Would you use a circuit breaker for AI agents?

Would you use something like this? One pattern I've seen while building agentic apps is that agents sometimes get stuck in tool loops. Example: search → search → search → search... browser → browser → browser... or recursive tool calls that keep burning tokens without making progress. By the time you notice, the run has already cost way more than it should have. I'm thinking about building an open-source SDK called Moven AI that acts like a circuit breaker for AI agents. Instead of being another observability platform, it sits in the execution loop and checks things like: repeated/near-identical tool calls token cost ceiling recursion depth no-progress detection If it detects a runaway agent, it aborts the run before it keeps spending money. The SDK would work completely standalone (MIT licensed), with an optional hosted dashboard for teams that want analytics and alerts. The goal isn't to replace LangSmith, Langfuse, Helicone, etc. Those help you understand what happened. This is meant to prevent expensive failures before they happen. A few questions: Have you actually had an agent get stuck in a loop? How much did it end up costing? Would you install something like this if it was literally a one-line wrapper around your agent? What heuristic would you trust the most (or least)? I'm mainly trying to figure out whether this solves a real pain point before I spend the next few weeks building it.