What is trainer-demo-deploy az-python.instructions.md?

A set of Python coding rules for architecture diagrams, cloud-tool servers, and utility scripts. Python is a programming language.

Use it when writing or reviewing Python code in the repository, including diagram tools and Azure pricing services.

It gives contributors consistent formatting, type hints, dependency handling, and lint checks across these scripts.

How MicrosoftLearning/trainer-demo-deploy configures GitHub Copilot

Reuse

Borrowing it

Nothing to install: this file belongs to MicrosoftLearning/trainer-demo-deploy. 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/MicrosoftLearning/trainer-demo-deploy/main/.github/instructions/az-python.instructions.md

Clone the repo

git clone --depth 1 https://github.com/MicrosoftLearning/trainer-demo-deploy

Made for: GitHub Copilot.

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/instructions/microsoftlearning/trainer-demo-deploy/az-python/github.svg)](https://agentmods.dev/instructions/microsoftlearning/trainer-demo-deploy/az-python)

Your own site

<a href="https://agentmods.dev/instructions/microsoftlearning/trainer-demo-deploy/az-python"><img src="https://agentmods.dev/badge/instructions/microsoftlearning/trainer-demo-deploy/az-python/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/instructions/microsoftlearning/trainer-demo-deploy/az-python"><img src="https://agentmods.dev/badge/instructions/microsoftlearning/trainer-demo-deploy/az-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 701 This file is loaded in full into every session.

When invoked 701 The same file — it is already loaded in full.

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	$0.00701	$0.00701
Opus 5.5	$0.00280	$0.00280
Sonnet 5.5	$0.00140	$0.00140
Haiku 4.5	$0.00070	$0.00070

Measured today against content hash f7f40e5ba76a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

trainer-demo-deploy az-python.instructions.md 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 today.

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/instructions/az-python.instructions.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Guidelines

Instructions for writing clean, consistent Python in this repository. Target Python 3.10+ with Ruff for linting and formatting.

Project Context

Python is used for three purposes in this repo:

Architecture diagrams — diagrams library scripts in generated-scenarios/ and .github/skills/
Azure Pricing MCP server — async aiohttp/starlette server in mcp/azure-pricing-mcp/
Utility scripts — Checkov scanning, diagram verification

Style & Formatting

Formatter: Ruff (ruff format) — double quotes, space indentation
Linter: Ruff with rules: E, W, F, I, B, C4, UP, SIM
Line length: 120 characters (matches project-wide setting)
Imports: sorted by isort rules via Ruff — stdlib, third-party, first-party
Quotes: double quotes for strings
Type hints: use for function signatures; pyproject.toml sets basic type checking

Package Management

Use uv (Astral) as the package manager — installed in devcontainer
Root dependencies in requirements.txt: diagrams, matplotlib, pillow, checkov
MCP server dependencies in mcp/azure-pricing-mcp/pyproject.toml
Use virtual environments: MCP server has its own .venv

Diagram Scripts

Follow the existing pattern for architecture diagram generation:

"""Brief description of what the diagram shows."""

from diagrams import Cluster, Diagram
from diagrams.azure.compute import AppServices
from diagrams.azure.network import FrontDoors

with Diagram("Diagram Title", show=False, filename="output-name", direction="TB"):
    with Cluster("Resource Group"):
        # Resources...
        pass

Always set show=False to prevent auto-opening
Use direction="TB" (top-to-bottom) for consistency
Group resources in Cluster blocks matching Azure resource groups
Set explicit filename parameter to control output location

Async Patterns (MCP Server)

The Azure Pricing MCP server uses async patterns:

Use async def with await — never mix sync and async I/O
Use aiohttp.ClientSession for HTTP requests — create once, reuse
Use cachetools.TTLCache for pricing data caching
Handle azure.identity credential errors gracefully with fallback

Read the full file on GitHub · 81 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.

today First seen · 81 lines · 701 tokens per session scan A f7f40e5ba76a

Subscribe to this mod's changes

trainer-demo-deploy az-python.instructions.md is an instructions file published in the GitHub repository MicrosoftLearning/trainer-demo-deploy (31 stars, last pushed 11d ago), licensed MIT. It adds 701 tokens to every session, about $0.0028 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 2026-11-07.

Cloud DevOps and cloud Languages Python

trainer-demo-deploy az-python.instructions.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
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trainer-demo-deploy: Instructions file for GitHub Copilot