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memory-maintenance记忆维护

Agent Skill

memory-maintenance 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

62,328

周安装

2,650

GitHub Stars

6

下载量

21,836
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:memory-maintenance(记忆维护)
来源仓库:https://github.com/maxlauriehutchinson/memory-maintenance
安装命令:
openclaw skills install memory-maintenance
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install memory-maintenance

简介

OpenClaw 代理的智能内存管理。查看每日笔记、建议 MEMORY.md 更新、维护目录运行状况并自动清理旧文件。推荐用于内存占用不断增加的代理。

SKILL.md

name
memory-maintenance
version
1.0.0
description
Intelligent memory management for OpenClaw agents. Reviews daily notes, suggests MEMORY.md updates, maintains directory health, and auto-cleans old files. Recommended for agents with growing memory footprints.
homepage
https://github.com/MaxLaurieHutchinson/memory-maintenance
author
name
Max Hutchinson
email
max.hutchinson258@gmail.com
url
https://github.com/MaxLaurieHutchinson
tags
["memory", "maintenance", "automation", "agent-improvement", "workflow"]
metadata
openclaw
emoji
🧹
requires
bins
["gemini", "jq"]
env
["GEMINI_API_KEY"]
install
kind
script
script
./scripts/install.sh
label
Install memory maintenance

Memory Maintenance Skill

Intelligent memory management for OpenClaw agents. Reviews daily notes, suggests MEMORY.md updates, maintains directory health, and auto-cleans old files.

Why This Exists

Agents wake up fresh every session. Without maintenance:

  • Daily notes pile up and become unsearchable
  • Important decisions get buried in old sessions
  • Context windows fill with irrelevant history
  • You repeat the same context-setting every day

This skill automates the tedious work of keeping your agent's memory organized and actionable.

Features

  • Content Review: Analyzes daily notes and suggests MEMORY.md updates
  • Directory Health: Monitors memory/ directory for naming issues, fragmentation, bloat
  • Auto-Cleanup: Archives old reviews (7+ days) and enforces retention policy (30 days)
  • Safe by Default: Content changes require approval; only safe maintenance auto-applies

Recommended Model

This skill works well with lightweight models. We recommend:

  • Primary: gemini-2.5-flash (fast, cost-effective)
  • Fallback: gemini-2.5-flash-lite (if rate limits hit)

Both handle the structured output and analysis tasks efficiently.

Quick Start

# Install the skill
clawhub install memory-maintenance

# Configure (optional)
# Edit config/settings.json to customize schedule, retention, etc.

# Run manually
openclaw skill memory-maintenance run

# Or let it run automatically via cron (configured during install)

Architecture

Daily Session Notes (memory/YYYY-MM-DD.md)
    ↓
Review Agent (scheduled daily)
    ↓
Structured Suggestions (JSON)
    ↓
Human Review (markdown report)
    ↓
Approved Updates → MEMORY.md
    ↓
Auto-Cleanup (archive old files)

Workflow

  1. Daily Review (23:00 by default)

- Scans configurable lookback period (default: 7 days) - Checks memory/ directory health - Generates suggestions via LLM - Outputs structured JSON + human-readable markdown

  1. Human Review

- Read agents/memory/review-v2-YYYY-MM-DD.md - Approve/reject suggestions

  1. Apply Changes
   # Dry run (preview)
   openclaw skill memory-maintenance apply --dry-run 2026-02-05
   
   # Apply safe changes (archiving, cleanup)
   openclaw skill memory-maintenance apply --safe 2026-02-05
   
   # Apply all (requires confirmation)
   openclaw skill memory-maintenance apply --all 2026-02-05
  1. Auto-Cleanup (runs after successful review)

- Archives reviews older than configured threshold - Deletes archive files older than retention period - Cleans up error logs

Configuration

Edit config/settings.json:

{
  "schedule": {
    "enabled": true,
    "time": "23:00",
    "timezone": "Europe/London"
  },
  "review": {
    "lookback_days": 7,
    "model": "gemini-2.5-flash",
    "max_suggestions": 10
  },
  "maintenance": {
    "archive_after_days": 7,
    "retention_days": 30,
    "consolidate_fragments": true,
    "auto_archive_safe": true
  },
  "safety": {
    "require_approval_for_content": true,
    "require_approval_for_delete": true,
    "trash_instead_of_delete": true
  }
}

Safety

  • Content suggestions: Never auto-applied (human review mandatory)
  • Safe maintenance (archiving): Auto-applied with --safe
  • Risky operations (delete, rename): Require --all + confirmation
  • Trash recovery: Deleted files go to agents/memory/.trash/ (recoverable for retention period)

Commands

# Run review manually
openclaw skill memory-maintenance review

# Apply changes
openclaw skill memory-maintenance apply [--dry-run|--safe|--all] DATE

# Run cleanup
openclaw skill memory-maintenance cleanup

# Check status
openclaw skill memory-maintenance status

# View stats
openclaw skill memory-maintenance stats

Integration with MEMORY.md

The skill suggests updates to standard MEMORY.md sections:

  • Agent Identity and Core Preferences
  • Infrastructure/Setup
  • Memory Management
  • Backup & Migration
  • Contacts
  • Scheduled Operations
  • Content Creation & Projects
  • Active Projects

Files

Output

  • agents/memory/review-v2-YYYY-MM-DD.json — Structured suggestions
  • agents/memory/review-v2-YYYY-MM-DD.md — Human-readable report
  • agents/memory/stats.json — Aggregate statistics

Archive

  • agents/memory/archive/YYYY-MM/ — Monthly buckets
  • agents/memory/.trash/ — Recoverable deletions

Requirements

  • OpenClaw >= 2026.2.0
  • Gemini CLI (brew install gemini-cli)
  • jq (brew install jq)
  • Gemini API key (from Google AI Studio)

Troubleshooting

"Gemini failed" → Check GEMINI_API_KEY is set in .env or environment

"No suggestions generated" → Check daily notes exist in memory/YYYY-MM-DD.md → Review error logs in agents/memory/error-*.txt

"Too many maintenance tasks" → Run openclaw skill memory-maintenance apply --safe to archive old files → Adjust archive_after_days in config

Author

Built by Max Hutchinson as part of an AI agent infrastructure exploration.

License

MIT — Free to use, modify, distribute.


*Part of the Hybrid Agent Architecture. Built for agents that improve over time.*

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

88.22%
按下载量换算19,264

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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