Love this architectural approach. Using probabilistic models to verify other probabilistic models is just turtles all the way down, so anchoring the agent to deterministic AST evidence is exactly the right move.

I've been working on the exact same philosophical problem, but at the production execution layer rather than the dev tooling layer. I built a zero-trust policy engine that sits right before an AI agent triggers a real-world consequence (like a financial transaction or DB write), requiring deterministic, cryptographically verifiable proof before allowing the execution.

It’s incredibly refreshing to see this strict, "fail-closed" deterministic fact-checking mindset being applied to the debugging phase too. Awesome work on the implementation!

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