SlideTrace: Governed Memory for Cross-Project Slide Personalization

Cross-project slide personalization requires an agent to carry reusable user preferences across projects while preserving their scope and evolution over time. Raw feedback histories leave these properties implicit, making it difficult to determine which preferences remain applicable as interactions accumulate. We introduce SlideTrace, a governed memory framework that represents reusable feedback as atomic, scoped preference claims and maintains them across project working memory and canonical long-term memory. Semantic relation proposals and deterministic validation govern how claims are updated, related, and consolidated across projects. We evaluate SlideTrace against four memory systems and a no-memory reference under a shared generator. After 20 sequential training projects, frozen memory states are evaluated on 15 held-out tasks. SlideTrace achieves the highest overall Score under both GPT-5.4 and Kimi-K3, exceeding the strongest baseline by 0.38 and 0.51 points, with the clearest gains in requirement realization. Ablations further support relation-governed canonicalization and structured memory packages. These findings show that cross-project personalization benefits from governing reusable preference state rather than merely retaining interaction history. Code and data are available in our anonymous repository at https://anonymous.4open.science/r/slidetrace-anonymous-artifact-1315.