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- ReplayResult records per-rollout tokens + latency_ms; replay_one measures them (approximated from text length when the backend doesn't track tokens, e.g. mock). - replay.multi_objective_reward(w_acc, w_tokens, w_latency): weighted reward so a skill can be optimized to be cheaper/faster, not only more accurate (cost terms normalized vs a reference, default = accuracy-only / backward compatible). - Backend.preferences (free text) injected into reflect as a prior; build_backend attaches it (to the optimizer for dual backends). run_gbrain gains --preferences. 3 new tests (multi-objective ordering, preference injection, cost recording). 29 tests pass; mock gates + 3.8/3.12 compile green. Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>