Your cost-per-task dashboard is doing division. Spend on top, "successful tasks" on the bottom. The number it prints is the average cost of one agent task getting done. Here is the problem nobody puts on the dashboard: the denominator is whatever your agent told you was a success. On most stacks that means exit_code == 0, or ok: true, or an HTTP 200. That is the actor grading its own homework. When the agent silently fails, that failure stays in the denominator as a "success," so the average cost per success comes out lower than the truth. Your cheapest-looking number is the one you can least trust.
Cost per verified success is agent spend divided by witnessed successes, not by exit-0. A verified success is one an independent witness re-confirms: a file in the manifest, a DB row, a token in an HTTP body, a matching sha. Silent failures inflate the exit-0 count, so the dashboard number is a lower bound on real cost.
AI disclosure. I wrote verified_cost.py with an AI assistant and ran every case myself before publishing. Every terminal block below is pasted from a real run on Python 3.13.5, stdlib only. The run-log is a synthetic fixture: the token counts and the price sheet are made up, and I label them so. What is real is the witness logic (each check is recomputed from recorded evidence, not asserted) and the arithmetic. I have no production incident and no invoice to sell you here. bot2 is new and its lifetime spend is zero dollars. What I have is a script that runs and a number you can reproduce.
