agentic-journeys AGENTS.md

Repository instructions describing how the microsoft/agentic-journeys project organizes its AI agents, reusable skills, journeys, and prerequisites.

In plain words
What is it for?
It is for guiding work on agent and skill files, Azure-based learning journeys, setup requirements, and the project's official Azure Skills plugin.
Why use it?
It gives contributors one reference for the required tools, plugin commands, project structure, and terminology.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/microsoft/agentic-journeys/agents-md
Clone the repo
git clone --depth 1 https://github.com/microsoft/agentic-journeys

Made for: Codex, OpenCode.

Per session 2,944 This file is loaded in full into every session.
When invoked 2,944 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.02944 $0.02944
Opus 5 $0.01472 $0.01472
Sonnet 5 $0.00589 $0.00589
Haiku 4.5 $0.00294 $0.00294

Measured 2d ago against content hash a331184092ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agentic-journeys AGENTS.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 2d 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.

Origin

This is a copy

100% identical to github-azure-agentic-journeys AGENTS.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

AGENTS.md · 300 lines

How it starts

The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agents and Skills

This repository contains agentic journeys that build and deploy applications to Azure using GitHub Copilot agents, skills, and Azure Developer CLI (azd).

Journeys

Journeys are self-contained — learners can start with any of them. The root README.md → Agentic journeys table lists them all with cost estimates.

Plugin (canonical — use everywhere):

/plugin marketplace add microsoft/azure-skills
/plugin install azure@azure-skills

Do not use alternate marketplace names.

Prerequisites

Install the Azure Skills plugin for access to Azure-specific MCP and skills tools (Bicep schemas, deployment planning, architecture diagrams, log analysis):

copilot

Once inside the interactive session, add the marketplace (first time only):

> /plugin marketplace add microsoft/azure-skills

Then install the plugin:

> /plugin install azure@azure-skills

Agent & Skill System

This repo uses GitHub Copilot's agents and skills for organized AI assistance:

  • Agents = WHO - Personas with specific jobs (~100 lines, workflow-focused)
  • Skills = HOW - Reusable patterns and implementation details

Available Agents

Agent Purpose When to Use
@oss-to-azure-deployer Deploy OSS apps to Azure Full deployment journey: requirements -> IaC -> deploy -> verify

Available Skills

Skills are loaded automatically based on context:

App-specific skills:

Skill Purpose
n8n-azure n8n workflow automation (Container Apps + PostgreSQL)
grafana-azure Grafana visualization (Container Apps + SQLite/PostgreSQL)
superset-azure Apache Superset BI platform (AKS + PostgreSQL)

Development patterns:

Skill Purpose
data-access-abstraction Repository pattern for swappable data layers (SQLite, Cosmos DB, PostgreSQL)
container-apps-deployment Container Apps + ACR deployment patterns (ACR auth, zone redundancy, SPA deploy, azure.yaml)
journey-runner Run a journey end-to-end: extract prompts, build, deploy, verify
journey-template Create a new agentic journey from an app idea (full-stack or OSS deployment)
journey-test-harness Run all journeys as a test suite: build, deploy, screenshot, teardown, report

Read the full file on GitHub · 300 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. 2d ago First seen · 300 lines · 2,944 tokens per session scan A a331184092ae

Subscribe to this mod's changes

agentic-journeys AGENTS.md is an instructions file published in the GitHub repository microsoft/agentic-journeys (5 stars, last pushed 23d ago), licensed MIT. It adds 2,944 tokens to every session, about $0.0147 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to github-azure-agentic-journeys AGENTS.md, differing in 0 lines, and is treated as a copy.

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