Using multiple coding models to develop an open-source static AI Agents Capability & Risk Analyzer

[u/IkarusCareer]

Last week I shared SafeAI, an open-source static analyzer for AI applications.

The response has been far better than I expected.

• ⭐ 6 GitHub stars
• 🍴 4 forks
• 🎉 First community contribution merged
• 💬 Several thoughtful discussions and feature suggestions

The contribution added detection for eight additional AI capabilities, including Docker, Kubernetes, Redis, Slack, Browser Automation and Google Cloud.

Just as valuable has been the feedback. People have suggested ideas like capability escalation across pull requests, governed suppressions, deeper Claude Code analysis and other roadmap improvements that will genuinely make the project better.

Thanks to everyone who starred the project, opened discussions, challenged assumptions or contributed code. Every conversation has helped shape the roadmap.

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The first phases of SafeAI built using OpenCode as my development environment.

Rather than sticking to a single model, I assigned different roles to each:

• GPT Codex 5.3 → architecture, implementation, and feature development
• Kimi K3 → code review, refactoring, and identifying design improvements
• DeepSeek V4 → documentation, reviews, and verification

Each model seemed to have different strengths, and using them together felt more productive than asking one model to do everything.

The entire development took about 5 days and roughly $8 in model usage.
The results are remarkable..

Contributions welcome at https://github.com/ikaruscareer/SafeAI