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 arcasilesgroup · Codex Skill · ★ 55
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-engineering safe to install? View the security audit →
{ai} engineering turns AI-assisted delivery into a governed local workflow. <img src="https://sonarcloud.io/api/projectbadges/measure?project=arcasilesgroupai-engineering&metric=alertstatus" alt="Q
| Stars | 55 |
| Forks | 3 |
| Language | TypeScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 69.4267097502631/100 |
| Last Updated | 2026-09-17 |
| Created | 2026-02-04 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~15k |
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ai-engineering is The governance floor for AI coding agents: install, guard, prove. Guards, git hooks, an executable contract and a receipt per run — no hosted control plane, no provider lock-in.. It is categorized as a Codex Skill with 55 GitHub stars.
ai-engineering is primarily written in TypeScript. It covers topics such as agent-skills, ai-agents, ai-governance.
You can find installation instructions and usage details in the ai-engineering GitHub repository at github.com/arcasilesgroup/ai-engineering. The project has 55 stars and 3 forks, indicating an active community.
ai-engineering is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to ai-engineering on Agent Skills Hub include agent-skills, agent-skills-cli, awesome-ai-agent-skills. 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: