Developer seeks code review for Tsukuyomi, a safety system designed to stop AI agents from cascading failures — open-source, Apache 2.0 licensed

A non-programmer built Tsukuyomi V1.0, a five-layer safety architecture for AI agents (autonomous AI systems that make decisions and take actions on their own), and released the code publicly on GitHub under Apache 2.0 license. The creator passed their own tests but explicitly states those tests are unreliable and is asking experienced developers to audit whether the system actually works.

Tsukuyomi targets a specific failure mode: agents succeed 70% of the time but fail in the final 30% of task completion, where cascading errors cause real business losses. The system aims for 90/10 reliability with a fail-safe that halts the agent instead of letting it spiral into worse mistakes.

For business teams evaluating AI agents (especially in automation, customer service, or operations), this matters because most agent failures happen late in workflows when the damage is hardest to contain. If the code audit confirms Tsukuyomi works, it becomes a free, transparent safety layer any company can bolt onto their existing agents — no vendor lock-in, no licensing fees.