據 AlphaMoat 統計,截至 2026-09,Memory Maintenance 累計下載 4,028 次、獲 6 個星標,在全部 5,078 個 AI 技能中排名第 2,531 位,在「AI 智慧體」分類(969 個)中排名第 493 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 100 | 3131 | 6 | - |
| SkillHub ↗ | 329 | 4028 | 6 | — |
各平台的計數口徑不同,統計時間不一致。
生成結構化建議和報告,內容變更須人工批准,歸檔或清理可先預覽。依賴 Gemini CLI、jq、憑據和相容 OpenClaw 配置。筆記可能發往 Gemini,維護可能移動或刪除檔案;啟用前須審查定時、保留策略、模型生成路徑及環境變數載入範圍。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 4028 | — | 6 |
| 2026-08 | 3671 | +3.1% | 6 |
| 2026-07 | 3559 | — | 6 |
| 2026-05 | 3167 | — | 6 |
| 2026-03 | 2480 | — | 5 |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 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.*
將開發過程中的經驗、錯誤與修正記錄為 Markdown 檔案,供日後重用並提升為工作區記憶。
用自然語言描述需求,在本機與遠端技能市場尋找技能並取得推薦。
給 AI agent 用的瀏覽器自動化命令列技能。
將使用者明確糾正與自我檢視整理成分層記憶,並依使用情況升級或封存。
在安裝第三方技能之前,按清單審查來源、許可權與危險模式的技能。
將代理記憶與跨技能狀態整理成具型別與約束的知識圖譜。
規劃 AI 代理主動跟進、工作記憶與回顧流程的工作區設定指南。
指導如何建立與更新有效 Claude 技能的寫作指南。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。