据 AlphaMoat 统计,截至 2026-09,Memory Maintenance 累计下载 4,028 次、获 6 个星标,在全部 5,078 个 AI 技能中排名第 2,531 位,在「AI 智能体」分类(969 个)中排名第 493 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 100 | 3,131 | 6 | - |
| SkillHub ↗ | 329 | 4,028 | 6 | — |
各平台的计数口径不同,统计时间不一致。
生成结构化建议和报告,内容变更须人工批准,归档或清理可先预览。依赖 Gemini CLI、jq、凭据和兼容 OpenClaw 配置。笔记可能发往 Gemini,维护可能移动或删除文件;启用前须审查定时、保留策略、模型生成路径及环境变量加载范围。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,028 | — | 6 |
| 2026-08 | 3,671 | +3.1% | 6 |
| 2026-07 | 3,559 | — | 6 |
| 2026-05 | 3,167 | — | 6 |
| 2026-03 | 2,480 | — | 5 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- 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: "[email protected]" url: "https://github.com/MaxLaurieHutchinson" tags: ["memory", "maintenance", "automation", "agent-improvement", "workflow"]
metadata:
openclaw:
emoji: 🧹
requires:
bins: ["gemini", "jq"]
env: ["GEMINI_API_KEY"]
install:
- id: setup
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
```bash
# 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
2. **Human Review**
- Read `agents/memory/review-v2-YYYY-MM-DD.md`
- Approve/reject suggestions
3. **Apply Changes**
```bash
# 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
```
4. **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`:
```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
```bash
# 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.
- GitHub: [@MaxLaurieHutchinson](https://github.com/MaxLaurieHutchinson)
- Agent: Ash (OpenClaw)
## License
MIT — Free to use, modify, distribute.
---
*Part of the Hybrid Agent Architecture. Built for agents that improve over time.*
把开发过程中的经验、错误与纠正记录为 Markdown 文件,供后续复用并晋升为工作区记忆。
用自然语言描述需求,在本地与远程技能市场里找技能并给出推荐的技能。
给 AI agent 用的浏览器自动化命令行技能。
把用户纠正与自我复盘沉淀成分层记忆、并按使用情况升降级的技能。
在安装第三方技能之前,按清单审查来源、权限与危险模式的技能。
把 agent 的记忆与跨技能状态存成带类型和约束的知识图谱的技能。
一份为 AI 代理规划主动跟进、工作记忆与复盘流程的工作区配置指南。
指导如何创建与更新有效 Claude 技能的写作指南。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。