# Memory Master

> Local memory and knowledge base system with structured indexing and auto-index. Write to local files only. Network learning is a SEPARATE optional feature — user must explicitly trigger it (say '我去查一下'). Full user control: all files visible, editable, deletable.

- Skill: `modbender/memory-master` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add modbender/memory-master`
- Raw SKILL.md: https://api.skillmd.com/api/skills/modbender/memory-master/raw
- Safety review: pending (external: skill-scanner PASS, skillspector CAUTION)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: modbender (https://skillmd.com/u/modbender)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/modbender/memory-master

---


# 🧠 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 |
| **🧠 Network Learning** | SEPARATE feature — user must EXPLICITLY say "我去查一下" or "let me search the web" to trigger |
| **🔓 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**

- 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：告知"我不会" → 网络学习 → 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

### ⚠️ IMPORTANT: Auto-Trigger Write

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

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

### 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)

### 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

- **Local by Default**: Memory/knowledge writes to local workspace files only
- **Network Learning is Separate**: Must be explicitly triggered by user saying "我去查一下" or "let me search" — NOT automatic
- **Full Control**: User can view/edit/delete any file in memory/ at any time
- **No Secrets**: Do NOT store API keys, passwords, or sensitive data in memory files
- **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.** 🧠⚡