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Dat Phamleft a comment
70% token savings is the real headline here. The MEMORY.md approach works until you hit ~50k tokens of context and your agent starts hallucinating its own history. Context-tree architecture is the right abstraction - hierarchical retrieval instead of dumping everything into the prompt. 26k users in a week tells you people were desperate for this.
ByteRover Memory System for OpenClaw File-based memory for OpenClaw with >92% retrieval accuracy
Give OpenClaw agents stateful memory that keep your context's timeline, facts, and meaning perfectly in place. ByteRover is a memory layer that gets 26k+ downloads from OpenClaw power users within one week, and delivers a market-best 92.19% retrieval accuracy, local-to-cloud portability, and built-in version control.
ByteRover Memory System for OpenClaw File-based memory for OpenClaw with >92% retrieval accuracy