by aws-samples · Codex Skill · ★ 179
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🏗️ Well-Architected Skills & Steering for AI Coding Agents Reusable skills and steering that teach AI coding agents how to apply the AWS Well-Architected Framework. One set of playbooks, 12 supported tools. Kiro · Claude Code · Cursor · Codex · Windsurf · GitHub Copilot · Gemini CLI · Antigravity · Junie · Amp · Cline · AWS DevOps Agent [!IMPORTANT] This sample is provided for educational and demonstrative purposes. It is not intended for production use without additional review and testing appropriate to your environment. 🎯 Why this exists Developers don't stop to consult documentation — they ask their AI assistant. If the assistant doesn't know the Well-Architected Framework, the guidance never reaches the code. This project embeds WA best practices where development actually happens: in the IDE, at the moment code is being written.
| Stars | 179 |
| Forks | 30 |
| Language | Python |
| Category | Codex Skill |
| License | MIT-0 |
| Quality Score | 55.486/100 |
| Last Updated | 2026-06-16 |
| Created | 2026-05-21 |
| Platforms | aws, claude-code, cli, codex, gemini, python |
| Est. Tokens | ~16k |
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sample-well-architected-skills-and-steering is Reusable skills and steering that teach AI coding agents how to apply the AWS Well-Architected Framework. One set of playbooks, 13 supported tools.. It is categorized as a Codex Skill with 179 GitHub stars.
sample-well-architected-skills-and-steering is primarily written in Python. It covers topics such as ai-coding-agents, amp, antigravity.
You can find installation instructions and usage details in the sample-well-architected-skills-and-steering GitHub repository at github.com/aws-samples/sample-well-architected-skills-and-steering. The project has 179 stars and 30 forks, indicating an active community.
sample-well-architected-skills-and-steering is released under the MIT-0 license, making it free to use and modify according to the license terms.
The top alternatives to sample-well-architected-skills-and-steering on Agent Skills Hub include awesome-agent-skills, kasetto, fallow-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.