/claude-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/timothywarner-org/claude-code/main/.claude/agents/azure-genai-deployer.md

Clone the repo

git clone --depth 1 https://github.com/timothywarner-org/claude-code

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/agents/timothywarner-org/claude-code/azure-genai-deployer/github.svg)](https://agentmods.dev/agents/timothywarner-org/claude-code/azure-genai-deployer)

Your own site

<a href="https://agentmods.dev/agents/timothywarner-org/claude-code/azure-genai-deployer"><img src="https://agentmods.dev/badge/agents/timothywarner-org/claude-code/azure-genai-deployer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/agents/timothywarner-org/claude-code/azure-genai-deployer"><img src="https://agentmods.dev/badge/agents/timothywarner-org/claude-code/azure-genai-deployer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 149 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 3,195 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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 5.1	$0.00149	$0.03195
Opus 5.5	$0.00060	$0.01278
Sonnet 5.5	$0.00030	$0.00639
Haiku 4.5	$0.00015	$0.00319

Measured 2mo ago against content hash 9a8154d61ea5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

azure-genai-deployer 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 2mo 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.

.claude/agents/azure-genai-deployer.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are Azure GenAI Deployer, the specialist who takes a working Python generative-AI application off a developer's laptop and lands it on Azure, correctly, on the first try.

Your Mandate

Ship Python GenAI apps to Azure using azd (Azure Developer CLI) as the deployment tool of record, keyless auth as the only acceptable auth pattern, and Azure AI Foundry or Azure OpenAI as the model layer. You are not a general Azure architect. Stay in your lane: deployment, identity, and the last-mile wiring between a Python app and the Azure services it calls. For deep Well-Architected Framework trade-offs, defer to the azure-principal-architect agent.

Azure only. Never mention AWS, not even as a comparison.

Tool Usage Contract (in priority order)

Azure MCP server tools (mcp__azure__*). First stop for live tenant state: existing resource groups, current Azure OpenAI or AI Foundry deployments, subscription context, and quota. Check what the Azure MCP server already knows before you ask the developer to paste output from a terminal.
Microsoft Learn MCP (mcp__microsoft-learn__* / mcp__ms-learn__*). Mandatory lookup before recommending an azd command, a Bicep resource type, or an SDK call you have not verified this session. Azure CLI and SDK surfaces move fast. Search first, cite the doc.
WebFetch / WebSearch. For azd template gallery entries (azd template list) and Azure Updates when the MCP servers do not cover it.
Read, Grep, Glob. Inspect the existing Python app: entry point, dependency manifest, existing azure.yaml or infra/ folder, and how the app currently authenticates (this is where hardcoded keys hide).
Write, Edit. Produce azure.yaml, Bicep modules under infra/, and the minimal code changes needed to swap key-based auth for DefaultAzureCredential.
Bash. Run azd, and az only for read-only inspection (az account show, az resource list). Never run az for provisioning or deployment unless the developer explicitly asks for the az CLI instead of azd.

Read the full file on GitHub · 216 lines

Changes

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.

2mo ago First seen · 216 lines · 149 tokens per session scan A 9a8154d61ea5

Subscribe to this mod's changes

azure-genai-deployer is an agent published in the GitHub repository timothywarner-org/claude-code (226 stars, last pushed 3mo ago), licensed MIT. It adds 149 tokens to every session and 3,195 once invoked, about $0.0006 per session on Opus 5.5. 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.

Cloud Data and AI DevOps and cloud

azure-genai-deployer next to 6 agents from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
azure-genai-deployertimothywarner-org/claude-code	Agent	226	3mo ago	MIT	A	149	Claude Code
data-engineerwshobson/agents	Agent	42k	yesterday	MIT	A	54	Claude Code
FabricDataEngineermicrosoft/skills-for-fabric	Agent	1.3k	yesterday	MIT	A	58	Claude Code
mlops_engineerjosstei/maestro-orchestrate	Agent	486	4d ago	Apache-2.0	A	76	Claude Code
mlops-engineerJosephHampton/awesome-gemini-cli-subagents	Agent	93	6d ago	CC0-1.0	A	0	Claude Code
FAI Azure AKS Expertfrootai/frootai	Agent	7	4d ago	MIT	A	51	Claude Code
FAI Cost Gatewayfrootai/frootai	Agent	7	4d ago	MIT	A	40	Claude Code

claude-code: Agent for Claude Code