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Agent Architecture Review Sample
The Architecture Review Agent is an open-source AI agent sample that reviews software architectures and generates interactive diagrams automatically.
Install
git clone https://github.com/Azure-Samples/agent-architecture-review-sampleInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Architecture Review Agent Sample
What is the Architecture Review Agent?
The Architecture Review Agent is an open-source AI agent sample that reviews software architectures and generates interactive diagrams - automatically. Feed it any architectural description (YAML, Markdown, plain text, code, design docs) and it returns a structured review with risk analysis, actionable recommendations, and an Excalidraw diagram you can edit and share.
For a structured docs map (setup, deployment, scripts, scenarios, testing), see docs/README.md.
Architecture
Clients (Teams/M365 Copilot, CLI, Web Browser) → Foundry Agent Service or Web App → Core Engine (Smart Parser, Risk Detector, Report Builder, Diagram Renderer, LLM Inference) → Azure OpenAI / Excalidraw MCP / ACR / Azure App Service
Internal Data Flow
flowchart TB
subgraph Agent["Architecture Review Agent"]
review_architecture
infer_architecture
end
subgraph Tools["tools.py"]
Parser["ParserYAML / MD / Plaintext"]
LLMInference["LLM InferenceAzureOpenAIChatClient"]
RiskDetector["Risk DetectorTemplate + LLM"]
DiagramRenderer["Diagram RendererExcalidraw + PNG"]
ComponentMapper["Component Mapper"]
ReportBuilder["Report Builder"]
MCPClient["MCP Client(Excalidraw Server)"]
end
review_architecture --> Tools
infer_architecture --> Tools
Tools --> LocalOutputs[".excalidraw / .png / .json"]
MCPClient --> ExcalidrawMCP["Excalidraw MCP(Interactive View)"]
Why use it?
- Instant architecture feedback - get a prioritised risk assessment and improvement plan in seconds, not days.
- Works with what you already have - paste a YAML spec, drag in a README, or describe your system in plain English. The LLM infers structure when the input isn't formal.
- Interactive diagrams - auto-generated Excalidraw diagrams render components, connections, and data flows. Edit them in-browser or export to PNG.
- Two deployment options - run as a full-stack Web App (FastAPI + React) on Azure App Service, or as a Hosted Agent on Microsoft Foundry with Teams / M365 Copilot integration.
- Built for developers - runs locally with a single script, deploys to Azure with one command, and exposes a REST API for pipeline integration.
Demo
Microservices Banking Architecture — full end-to-end review: file upload → risk detection → interactive Excalidraw diagram → recommendations.
If the video does not render inline, download and watch it here.
Features
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