No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by junminhong · Codex Skill · ★ 123
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awsui safe to install? View the security audit →
awsui Website Stop wiring machine-specific AWS profile names into every command. Choose an environment, verify the account, and launch Claude Code, Codex, Kiro, Terraform, or any CLI in the right AWS context. You work in environments such as , , and . AWS tools work with profile names such as . awsui maps the project environment to a local AWS profile, verifies the authenticated account, and launches your tool only when the account matches the project configuration. Initialize the project, bind a profile, verify the account, and launch a tool. What problem does awsui solve? You choose the environment. awsui handles the context checks behind
| Stars | 123 |
| Forks | 3 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 70.1650920742311/100 |
| Last Updated | 2026-08-23 |
| Created | 2025-09-30 |
| Platforms | aws, claude-code, cli, codex, python |
| Est. Tokens | ~16k |
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awsui is Verified, project-aware AWS contexts for any CLI or AI coding agent.. It is categorized as a Codex Skill with 123 GitHub stars.
awsui is primarily written in Python. It covers topics such as ai, ai-tools, antigravity.
You can find installation instructions and usage details in the awsui GitHub repository at github.com/junminhong/awsui. The project has 123 stars and 3 forks, indicating an active community.
awsui is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awsui on Agent Skills Hub include sample-well-architected-skills-and-steering, hcom, kasetto. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: