Skill: lizhelong0907/memory-master (version 2.6.5)

--- name: memory-master version: 2.6.1 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 (Enhanced for v2.6.0) ```bash # 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): ```bash # 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 ``` --- ## ⚠️ 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 --- ## Compression Detection (v2.6.3+) **⚠️ Important: Must run after EVERY response!** ### Run after every response: ```bash 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 --- ## 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.** 🧠⚡


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)