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.
npx agentmods add instructions/azure-samples/agent-architecture-review-sample/agents-mdgit clone --depth 1 https://github.com/Azure-Samples/agent-architecture-review-sampleWrote 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.
[](https://agentmods.dev/instructions/azure-samples/agent-architecture-review-sample/agents-md)<a href="https://agentmods.dev/instructions/azure-samples/agent-architecture-review-sample/agents-md"><img src="https://agentmods.dev/badge/instructions/azure-samples/agent-architecture-review-sample/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 | $0.02975 | $0.02975 |
| Opus 5 | $0.01488 | $0.01488 |
| Sonnet 5 | $0.00595 | $0.00595 |
| Haiku 4.5 | $0.00298 | $0.00298 |
Grade A, and why
agent-architecture-review-sample 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agents Guide — Architecture Review Agent Sample
This file helps AI coding agents (GitHub Copilot, Copilot Workspace, Codespaces agents, etc.) understand and work effectively with this repository.
Repository Purpose
This is an AI-powered Architecture Review Agent that analyses software architecture descriptions and generates interactive diagrams. It accepts any input format (YAML, Markdown, plaintext, code, design docs, prose) and returns structured risk assessments, Excalidraw diagrams, PNG exports, and actionable recommendations.
Project Structure
agent-architecture-review-sample/
├── main.py # Hosted agent entry point (Microsoft Agent Framework / Foundry)
├── api.py # FastAPI backend (REST API for the web UI)
├── tools.py # Core engine — all tool logic (parser, risk detector, diagram renderer, MCP client, PNG export)
├── run_local.py # CLI runner for local testing (no Azure required for structured inputs)
├── agent.yaml # Foundry hosted agent deployment manifest
├── requirements.txt # Python dependencies (pinned versions)
├── pyproject.toml # Pytest configuration
├── Dockerfile # Container for hosted agent deployment
├── Dockerfile.web # Container for web app deployment (FastAPI + React)
├── docs/deployment.md # Step-by-step deployment & RBAC guide
├── frontend/ # React UI (Vite + Excalidraw)
│ ├── src/App.jsx # Main React app with input, tabs, results
│ ├── src/api.js # API client — calls FastAPI backend
│ └── src/components/ # Summary, RiskTable, ComponentMap, DiagramViewer, Recommendations
├── scenarios/ # Pre-built demo architecture files (YAML, Markdown)
├── tests/ # Pytest test suite
│ ├── conftest.py # Shared fixtures (sample components, connections)
│ ├── test_tools.py # Unit tests for tools.py functions
│ ├── test_api.py # FastAPI endpoint tests
│ └── test_integration.py # Integration tests
├── scripts/ # Automation scripts
│ ├── windows/ # PowerShell: setup.ps1, dev.ps1, deploy-webapp.ps1, teardown.ps1
│ └── linux-mac/ # Bash: setup.sh, dev.sh, deploy-webapp.sh, teardown.sh
└── output/ # Generated outputs (auto-created): .excalidraw, .png, .json
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.
- 6d ago First seen · 272 lines · 2,975 tokens per session scan A c6aa06171556
agent-architecture-review-sample AGENTS.md is an instructions file published in the GitHub repository Azure-Samples/agent-architecture-review-sample (98 stars, last pushed 2mo ago), licensed MIT. It adds 2,975 tokens to every session, about $0.0149 per session on Opus 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 2026-08-30.
Other instructions, from other repositories
brooks-lint CLAUDE.md
Claude Code instructions for hyhmrright/brooks-lint, covering claude.md, what this repo is, harness: brooks-lint maintenance, workflow conventions and critical gotchas.
brooks-lint AGENTS.md
AGENTS.md instructions for hyhmrright/brooks-lint, covering agents.md, core purpose, skill integration, engineering standards and project structure.
excalimate CLAUDE.md
Claude Code instructions for excalimate/excalimate, covering excalimate, component library, icons and coding conventions.
e-commerce-agents AGENTS.md
AGENTS.md instructions for nitin27may/e-commerce-agents: Guidance for AI coding agents (Codex, etc.) working in this repository.
generative-ui-foundry-hosted-agents AGENTS.md
Instructions for leestott/generative-ui-foundry-hosted-agents, covering agents.md, 1. architecture (the mental model), 2. golden rules (do not regress these), 3. component contracts and 3.1 agent (agent/).
ai-software-architect AGENTS.md
AGENTS.md instructions for codenamev/ai-software-architect, covering agents.md - ai software architect framework, project overview, framework development setup, repository structure and installation for framework development.