Memory Master

Local memory system with structured indexing and auto-learning. Auto-write, heuristic recall, auto learning when knowledge is insufficient. Compatible with s...

Security Scan

The skill largely does what it says (local memory, indexing, and write/recall), but its runtime instructions and shipped scripts give it broad authority to auto-modify your workspace files (AGENTS.md, MEMORY.md, HEARTBEAT.md) and to run actions after every response without declaring those config paths or requiring binaries—this mismatch and the automatic-write/auto-learn behavior warrant caution.

Purpose & Capability

The skill's name and description (local memory, indexing, heuristic recall, auto-learning) align with the included files: templates, SKILL.md, and two Node scripts for init and compression detection. However, the skill will modify important workspace files (AGENTS.md, MEMORY.md, HEARTBEAT.md) and create ~/.openclaw/workspace/memory/ files, yet the registry metadata lists no required config paths or required binaries. That omission is unexpected because the scripts operate on a specific workspace path and package.json indicates an init script that requires Node.

Instruction Scope

SKILL.md and README explicitly instruct the agent to auto-write memory entries ("Before every response, quickly check... write immediately if new"), to run compression detection after every response, and to automatically migrate/modify AGENTS.md and MEMORY.md during initialization. Those instructions grant the agent broad discretion to read and overwrite user workspace files and to perform automatic web searches when knowledge is missing. This is outside a minimal passive memory-read scope and can cause persistent changes without per-action user confirmation.

Install Mechanism

There is no remote download or installer—no install spec—so code is not fetched at install time. The package includes scripts/init.js and scripts/detect.js and package.json references an initScript and 'requiresNode'. Running these scripts (clawdhub init or node scripts/init.js) will perform file operations on the user's workspace. The absence of a declared install step or required binary (Node) in the registry metadata is an inconsistency to be aware of.

Credentials

The skill declares no required environment variables or credentials, and the code does not exfiltrate secrets. It does, however, read the WORKSPACE env var (fallbacks to ~/.openclaw/workspace) and directly reads/writes files in that directory. That file-system access is reasonable for a local memory manager, but the registry metadata failing to surface that required config path is a transparency gap. The skill also references automatic 'network learning' flows in its instructions (mentions tavily/web_fetch), but does not require or declare credentials for any external service—meaning the network behavior depends on other agent skills or tools and is not controlled here.

Persistence & Privilege

The skill does not request always:true, but its runtime rules instruct the agent to automatically write to disk before every response and to migrate/overwrite AGENTS.md and other workspace files during init. Because agents can invoke skills autonomously, this yields a significant ability to alter the agent's persistent behavior and configuration (AGENTS.md contains rules that are loaded every session). The combination of autonomous invocation + file-modifying instructions increases risk if you don't review/consent to changes.

What to consider before installing

This skill is coherent with its purpose (local memory and indexing) but it will actively modify your agent workspace (AGENTS.md, MEMORY.md, HEARTBEAT.md), create a backup folder, and recommends running a detect script after every response. Before installing: 1) Review the two included scripts (scripts/init.js and scripts/detect.js) yourself and confirm you trust them; 2) Back up ~/.openclaw/workspace (or set WORKSPACE to a sandbox) because init.js will rewrite AGENTS.md and MEMORY.md; 3) Be cautious about the "auto-write before every response" and "auto-learn (web search)" behaviors—if you want manual control, disable or modify those rules in the SKILL.md/templates before running init; 4) Note package.json signals an init script that requires Node even though the registry lists no required binaries—ensure your environment and policies allow running node scripts from this skill; 5) If you depend on external web-search tooling (tavily/web_fetch), verify how that will be invoked and what credentials (if any) it needs. If unsure, test the init script in an isolated workspace first.

🧠 Memory Master — The Precision Memory System

Transform your AI agent from forgetful to photographic.

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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.

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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.

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The Memory Format

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

Format:

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

Example:

## [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:

# 记忆索引

- 主题名 → daily/日期.md,日期.md

Example:

# 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

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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."

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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：

# 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

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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

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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

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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

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Requirements

None. This skill works with pure OpenClaw:

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

No external APIs. No embeddings. No costs.

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Installation

1. Install Skill

clawdhub install memory-master

2. Auto-Initialize (Enhanced for v2.6.0)

# This will automatically:
# - Migrate heartbeat rules from AGENTS.md to HEARTBEAT.md
# - Optimize AGENTS.md (deduplicate, streamline, restructure)
# - Convert MEMORY.md to pure lessons/experience repository
# - Create memory directory structure and index files
# - Backup original files to .memory-master-backup/ directory
clawdhub init memory-master

What the enhanced initialization does:

Step	Action	Result
1	Backup	Original files saved to .memory-master-backup/
2	Heartbeat Migration	Heartbeat content moved from AGENTS.md to HEARTBEAT.md
3	AGENTS.md Optimization	Remove duplicates, outdated rules, streamline language
4	MEMORY.md Transformation	Convert to pure lessons/experience repository
5	Memory Structure	Create memory/ directories and index files

Post-initialization files:

~/.openclaw/workspace/
├── AGENTS.md              # Optimized behavior rules + memory system rules
├── MEMORY.md              # Pure lessons/experience repository
├── HEARTBEAT.md           # Heartbeat tasks and guidelines
├── memory/
│   ├── daily/             # Daily records (YYYY-MM-DD.md format)
│   ├── knowledge/         # Knowledge base (*.md files)
│   ├── daily-index.md     # Memory index
│   └── knowledge-index.md # Knowledge index

Or manually (advanced users):

# 1. Run the initialization script directly
node ~/.agents/skills/memory-master/scripts/init.js

# 2. Or manually copy templates
cp ~/.agents/skills/memory-master/templates/optimized-agents.md ~/.openclaw/workspace/AGENTS.md
cp ~/.agents/skills/memory-master/templates/heartbeat-template.md ~/.openclaw/workspace/HEARTBEAT.md
cp ~/.agents/skills/memory-master/templates/memory-lessons.md ~/.openclaw/workspace/MEMORY.md

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

# 4. 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

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⚠️ 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

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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

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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

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Compression Detection (v2.6.3+)

⚠️ Important: Must run after EVERY response!

Run after every response:

node ~/.agents/skills/memory-master/scripts/detect.js

Display status at the bottom of every response:

• 50%: 📝 上下文使用率：50% - 是否需要记录记忆或知识库？
• 70%: ⚠️ 上下文使用率：70% - 建议记录当前进度
• 85%: 🚨 上下文使用率：85% - 请立即记录当前进度！

Why this matters:

• Prevents context loss from compression
• Reminds user to record memories before data is lost
• Works with heartbeat but runs more frequently

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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. 🧠⚡