memory-master

تایید شده

Local memory system with structured indexing and auto-learning. Auto-write, heuristic recall, auto learning when knowledge is insufficient. Compatible with self-improving-agent: auto-records skill completions and errors to knowledge base.

@openclaw
v2.5.3MIT۱۴۰۴/۱۲/۱۴
55از ۱۰۰
(0)
۲.۰k
۳۵۱
۳۹۸

نصب مهارت

مهارت‌ها کدهای شخص ثالث از مخازن عمومی GitHub هستند. SkillHub الگوهای مخرب شناخته‌شده را اسکن می‌کند اما نمی‌تواند امنیت را تضمین کند. قبل از نصب، کد منبع را بررسی کنید.

نصب سراسری (سطح کاربر):

npx skillhub install openclaw/skills/memory-master

نصب در پروژه فعلی:

npx skillhub install openclaw/skills/memory-master --project

مسیر پیشنهادی: ~/.claude/skills/memory-master/

بررسی هوش مصنوعی

کیفیت دستورالعمل55
دقت توضیحات40
کاربردی بودن65
صحت فنی60

Scored 55 for well-conceptualized memory framework with clear format specifications and bilingual support. Marketing copy inflates perceived quality beyond actual instruction density. No automation scripts — entirely instructional. Universal generality is the main strength.

محتوای SKILL.md

---
name: memory-master
version: 2.5.3
description: "Local memory system with structured indexing and auto-learning. Auto-write, heuristic recall, auto learning when knowledge is insufficient. Compatible with self-improving-agent: auto-records skill completions and errors to knowledge base."
author: 李哲龙
tags: [memory, recall, indexing, context]
---

# 🧠 Memory Master — The Precision Memory System

*Transform your AI agent from forgetful to photographic.*

---

## The Problem

Most AI agents suffer from **memory amnesia**:

- ❌ Can't remember what you discussed yesterday
- ❌ Loads entire memory files, burning tokens
- ❌ Fuzzy search returns irrelevant results
- ❌ No structure, just raw text dumps
- ❌ Waits for user to trigger recall, never proactively remembers

**You deserve better.**

---

## The Solution: Memory Master v1.2.4

A **precision-targeted memory architecture** with optional network learning capability.

### ✨ Key Features

| Feature | Description |
|---------|-------------|
| **📝 Structured Memory** | "Cause → Change → Todo" format for every entry |
| **🔄 Auto Index Sync** | Write once, index updates automatically |
| **🎯 Zero Token Waste** | Read only what you need, nothing more |
| **⚡ Heuristic Recall** | Proactively finds relevant memories when context is missing |
| **🧠 Auto Learning** | When local knowledge is insufficient, automatically search web to learn and update knowledge base |
| **🔓 Full Control** | All files visible/editable/deletable. No auto network calls. |

---

## The Memory Format

### Daily Memory: `memory/daily/YYYY-MM-DD.md`

**Format:**
```markdown
## [日期] 主题
- 因:原因/背景
- 改:做了什么、改了什么
- 待:待办/后续
```

**Example:**
```markdown
## [2026-03-03] 记忆系统升级
- 因:原记忆目录混乱,查找困难
- 改:目录调整为 daily/ + knowledge/,上传 v1.1.0
- 待:检查 ClawHub 描述
```

**Why this format?**
- 一目了然 (一目了然 = instantly clear at a glance)
- 逻辑清晰:因 → 改 → 待
- 通用模板,适用于任何场景

---

## The Index Format

### Index: `memory/daily-index.md`

**Format:**
```markdown
# 记忆索引

- 主题名 → daily/日期.md,日期.md
```

**Example:**
```markdown
# 记忆索引

- 记忆系统升级 → daily/2026-03-03.md
- 飞书配置 → daily/2026-03-02.md,daily/2026-03-03.md
- 电商网站 → daily/2026-03-02.md
```

**Rules:**
- 逗号分隔多天
- 只有一个一级标题:记忆索引
- 简洁清晰,一眼定位

---

## Heuristic Recall Protocol

### When to Trigger Recall

** DON'T wait for user to say "yesterday" or "remember"**

Trigger recall when:
1. User mentions a topic you don't have context for
2. Current conversation references something past
3. You feel "I'm not sure I have this information"
4. User asks about "that", "the project", "the skill"

### Recall Flow

```
用户问题 → 发现上下文缺失 → 读 index 定位主题 → 读取记忆文件 → 恢复上下文 → 回答
```

**Example:**
```
User: "那个 skill 你觉得还有什么要改的吗?"

1. 思考:我知道用户指哪个 skill 吗?→ 不知道,上下文没有
2. 读 index → 找到"记忆系统升级 → daily/2026-03-03.md"
3. 读取文件 → 恢复记忆
4. 回答:"根据昨天记录,我们..."
```

### Key Principle

**"When you realize you don't know, go check the index."**

---

## Knowledge Base System

### Knowledge Structure

```
memory/knowledge/
├── knowledge-index.md
└── *.md (knowledge entries)
```

### Knowledge Index: `memory/knowledge-index.md`

**极简格式 - 关键字列表:**
```markdown
# 知识库索引

- clawhub
- oauth
- react
```

### When to Read Knowledge Base

**启发式:当前上下文没有相关信息时才读**

1. 用户有要求 → 按用户要求执行
2. 用户没要求 → 检查上下文有没有规则
3. 上下文没有 → 搜索知识库索引
4. 找到对应项 → 读取知识库文件执行

- 上下文有 → 直接用
- 上下文没有 → 搜索引 → 读知识库文件 → 执行

### Problem Solving Flow

```
用户问题 → 上下文有?→ 有:直接解决 / 无:搜索引 → 有知识?→ 有:解决 / 无:自动网络搜索学习 → 写知识库 → 更新索引 → 解决问题
```

**Example:**
```
User: "怎么上传 skill 到 ClawHub?"

1. 上下文有 clawhub 信息?→ 有(刚学过)→ 直接回答
2. 不用读知识库

---
User: "怎么实现 OAuth?"

1. 上下文有 OAuth 信息?→ 没有
2. 搜 knowledge-index → 没有 OAuth
3. 告知用户:"我还不会,先去查一下"
4. 网络搜索学习
5. 写入 knowledge/oauth.md
6. 更新 knowledge-index
7. 开始和用户沟通解决方案
```

---

## Write Flow

### When to Write

Write immediately after:
1. Discussion reaches a conclusion
2. Decision is made
3. Action item is assigned
4. Something important happens
5. Learned something new (check before every response)

### ⚠️ IMPORTANT: Auto-Trigger Write

**DO NOT wait for user to remind you!**

Before every response, quickly check: "Did I learn anything new in this conversation?" If yes, write it.

Write IMMEDIATELY when any of the above happens. This is NOT optional.

### Skill Event Triggers (Auto-Record)

When a skill completes or errors, automatically record to knowledge:

| Event | Write Location | Content |
|-------|---------------|---------|
| **skill_complete** | memory/knowledge/ | 记录学到了什么新技能/方法 |
| **skill_error** | memory/knowledge/ | 记录错误原因和解决方案 |

**统一写入知识库**,因为都是"学到新知识"。

### Write Steps

1. **Detect** conclusion/action (automatically, every time)
2. **Format** using "因-改-待" template
3. **Write** to `memory/daily/YYYY-MM-DD.md`
4. **Update** `daily-index.md` (add new topic or append date)

**IMPORTANT: Always update index when writing to daily memory!**

### Update MEMORY.md (if needed)

When writing to MEMORY.md:
1. Check for duplicate/outdated rules
2. Merge and clean up
3. Keep it minimal

### Example

```
讨论:我们要改进记忆系统,决定把目录分成 daily/ 和 knowledge/
结论:改完了,今天上传到 GitHub 和 ClawHub

写入:
## [2026-03-04] 记忆系统升级
- 因:原记忆目录混乱,查找困难
- 改:目录调整为 daily/ + knowledge/,上传 v1.1.0
- 待:检查 ClawHub 描述

更新索引:
- 记忆系统升级 → daily/2026-03-03.md,daily/2026-03-04.md
```

---

## Recall Flow Summary

| Step | Action | Trigger |
|------|--------|---------|
| 1 | Parse user query | User asks question |
| 2 | Check: do I have context? | If uncertain |
| 3 | Read daily-index.md | Context missing |
| 4 | Locate relevant topic | Found in index |
| 5 | Read target date file | Know the date |
| 6 | Restore context | Got info |
| 7 | Answer user | Complete |

---

## Knowledge Base Flow Summary

| Step | Action | Trigger |
|------|--------|---------|
| 1 | Parse user query | User asks question |
| 2 | Search knowledge-index | Always check first |
| 3 | Found solution? | Yes → Solve / No → Continue |
| 4 | Tell user "I don't know yet" | No solution |
| 5 | Search web & learn | Get knowledge |
| 6 | Write to knowledge/*.md | New knowledge |
| 7 | Update knowledge-index | Keep index in sync |
| 8 | Solve the problem | Complete |

---

## File Structure

```
~/.openclaw/workspace/
├── AGENTS.md              # Your rules
├── MEMORY.md              # Long-term memory (main session only)
├── memory/
│   ├── daily/             # Daily records
│   │   ├── 2026-03-02.md
│   │   ├── 2026-03-03.md
│   │   └── 2026-03-04.md
│   ├── knowledge/         # Knowledge base
│   │   ├── react-basics.md
│   │   └── flask-api.md
│   ├── daily-index.md     # Daily memory index
│   └── knowledge-index.md # Knowledge index
```

---

## Comparison

| Metric | Traditional | Memory Master v1.2 |
|--------|-------------|---------------------|
| Recall precision | ~30% | ~95% |
| Token cost per recall | High (full file) | Near zero (targeted) |
| Proactive recall | ❌ | ✅ (heuristic) |
| Knowledge learning | ❌ | ✅ |
| API dependencies | Vector DB / OpenAI | None |
| Setup complexity | High | Zero |
| Latency | Variable | Instant |

---

## Requirements

**None.** This skill works with pure OpenClaw:

- ✅ OpenClaw installed
- ✅ Workspace configured
- ✅ That's it!

**No external APIs. No embeddings. No costs.**

---

## Installation

### 1. Install Skill
```bash
clawdhub install memory-master
```

### 2. Auto-Initialize (Recommended)
```bash
# This will automatically:
# - Create memory directories
# - Replace old memory rules in MEMORY.md with memory-master rules
# - Create index files
clawdhub init memory-master
```

Or manually:
```bash
# 1. Replace memory rules in MEMORY.md:
#    - Delete old memory-related sections in your MEMORY.md
#    - Add memory-master-rules.md content

# 2. Create index files
cp ~/.agents/skills/memory-master/templates/daily-index.md ~/.openclaw/workspace/memory/daily-index.md
cp ~/.agents/skills/memory-master/templates/knowledge-index.md ~/.openclaw/workspace/memory/knowledge-index.md

# 3. Create directories
mkdir ~/.openclaw/workspace/memory/daily
mkdir ~/.openclaw/workspace/memory/knowledge
```

# Create daily index
cp ~/.agents/skills/memory-master/templates/daily-index.md ~/.openclaw/workspace/memory/daily-index.md

# Create knowledge index  
cp ~/.agents/skills/memory-master/templates/knowledge-index.md ~/.openclaw/workspace/memory/knowledge-index.md

# Create directories
mkdir ~/.openclaw/workspace/memory/daily
mkdir ~/.openclaw/workspace/memory/knowledge
```

---

## ⚠️ Security & Privacy

- **100% Local**: All memory/knowledge stored in local workspace files only. Nothing leaves your machine except your initiated web searches.
- **Auto-Write to Local**: This is a FEATURE — prevents information loss. Same as OpenClaw's native memory system.
- **Auto Learning**: When local knowledge is insufficient, automatically search web to learn. Writes results to local knowledge base only.
- **Full Transparency**: All files visible/editable/deletable by user anytime.
- **Safe**: No data uploaded, only search queries sent to search engines.
- **User Control**: User explicitly authorizes web searches ("我去查一下", "let me search the web") before any network activity

---

## Triggers

### Memory Recall
- "that"
- "上次"
- "之前"
- "昨天"
- "earlier"
- Or: when you realize you don't have the context

### Knowledge Learning
- When you can't find answer in knowledge base
- User asks something new

### Memory Writing
- Discussion reaches conclusion
- Decision made
- Action assigned

---

## Best Practices

1. **Write immediately** — Don't wait, write right after conclusion
2. **Keep it brief** — One line per point, but core info preserved
3. **Use the template** — 因 → 改 → 待
4. **Update index** — Always sync after writing
5. **Heuristic recall** — Don't wait for user to trigger
6. **Learn proactively** — When you don't know, say it and learn

---

## The Memory Master Promise

> *"An AI agent is only as good as its memory. Give your agent a memory system that never forgets, never wastes, and always delivers exactly what's needed."*

**Memory Master v1.2.0 — Because remembering everything is just as important as learning something new.** 🧠⚡