SkillForge Verifies Stored Agent Skills Against the Environment Instead of Treating the Skill Bank as Append-Only

arXiv 2608.24747·medium signalXBlueskyLinkedInCopy link

Skill-based RL approaches like SkillRL extract skills from raw trajectories but never check whether a stored skill still works, so the bank grows monotonically while quality decays. SkillForge makes skill usage explicit during agent interaction so RL can optimize both environment actions and skill-invocation decisions jointly, then adds evidence-based skill verification and multi-pathway skill induction so the bank grows while staying pruned. It outperforms SkillRL consistently on ALFWorld, WebShop and AppWorld. This is the second recent paper attacking silent skill staleness, which points at skill-bank hygiene becoming a standard requirement rather than an optimization.