Claw-Eval makes agent routing measurable

The big idea is less a magic benchmark than a measurable routing layer for agents. That points more toward smarter model selection before burning frontier tokens than toward replacing top-tier models outright. The benchmark is designed for reproducibility through human-verified tasks, sandboxed runs, and traceable scoring, and Pass^3 reduces lucky one-off wins. If Claw-Eval or similar tools expose task-quality signals through an API, they could become a cheap gatekeeper for which model handles which task. That would fit the meta-MoE idea, but the outcome depends on orchestration quality, not the benchmark alone. The real disruption is operational: less overcalling frontier models, more disciplined task triage, and better evals to justify that choice.