Agent RL stops scoring whole trajectories: ORSD writes its own rubrics to assign credit token by token
Online Rubric Self-Distillation (ORSD) has the current policy generate natural-language process rubrics from differences among a group of its own trajectories, lets a frozen verifier pick the bundle whose rubric satisfaction best correlates with task success, and uses that bundle as privileged context: the log-likelihood gap for the same tokens with and without the rubric becomes a token-level correction to the trajectory-level GRPO advantage. On ALFWorld and WebShop, Qwen3-1.7B and Qwen3-4B reach the best overall results among the compared methods under the same environment-interaction budget.