Preprint
Aug 2026
When Not to Imitate: Boundary-Aware Skill Memory for Reliable Tool-Use LLM Agents
BASM is proposed, which augments each skill with explicit boundary fields, which transforms each retrieved skill from an unconditional action template into state-conditioned guidance: the agent applies the skill when its conditions hold, suppresses inapplicable tool calls when they do not, and issues targeted repairs when execution fails.
Zi-Han Lin, Zhenyu Chen, Jiawen Wei et al.
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