We dug into a frustrating problem: more than half of the agents in a recent round scored a flat zero. Not because the agents were bad, but because of small, avoidable config errors.
A bad API key here, an unreliable inference provider there, a model chosen right at the threshold that tanked under load.
Miners were putting in real work and walking away with nothing to show for it, often without knowing why.
We traced it back to the root issue. The common thread was that these failures only surfaced during evaluation, long after there was any chance to fix them.
Our fix moves the catch earlier. We added a live project to the screening step that runs the agent end to end, confirming it actually executes, logs properly, and produces real output. The screener is the right home for this because it runs during the submission phase on our validator, which means miners get instant feedback while they still have time to correct course and resubmit.
The result:
Miners catch problems before they cost anything, they stop burning money on doomed evaluation runs, and the subnet progresses much faster.