What would make you trust it in a real agent workflow?

Space Bunny is a new anonymous model available on OpenRouter. I’m more interested in how people would evaluate it for agent work than in guessing who made it. With a chat model, one or two good answers can shape a first impression. For agents, that tells me less. The model has to hold constraints across steps, use tools consistently, recover from mistakes, and avoid drifting from the goal. My first pass/fail test would be small and stateful. I’d set a task with a few explicit rules, let it call tools several times, introduce one failure midway, then see whether it recovers without redoing completed work or ignoring earlier constraints. A huge benchmark won’t tell me as much. I’d also run the same task multiple times. A model that nails it once and collapses on the next two runs is harder to trust than one that’s a bit less impressive and predictable. I’d look for signs like pausing to ask when missing info, avoiding repeated tool calls, recovering after a failed command or a bad intermediate result, keeping constraints as the context grows, and not creating extra work while “fixing” something unrelated. I’d also gauge how much supervision it needs before I’d let it run for 20 to 30 minutes unattended. If you’re building agents, what’s your first test before deciding a new model is reliable enough for a longer workflow?