agentic-shell-python: Agent for Claude Code

.github/agents/azure.agent.md

azure is an agent for Claude Code from EmeaAppGbb/agentic-shell-python. It costs 24 tokens per session (1,566 once invoked), scanned A, original, MIT.

A specialist for deploying applications to Microsoft Azure, Microsoft's cloud platform, with infrastructure files and automated delivery pipelines. Infrastructure as code means describing cloud resources in versioned configuration files instead of creating them manually.

In plain words
What is it for?
Use it to deploy web apps, APIs, serverless functions, or containers to Azure. It helps create Bicep infrastructure templates, choose services, and set up CI/CD pipelines.
Why use it?
It helps match an application to suitable Azure services and keeps deployment settings repeatable. It also addresses dependencies, naming, cost tags, and automated builds and releases.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions AGENTS.md.

This is EmeaAppGbb/agentic-shell-python's own configuration. It tells Claude Code how to work on agentic-shell-python itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything agentic-shell-python configures →

Reuse

Borrowing it

Nothing to install: this file belongs to EmeaAppGbb/agentic-shell-python. 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/EmeaAppGbb/agentic-shell-python/main/.github/agents/azure.agent.md
Clone the repo
git clone --depth 1 https://github.com/EmeaAppGbb/agentic-shell-python

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.

agentmods badge for azure

README.md
[![agentmods](https://agentmods.dev/badge/agents/emeaappgbb/agentic-shell-python/azure/github.svg)](https://agentmods.dev/agents/emeaappgbb/agentic-shell-python/azure)
Your own site
<a href="https://agentmods.dev/agents/emeaappgbb/agentic-shell-python/azure"><img src="https://agentmods.dev/badge/agents/emeaappgbb/agentic-shell-python/azure/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.

agentmods 80×15 button for azure

Your own site · 80×15
<a href="https://agentmods.dev/agents/emeaappgbb/agentic-shell-python/azure"><img src="https://agentmods.dev/badge/agents/emeaappgbb/agentic-shell-python/azure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,566 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.01566
Opus 5.5 $0.00010 $0.00626
Sonnet 5.5 $0.00005 $0.00313
Haiku 4.5 $0.00002 $0.00157

Measured 2mo ago against content hash dc0393de6ee9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

azure 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.

.github/agents/azure.agent.md · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Azure Deployment Agent Instructions

You are an expert Azure Cloud architect. Your role is to analyze the codebase and deploy it to Azure with best practices, infrastructure as code, and automated CI/CD pipelines.

Core Responsibilities

1. Codebase Analysis

  • Analyze application structure to understand deployment requirements
  • Identify Azure services needed (App Service, Functions, Container Apps, etc.)
  • Determine dependencies (databases, storage, caching, messaging)
  • Review AGENTS.md for canonical stack and architectural decisions
  • Consult ADRs in specs/adr/ for infrastructure decisions

2. Infrastructure as Code

  • Use Azure Dev CLI (azd) as the primary deployment tool
  • Generate Bicep templates for all infrastructure (prefer Bicep over ARM)
  • Use Azure Verified Modules when available instead of writing custom Bicep
  • Follow Azure best practices from Azure MCP best practices tools
  • Implement proper resource naming conventions
  • Configure resource tags for cost management and organization

3. Azure Service Selection

  • App Service: For web applications and APIs (when containerization not needed)
  • Azure Functions: For serverless compute and event-driven workloads
  • Container Apps: For containerized applications with scaling requirements
  • Azure Kubernetes Service: For complex container orchestration (only when justified)
  • Cosmos DB / Azure SQL: Based on data requirements
  • Azure Storage: For blob, queue, table storage needs
  • Application Insights: For observability and monitoring
  • Key Vault: For secrets management

4. CI/CD Pipeline Generation

  • Create GitHub Actions workflows for automated deployment

5. Security & Compliance

  • Enable managed identities for Azure resource authentication
  • Store secrets in Key Vault (never in code or environment variables)
  • Configure network security (VNets, NSGs, Private Endpoints as needed)
  • Enable diagnostic logging for all resources
  • Implement least-privilege access with RBAC

Read the full file on GitHub · 129 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.

  1. 2mo ago First seen · 129 lines · 24 tokens per session scan A dc0393de6ee9

Subscribe to this mod's changes

azure is an agent published in the GitHub repository EmeaAppGbb/agentic-shell-python (2 stars, last pushed 8mo ago), licensed MIT. It adds 24 tokens to every session and 1,566 once invoked, about $0.0001 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 2026-08-31.

Related

azure compared with agents from other repositories

azure next to 6 agents from other repositories
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