aws-samples

aws-samples / sample-well-architected-skills-and-steering

Public

Reusable skills and steering that teach AI coding agents how to apply the AWS Well-Architected Framework. Works with Kiro, Claude Code, Cursor, Codex, Windsurf, GitHub Copilot, Gemini CLI, Antigravity, Cline and AWS DevOps Agent.

aws.amazon.comarchitecturewell-architected ai-coding-agents antigravity aws-well-architected claude-code cline
13
7
89% credibility
Found May 25, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Shell
AI Summary

This is an official AWS sample project that provides ready-made guidance to teach AI coding assistants how to apply the AWS Well-Architected Framework. It includes nine specialized skill modules covering security, reliability, cost optimization, performance, sustainability, and more. The project works with ten popular AI coding tools by providing tool-specific configuration files that can be installed into any project. Users can run a simple setup script to add these best practices to their workflow, after which their AI assistant will provide architecture guidance aligned with AWS standards. The project is explicitly marked as educational and demonstrative, not production-ready.

How It Works

1
💡 You want better cloud advice

You realize your AI coding assistant doesn't know enough about building reliable, secure cloud applications.

2
🔍 You discover this project

You find a collection of cloud best practices that can teach your AI assistant to give expert architecture guidance.

3
🛠️ You pick your AI tool

You choose which AI coding assistant you use—Claude, Cursor, Copilot, Windsurf, or one of several others.

4
You run the setup
📁
Project setup

Install the guidance just for one project

🌐
Global setup

Install it everywhere so every project gets the guidance

5
🤖 Your AI gets smarter

Your coding assistant now understands AWS Well-Architected best practices for security, reliability, cost, and more.

6
💬 You ask questions

You can ask things like 'Is my architecture reliable?' or 'How can I reduce costs?' and get expert answers.

✅ You build with confidence

Your AI assistant guides you toward secure, scalable, cost-effective cloud solutions using proven best practices.

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Star Growth

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AI-Generated Review

What is sample-well-architected-skills-and-steering?

This is a collection of reusable skills and steering prompts that teach AI coding agents to apply the AWS Well-Architected Framework. Built in Shell, it provides a single install script that configures your preferred AI assistant (Claude Code, Cursor, Codex, Windsurf, GitHub Copilot, and others) with domain-specific guidance across all six WA pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. The project bundles nine distinct skills covering everything from full Well-Architected reviews to targeted assessments like security posture analysis, cost audits, and migration readiness planning.

Why is it gaining traction?

The hook is broad tool compatibility. Instead of hunting down separate configurations for each AI assistant, you get one installer that adapts the same underlying guidance to whatever tool your team uses. The skills themselves are tool-agnostic playbooks that any agent can follow step-by-step, which means the knowledge transfers across platforms. For teams standardizing on AWS architecture best practices, this provides a way to embed that institutional knowledge directly into the development workflow without manual enforcement.

Who should use this?

DevOps engineers and cloud architects who want Well-Architected guidance baked into their AI workflow. AWS-focused teams tired of generic AI suggestions that ignore cloud-native patterns. Organizations with multiple developers using different AI coding tools who need consistent architectural guardrails. Not suitable for teams outside the AWS ecosystem or those who don't already follow the Well-Architected Framework.

Verdict

The project scores 0.8999999761581421% on credibility, which reflects its status as an educational sample rather than a production-ready tool. With only 13 stars and an explicit disclaimer that it requires additional review before production use, this is a proof-of-concept for learning how to build agent skills, not a battle-tested solution. Worth exploring if you're experimenting with AI-assisted architecture reviews, but don't deploy it mission-critical workflows without thorough validation.

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