Claude Skill
adoresever/graph-memory
Graph Memory 是一个 OpenClaw 插件，能从对话中提取结构化三元组，压缩 75% 上下文，并通过知识图谱引擎实现跨会话经验复用。
概览
仓库信息
安装这个 Skill
git clone https://github.com/adoresever/graph-memory.gitRegistry 信息
git clone https://github.com/adoresever/graph-memory.gitnpm installnpx vitest run # verify 80 tests passnpx vitest # watch mode
项目简介
Graph Memory 是一个 OpenClaw 记忆插件，能从对话中提取结构化三元组，压缩 75% 的上下文，并通过知识图谱引擎实现跨会话经验复用。
Openclaw记忆插件Knowledge Graph + Memory；Knowledge Graph Context Engine for OpenClaw — extracts structured triples from conversations, compresses context 75%, enables cross-session experience reuse
要点
- 从对话中提取结构化三元组
- 压缩 75% 的上下文以提高效率
- 支持跨会话经验复用
- 基于 SQLite 实现轻量存储
- 集成 OpenClaw 插件生态
使用场景
- 长时间运行的 AI 代理对话
- 跨聊天会话的知识保留
- 为令牌受限模型压缩上下文
- 为编码助手构建持久记忆
README 摘要
<p align="center"> <img src="docs/images/banner.jpg" alt="graph-memory" width="100%" /> </p> <h1 align="center">graph-memory</h1> <p align="center"> <strong>Knowledge Graph Context Engine for OpenClaw</strong><br> By <a href="mailto:Wywelljob@gmail.com">adoresever</a> · MIT License </p> <p align="center"> <a href="#installation">Installation</a> · <a href="#how-it-works">How it works</a> · <a href="#configuration">Configuration</a> · <a href="README_CN.md">中文文档</a> </p> --- <p align="center"> <img src="docs/images/hero.png" alt="graph-memory overview" width="90%" /> </p> ## What it does When conversations grow long, agents lose track of what happened. graph-memory solves three problems at once: 1. **Context explosion** — 174 messages eat 95K tokens. graph-memory compresses to ~24K by replacing raw history with structured knowledge graph nodes 2. **Cross-session amnesia** — Yesterday's bugs, solved problems, all gone in a new session. graph-memory recalls relevant knowledge automatically via FTS5/vector search + graph traversal 3. **Skill islands** — Self-improving agents record learnings as isolated markdown. graph-memory connects them: "installed libgl1" and "ImportError: libGL.so.1" are linked by a `SOLVED_BY` edge **It feels like talking to an agent that learns from experience. Because it does.** <p align="center"> <img src="docs/images/graph-ui.png" alt="graph-memory knowledge graph visualization with community detection" width="95%" /> </p> > *58 nodes, 40 edges, 3 communities — automatically extracted from conversations. Right panel shows the knowledge graph with community clusters (GitHub ops, B站 MCP, session management). Left panel shows agent using `gm_stats` and `gm_search` tools.* ## What's new in v2.0 ### Community-aware recall