# Three Dimensional Memory > three-dimensional-memory - Skill: `johnalbertini14-glitch/three-dimensional-memory` (Agent Skill, multi-file: 5 files) - Install (CLI): `npx skillmds@latest add johnalbertini14-glitch/three-dimensional-memory` - Raw SKILL.md: https://api.skillmd.com/api/skills/johnalbertini14-glitch/three-dimensional-memory/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: johnalbertini14-glitch (https://skillmd.com/u/johnalbertini14-glitch) - Updated: 2026-09-21 - Page: https://skillmd.com/skills/johnalbertini14-glitch/three-dimensional-memory --- # three-dimensional-memory **Three-Dimensional Memory System for AI Assistants** — 人类思维方式的文件记忆管理 A memory management system that mirrors human cognition: organized by time, conversation, and topics. --- ## 🎯 Why This Skill? Traditional file management organizes by file type (docs, images, videos). Humans don't think that way. Humans remember: - **When** it happened (time) - **What was said** (conversation) - **What it was about** (topic) This skill creates a three-dimensional memory space for AI assistants and their users. --- ## 🧠 The Three Dimensions ### Dimension 1: Timeline Memory ``` memory/ ├── 2026-02-21.md ← What happened today ├── 2026-02-22.md ← What happened today └── 2026-02-23.md ← What happened today ``` **Purpose**: Daily work logs, chronological record of events **Update frequency**: Daily **Content**: Tasks completed, decisions made, meetings held --- ### Dimension 2: Conversation Stream ``` AI-memory-backup/ ├── backup-20260221.md ← Complete conversation transcript ├── backup-20260222.md ← Complete conversation transcript └── backup-20260223.md ← Complete conversation transcript ``` **Purpose**: Full context preservation, searchable dialogue history **Update frequency**: Per conversation **Content**: Every word exchanged, including user messages and AI responses --- ### Dimension 3: Topic Network ``` topic-memory/ ├── project-product-launch/ │ ├── proposal-v1.md │ ├── proposal-v2.md │ └── final-version.md │ ├── decision-org-restructure/ │ ├── options-considered.md │ ├── final-decision.md │ └── implementation-plan.md │ └── knowledge-market-analysis/ ├── competitor-research.md └── trend-report.md ``` **Purpose**: Project-centric information aggregation **Update frequency**: As projects evolve **Content**: All documents, decisions, and knowledge related to a specific topic --- ## 📁 Recommended File Structure ``` workspace/ │ ├── memory/ ← Dimension 1: Timeline │ ├── 2026-02-21.md │ ├── 2026-02-22.md │ └── 2026-02-23.md │ ├── AI-memory-backup/ ← Dimension 2: Conversation │ ├── backup-20260221.md │ ├── backup-20260222.md │ └── backup-20260223.md │ ├── topic-memory/ ← Dimension 3: Topics │ ├── project-[name]/ │ ├── decision-[name]/ │ ├── system-[name]/ │ └── knowledge-[name]/ │ ├── skills/ ← AI capabilities │ ├── MEMORY.md ← AI's long-term identity ├── SOUL.md ← AI's personality └── USER.md ← User preferences ``` --- ## 🚀 Quick Start ### Step 1: Initialize Structure Create the three directories in your workspace: ```bash mkdir -p memory mkdir -p AI-memory-backup mkdir -p topic-memory ``` ### Step 2: Daily Workflow **Every day**, the AI should: 1. **Write to `memory/YYYY-MM-DD.md`** - Summary of today's work - Decisions made - Tasks completed 2. **Backup conversation to `AI-memory-backup/backup-YYYYMMDD.md`** - Full transcript - Important context - User preferences learned 3. **Update relevant `topic-memory/` folders** - Add new documents to projects - Update decision records - Consolidate knowledge ### Step 3: Access Information **Find by time**: "What did we do on Monday?" → Check `memory/` **Find by context**: "What exactly did I say about pricing?" → Check `AI-memory-backup/` **Find by topic**: "Where's the product launch plan?" → Check `topic-memory/project-product-launch/` --- ## 📝 Example: A Day in Three Dimensions ### Scenario: Product Strategy Meeting **Dimension 1 - memory/2026-02-23.md**: ```markdown # 2026-02-23 Work Log ## Morning - Product strategy meeting with CEO - Decided on three-tier pricing model - Delayed launch by 2 weeks for additional testing ## Afternoon - Drafted pricing proposal - Created financial projections - Scheduled follow-up for tomorrow ## Decisions - ✅ Adopt tiered pricing (Basic/Pro/Enterprise) - ✅ Delay launch from March 1 → March 15 - ❌ Do not offer early-bird discounts ``` **Dimension 2 - AI-memory-backup/backup-20260223.md**: ```markdown # Conversation Backup - 2026-02-23 ## Product Pricing Discussion User: "We need to decide on pricing today." AI: "What are you considering?" User: "I'm thinking three tiers: $29, $99, $299" AI: "Have you considered the psychology of pricing? $29 might signal 'cheap', $299 signals 'premium'." User: "Good point. Let's go with $39, $99, $299" [Full conversation continues...] ``` **Dimension 3 - topic-memory/project-product-launch/**: ```markdown # Product Launch Project ## pricing-strategy.md (updated today) Final decision: Three-tier model - Starter: $39/month - Professional: $99/month - Enterprise: $299/month ## timeline.md (updated today) Launch date: March 15, 2026 (delayed from March 1) ## key-decisions.md - Pricing tiers finalized (2026-02-23) - Launch delayed for QA (2026-02-23) ``` --- ## 💡 Best Practices ### For Users 1. **Review daily logs weekly** - Quick scan of what happened 2. **Search conversation backups** - Find exact quotes and context 3. **Use topic folders** - Navigate by project, not by file type 4. **Keep MEMORY.md updated** - AI's identity and your preferences ### For AI Assistants 1. **Update all three dimensions daily** - Don't skip any 2. **Be consistent with naming** - Use clear, searchable topic names 3. **Cross-reference** - Link between dimensions when relevant 4. **Maintain the index** - Keep a master index of active topics --- ## 🔍 Troubleshooting **"I can't find a file"** → Check all three dimensions. If it's not in timeline or topic, search conversation backup. **"There's duplicate information"** → That's by design! Timeline shows when, topic shows what, conversation shows why. **"The AI forgot what we discussed"** → Check AI-memory-backup/. The full context is there. --- ## 🌟 Why It Works Traditional file management: **"Where did I save that document?"** Three-dimensional memory: **"We discussed pricing in yesterday's meeting"** → Check `memory/2026-02-23.md` → Find reference to `topic-memory/project-pricing/` → Open latest version **Result**: Find files in 10 seconds instead of 5 minutes. --- ## 📄 Metadata - **Author**: @openclaw-user - **Created**: 2026-02-23 - **Version**: 1.0.0 - **License**: MIT - **Tags**: memory, organization, productivity, workflow --- *"The best file system is the one you don't have to think about."*