Agent-Authored Skills Score 8-11 Points Worse Than No Skill At All, and RL on Execution Feedback Closes It

arXiv 2608.17587·high signalXBlueskyLinkedInCopy link

WER (Write, Execute, Refine; arXiv 2608.17587, 2026-08-18) opens with a blunt measurement: skills an agent writes for itself perform 8-11 points worse than running with no skill, meaning following procedural guidance and authoring it are separate capabilities. WER trains a dedicated Skill Optimizer outside a frozen executor, using matched successful/failed trajectories from a programmatic verifier as the refinement state. It gains 7.80 Pass@1 on BFCL v4 multi-turn and 3.85 on tau2-bench over no-skill, and a trained 4B optimizer hits 76.63% on BFCL v4, beating every off-the-shelf general-purpose model used as a skill optimizer.