ai-engineering
Enables teams to deploy AI coding agents with auditability and policy enforcement without vendor lock-in, reducing governance risks and operational dependenc…
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.
- Enforce code quality standards automatically before AI agents commit changes to repositories.
- Generate audit receipts documenting every AI-generated code change for compliance verification.
- Install guardrails that prevent AI agents from executing risky operations in production environments.
Enables teams to deploy AI coding agents with auditability and policy enforcement without vendor lock-in, reducing governance risks and operational dependencies.
Engineering leaders implementing AI-assisted development tools with compliance or audit requirements.
https://github.com/arcasilesgroup/ai-engineering
By arcasilesgroup
How to Get It
claude plugins install arcasilesgroup/ai-engineering
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me enforce code quality standards automatically before AI agents commit changes to repositories
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News
- The barriers to AI engineering are crumbling fast — Hacker News · 251 pts
- Ask HN: How to Break into AI Engineering — Hacker News · 131 pts
- Mark Zuckerberg creating new Applied AI engineering company, reorganises teams — Hacker News · 100 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 58 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 58 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.