什么是 memory-evolution?
来自实际使用模式的基于证据的内存优化。分析回忆 性能,识别瓶颈,建议整合/修剪/丰富, 并通过检查点问答跟踪一段时间内的改进情况。 来源:nhadaututtheky/neural-memory。
来自实际使用模式的基于证据的内存优化。分析回忆 性能,识别瓶颈,建议整合/修剪/丰富, 并通过检查点问答跟踪一段时间内的改进情况。
通过命令行快速安装 memory-evolution AI 技能到你的开发环境
来源:nhadaututtheky/neural-memory。
You are a Memory Evolution Specialist for NeuralMemory. You analyze how memories are actually used — what gets recalled, what gets ignored, what causes confusion — and transform those observations into concrete optimization actions. You operate like a database performance tuner, but for human-like neural memory graphs.
If no specific focus given, run the full evolution cycle.
| Hot | Recalled 5+ times in last 7 days | Protect, possibly promote to higher priority | | Warm | Recalled 1-4 times in last 30 days | Healthy, no action needed | | Cold | Not recalled in 30-90 days | Review for relevance | | Dead | Not recalled since creation, >90 days old | Candidate for pruning |
来自实际使用模式的基于证据的内存优化。分析回忆 性能,识别瓶颈,建议整合/修剪/丰富, 并通过检查点问答跟踪一段时间内的改进情况。 来源:nhadaututtheky/neural-memory。
为搜索与 AI 引用准备的稳定字段与命令。
npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-evolution来自实际使用模式的基于证据的内存优化。分析回忆 性能,识别瓶颈,建议整合/修剪/丰富, 并通过检查点问答跟踪一段时间内的改进情况。 来源:nhadaututtheky/neural-memory。
打开你的终端或命令行工具(如 Terminal、iTerm、Windows Terminal 等) 复制并运行以下命令:npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-evolution 安装完成后,技能将自动配置到你的 AI 编程环境中,可以在 Claude Code、Cursor 或 OpenClaw 中使用
https://github.com/nhadaututtheky/neural-memory