Agent Rule Management Scheme Using Memory as Index and Skill for Rules

On November 2, 2026, a technical write-up appeared on Juejin outlining a solution to a common problem in AI agent setups. The author observed that dumping every rule into Memory tends to make the agent miss executions, while token consumption climbs sharply. The rule file CLAUDE.md, meanwhile, is capped at 200 lines, which is not enough room for a complete rule set. To address this, the author proposed a division of labor: Memory serves as the retrieval index, Skill stores the concrete rules, and whatever needs to be reviewed each turn goes into Memory while everything else is delegated to Skill. The stated goals of the approach are to keep context overhead in check and raise execution accuracy. This is the earliest public material on the scheme so far; the sources available do not report whether other developers have adopted it or iterated on it since.