We started measuring "undeclared-intent spend" in agent workflows

Was extending some internal tooling this week and ended up building a metric I didn't expect to care about this much: *undeclared-intent spend*. The idea is simple. If an agent session declares it's trying to do A, but reasoning turns later touch systems or execution paths outside that declared intent, how much compute went toward that work? Example output from one session: Total compute 5,137 tokens Undeclared 1,173 tokens (22.8%) Declared 3,964 tokens (77.2%) What's interesting about this isn't governance language or policy enforcement. It's that unintended execution now has a measurable operational cost. Retries cost money. Loops cost money. Reasoning drift costs money. Off-task execution costs money. The more time I spend tracing agent systems, the more it feels like cost is becoming a behavioral signal, not just billing telemetry. One subtle thing we ran into while building this: sometimes "undeclared" genuinely reflects drift, where the agent wandered into systems it wasn't supposed to touch. Sometimes the runtime surface itself doesn't expose enough information to determine intent cleanly, and "undeclared" is really "indeterminable from here." That distinction ended up mattering a lot more than I expected, because the two failure modes deserve very different responses. Curious whether others running agents in production are thinking about off-task compute this way yet, or if most teams are still treating token spend purely as a billing and optimization problem. Specifically interested in whether anyone has tried to put a number on drift that wasn't just "the bill went up."