By githubnext
Compiles Markdown-based agent specs into secure, network-isolated Azure DevOps pipelines, then validates, deploys, and debugs those pipelines including firewall activity and tool call reports.
Download and analyze a finished ado-aw pipeline build. Use when the user wants a security/behavior report on a completed build — firewall/network activity, MCP tool calls, safe-output proposals, detection findings, token usage, or policy signals.
Compile an ado-aw agent file to Azure DevOps pipeline YAML and validate it. Use when the user asks to compile a workflow, check whether it is valid, verify a pipeline matches its source, or understand the compiled IR / dependency graph.
Create a new ado-aw agentic Azure DevOps pipeline from scratch. Use when the user wants to author a brand-new AI-powered ADO pipeline as a Markdown agent file. Ends with a clean compile + lint.
Diagnose a failing ado-aw agentic Azure DevOps pipeline. Use when the user reports a pipeline failing, an agent unable to reach an MCP/network host, safe outputs not being applied, or wants to understand why a build behaved a certain way.
Operate compiled ado-aw pipelines in Azure DevOps. Use when the user wants to register/enable/disable/remove build definitions, queue runs, set pipeline secrets, or report pipeline status.
Uses power tools
Uses Bash, Write, or Edit tools
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Azure DevOps Agentic Workflows. Write agentic workflows in human-friendly markdown; ado-aw compiles each into a secure, multi-stage Azure DevOps pipeline that runs an AI agent in a network-isolated sandbox.
Inspired by GitHub Agentic Workflows (gh-aw).
If you are an AI agent, use the specialized prompts in
prompts/for step-by-step guidance: create · update · debug
You author an agent file — a markdown document with YAML front matter that
describes what the agent should do, when it should run, and which tools it
can use. The ado-aw compiler transforms that file into a production-ready Azure
DevOps pipeline built around three core security stages:
┌────────────────────────┐ ┌──────────────────────┐ ┌───────────────────────┐
│ Agent │────▶│ Detection │────▶│ SafeOutputs │
│ (Stage 1 — Agent) │ │ (Stage 2 — Threats) │ │ (Stage 3 — Executor) │
│ │ │ │ │ │
│ • Runs inside AWF │ │ • Reviews proposed │ │ • Creates PRs │
│ network sandbox │ │ actions for safety│ │ • Creates work items │
│ • Read-only ADO token │ │ • Checks for prompt │ │ • Write ADO token │
│ • Produces safe │ │ injection, leaks │ │ • Never exposed to │
│ output proposals │ │ │ │ the agent │
└────────────────────────┘ └──────────────────────┘ └───────────────────────┘
The agent never has direct write access. All mutations (pull requests, work items) go through a safe outputs pipeline where they are threat-analyzed and then executed with a separate, scoped write token.
Run the first-time installer for your platform:
# Linux (x64)
curl -fsSL https://github.com/githubnext/ado-aw/releases/latest/download/install-linux.sh | sh
# macOS (Apple Silicon)
curl -fsSL https://github.com/githubnext/ado-aw/releases/latest/download/install-macos.sh | sh
# Windows (x64)
$script = Join-Path $env:TEMP "install-ado-aw.ps1"
Invoke-WebRequest "https://github.com/githubnext/ado-aw/releases/latest/download/install-windows.ps1" -UseBasicParsing -OutFile $script
Get-FileHash $script -Algorithm SHA256
Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
& $script
The installers download the release binary, verify it against checksums.txt, install it to a standard path (/usr/local/bin when writable, otherwise a user-local path), and update your PATH when needed.
Compare the Get-FileHash output with the install-windows.ps1 entry in checksums.txt before running the script.
If you see The Process object must have the UseShellExecute property set to false in order to use environment variables, run the five Windows commands above from an existing PowerShell prompt (not via a nested powershell -Command ... launch).
ado-aw init
This creates a Copilot agent at .github/agents/ado-aw.agent.md that helps you create, update, and debug agentic workflows. The agent automatically downloads the ado-aw compiler and handles compilation.
Ask your coding agent (Copilot, Claude, Codex) to create a workflow:
Create an ADO agentic workflow using
https://raw.githubusercontent.com/githubnext/ado-aw/main/prompts/create-ado-agentic-workflow.md
The purpose of the workflow is to check for outdated dependencies weekly
and open PRs to update them.
Or if you've run ado-aw init, simply ask your AI agent:
Create an agentic workflow that checks for outdated dependencies and opens PRs
The AI will generate a markdown file like:
---
name: "Dependency Updater"
description: "Checks for outdated dependencies and opens PRs"
engine:
id: copilot
model: claude-opus-4.7
on:
schedule: weekly on monday around 9:00
pool:
vmImage: ubuntu-22.04
tools:
azure-devops: true
permissions:
read: my-read-arm-connection
write: my-write-arm-connection
safe-outputs:
create-pull-request:
target-branch: main
draft: false
auto-complete: true
squash-merge: true
reviewers:
- "[email protected]"
---
## Instructions
Check all dependency manifests in this repository. For each outdated
dependency, update it to the latest stable version and create a pull
request with a clear description of what changed and why.
# Simple form — generates a `.lock.yml` alongside the source `.md`
npx claudepluginhub githubnext/ado-aw --plugin ado-awGoverned multi-agent SDLC pipeline for Claude Code — v3.0, a ground-up rewrite of the v2.x line. Declared-data pipeline, owned entry points, proof-anchored TDD, code-modular providers.
AI-powered Azure DevOps integration with skills - Intelligent work item management, configuration, and automation for Azure DevOps workflows with MCP integration
Build CI/CD pipelines for GitHub Actions, GitLab CI, Jenkins, and more
Complete Azure DevOps and Azure Pipelines expertise system with Sprint 254-262 features and Windows/Git Bash compatibility (2025). PROACTIVELY activate for: (1) ANY Azure DevOps/Pipelines task, (2) YAML pipeline creation/editing with expression functions (iif, trim), (3) Windows agent Git Bash path conversion issues, (4) Cross-platform pipeline scripts (Windows/Linux/macOS), (5) Workload identity federation (OIDC) passwordless authentication, (6) Pipeline performance analytics and monitoring, (7) Template management and reusability, (8) Microsoft Security DevOps (MSDO) integration, (9) Stage dependencies visualization, (10) Agent v4 with ARM64 support, (11) New OS images (Ubuntu-24.04, Windows-2025, macOS-15), (12) GitHub Copilot integration (Sprint 262), (13) OAuth apps migration to Entra ID (Sprint 261), (14) Continuous Access Evaluation (CAE), (15) Pipeline debugging/troubleshooting, (16) CI/CD optimization, (17) Security/compliance implementation, (18) Azure DevOps CLI operations. Provides: Windows/Git Bash path handling mastery (MSYS_NO_PATHCONV, cygpath, shell detection), cross-platform script patterns, MINGW path conversion guidance, Windows agent troubleshooting, Sprint 254-262 latest features, workload identity federation setup and migration guidance (2025 security standard), pipeline performance analytics and cost tracking, Agent v4 on .NET 8 with ARM64 platform support, Microsoft Defender for DevOps with MSDO extension (replaces deprecated CredScan), GitHub Advanced Security integration, template patterns for code reuse, iif() ternary operator and trim() function, stage-level variables and dependency visualization, Ubuntu-24.04/Windows-2025/macOS-15 hosted agents, GitHub Copilot work item integration, latest YAML schema (always researches current docs), Microsoft best practices, multi-stage pipeline patterns, caching/parallelization, Azure Key Vault integration, comprehensive security scanning (SAST/dependency/container/IaC/secrets), deployment strategies, performance optimization, systematic debugging, and cost efficiency analysis. Ensures production-ready, secure, efficient, cross-platform pipelines following Microsoft 2025 standards.
GitHub Actions CI/CD - workflows, authentication, inspection
Cloud infrastructure agents — cloud, container, SRE specialists