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Three Tier Memory

三级记忆管理系统 (Three-Tier Memory Management)。用于管理 AI 代理的短期、中期、长期记忆。包括:(1) 滑动窗口式短期记忆,(2) 自动摘要生成中期记忆,(3) 向量检索长期记忆 (RAG)。当需要管理对话历史、优化上下文、构建个人知识库、或实现记忆持久化时使用此 Skill。

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三级记忆管理系统 (Three-Tier Memory Management)。用于管理 AI 代理的短期、中期、长期记忆。包括:(1) 滑动窗口式短期记忆,(2) 自动摘要生成中期记忆,(3) 向量检索长期记忆 (RAG)。当需要管理对话历史、优化上下文、构建个人知识库、或实现记忆持久化时使用此 Skill。

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, references/references.md, scripts/memory_manager.py

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 9 sections Open source page

Memory Manager Skill

管理 AI 代理的三级记忆系统:短期(滑动窗口)、中期(自动摘要)、长期(向量检索)。

快速开始

# 初始化记忆系统 python3 scripts/memory_manager.py init # 添加短期记忆 python3 scripts/memory_manager.py add --type short --content "用户喜欢黑色" # 查询记忆 python3 scripts/memory_manager.py search "用户的偏好"

架构概览

层级存储位置触发条件用途短期memory/sliding-window.json实时保持当前对话连贯中期memory/summaries/Token 阈值压缩历史,保留大意长期memory/vector-store/语义检索永久记忆,RAG

1. 短期记忆:滑动窗口

配置:config/window_size(默认 10 条) 逻辑:FIFO 队列,超出则丢弃最旧消息 文件:memory/sliding-window.json

2. 中期记忆:自动摘要

触发:当前 token > config/summary_threshold(默认 4000) 模型:使用廉价模型(如 GPT-3.5-Haiku) 输出:memory/summaries/YYYY-MM-DD.json

3. 长期记忆:向量检索

后端:ChromaDB(本地向量库) 存:对话结束/摘要生成后自动向量化存储 取:每次查询前先检索相关记忆

配置文件

创建 memory/config.yaml: memory: short_term: enabled: true window_size: 10 max_tokens: 2000 medium_term: enabled: true summary_threshold: 4000 summary_model: "glm-4-flash" # 或 gpt-3.5-turbo long_term: enabled: true backend: "chromadb" top_k: 3 min_relevance: 0.7

使用场景

新对话开始:先 search 长期记忆,注入相关上下文 对话中:自动管理短期/中期记忆,超阈值自动摘要 对话结束:将重要信息存入长期记忆

详细用法

See REFERENCES.md for complete command reference.

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
2 Docs1 Scripts
  • SKILL.md Primary doc
  • references/references.md Docs
  • scripts/memory_manager.py Scripts