Ai runtime memory

Skill aiskillstore/marketplace/skills/dwsy/ai-runtime-memory

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npx -y skills add aiskillstore/marketplace --skill ai-runtime-memory

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AI Runtime分层记忆系统，支持SQL风格的事件查询、时间线管理，以及记忆的智能固化和检索，用于项目历史追踪和经验传承

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SKILL.md

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AI Runtime 记忆系统

概述

AI Runtime的记忆系统采用分层架构，模拟人类大脑的记忆机制，实现持续存在和认知主体性。系统分为三个层次，通过专门的工具支持SQL风格查询和智能管理。

核心功能

三层记忆架构

短期记忆: 当前会话上下文，7±2组块限制
长期记忆: 跨项目技术知识，结构化知识图谱
情景记忆: 项目历史事件，支持复杂时间线查询

查询能力

SQL风格条件查询（WHERE/ORDER BY/LIMIT）
多格式输出（table/json）
时间范围和标签过滤
全文搜索支持

快速开始

基本查询

# 进入记忆系统目录
cd .ai-runtime/memory

# 查看今天的事件
python3 memory_cli.py query --where "date='$(date +%Y-%m-%d)'"

# 查看架构决策
python3 memory_cli.py query --where "tags CONTAINS 'architecture' AND type='decision'"

使用便捷脚本

# 查看今天的事件
./scripts/memory-query.sh today

# 查看本周统计
./scripts/memory-query.sh week

# 搜索关键词
./scripts/memory-query.sh search "认证"

渐进式披露文档架构

基于 anthropics/skills 设计，按需加载详细信息：

核心架构

系统架构详解 - 分层记忆系统设计和实现原理

使用指南

工具使用指南 - memory_cli.py 和 memory_discovery.py 详细用法

高级主题

维护指南 - 记忆固化、清理和质量保证

实践示例

使用示例 - 从基础查询到高级分析的完整示例

事件记录格式

YAML Front Matter

---
id: unique-event-id
type: event|decision|error|meeting
level: day
timestamp: "2025-11-14T10:30:00"
tags: [architecture, decision]
---

目录结构

episodic/
└── 2025/11/14/
    └── event-description.md

编程接口

from memory_discovery import MemoryDiscovery

# 初始化
discovery = MemoryDiscovery('.ai-runtime/memory')

# 查询
events = discovery.query(
    where="date>='2025-11-14' AND tags CONTAINS 'architecture'",
    order_by="timestamp desc",
    limit=20
)

# 格式化输出
output = discovery.format_events(events, format_type="table")

维护建议

定期运行 ./scripts/memory-query.sh stats 检查系统状态
每周审查 ./scripts/memory-query.sh week 的活动记录
每月归档重要事件到 long-term 记忆层

基于 anthropics/skills 渐进式披露架构设计