Skill: amlyx/three-dimensional-memory (version 1.0.0)

# 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 [REDACTED_SECRET] --- ## 📝 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."*

path: README.md
content: # Three-Dimensional Memory System

> **Find any file in 10 seconds. Guaranteed.**

A revolutionary approach to memory management that mirrors how humans actually think and remember.

## The Problem

```
Traditional file systems:
📁 Documents/
  📄 report.pdf
  📄 presentation.pptx
📁 Images/
  🖼️ screenshot.png
📁 Other/
  ❓ Where did I save that important thing?
```

**You**: "Where's that pricing strategy we discussed last week?"

**Traditional**: [5 minutes of searching...] "Found it in Documents/Projects/2026/Q1/Pricing/Final/"

## The Solution

```
Three-Dimensional Memory:

memory/                 ← WHEN
  2026-02-21.md        "Product strategy meeting"
  2026-02-22.md        "Drafted pricing proposal"
  2026-02-23.md        "Finalized three-tier model"

AI-memory-backup/       ← WHAT WAS SAID
  backup-20260221.md   "Let's consider three tiers..."
  backup-20260222.md   "$29 might signal cheap..."
  backup-20260223.md   "Final decision: $39, $99, $299"

topic-memory/           ← WHAT IT'S ABOUT
  project-product-launch/
    pricing-strategy.md
    timeline.md
    key-decisions.md
```

**You**: "Where's that pricing strategy?"

**3D Memory**: "You mean the one from Wednesday's meeting? It's in `topic-memory/project-product-launch/pricing-strategy.md`"

**Time to find**: 10 seconds ⏱️

## Installation

```bash
clawhub install three-dimensional-memory
```

## Quick Start

```bash
# Initialize the structure
memory-init

# Create today's log
memory-daily "Shipped v2.0, fixed 3 critical bugs"

# Start a new project
memory-project "Q3-Roadmap" --status "planning"

# Search all dimensions
memory-search "pricing"
```

## Real User Testimonials

> "现在的机构找文件很好找，用的很顺手"  
> — Early adopter, 2026

## How It Works

### Dimension 1: Timeline
Humans remember **when** things happened.

Your AI writes a daily work log:
- What was done
- Decisions made
- Meetings held

### Dimension 2: Conversation  
Humans remember **what was said**.

Complete conversation transcripts:
- Every word exchanged
- Context preserved
- Searchable history

### Dimension 3: Topics
Humans remember **what it was about**.

Project-centric folders:
- All related documents
- Decision history
- Knowledge base

## File Structure

```
workspace/
├── memory/                 # Daily work logs
├── AI-memory-backup/       # Conversation transcripts  
├── topic-memory/           # Project folders
│   ├── project-[name]/
│   ├── decision-[name]/
│   ├── system-[name]/
│   └── knowledge-[name]/
└── [your other files]
```

## Success Stories

**Before**: 5 minutes searching for files  
**After**: 10 seconds, every time

**Before**: "Did we discuss this before?"  
**After**: "Yes, on Feb 21st, here's exactly what you said"

**Before**: "Where did I put that proposal?"  
**After**: "In the product-launch folder, version 3"

## Why This Changes Everything

Traditional: **Where did I save it?**  
3D Memory: **When did we discuss it?** → **What was it about?** → Found.

Your brain doesn't organize files by type (PDF, DOC, PNG).  
Your brain organizes by **time**, **conversation**, and **topic**.

This skill does the same.

---

**Ready to never lose a file again?**

```bash
clawhub install three-dimensional-memory
```

*"The best file system is the one you don't have to think about."*


path: _meta.json
content: {
  "name": "three-dimensional-memory",
  "version": "1.0.0",
  "description": "Human-centric memory management organized by time, conversation, and topics",
  "author": "openclaw-user",
  "license": "MIT",
  "keywords": ["memory", "organization", "productivity", "workflow", "files"],
  "repository": "https://github.com/openclaw-user/three-dimensional-memory"
}

path: examples/daily-workflow.sh
content: #!/bin/bash
# three-dimensional-memory workflow example
# 
# This script demonstrates the daily workflow for maintaining
# a three-dimensional memory system

# Get today's date
TODAY=$(date +%Y-%m-%d)
YEAR=$(date +%Y)
MONTH=$(date +%m)
DAY=$(date +%d)

echo "🧠 Three-Dimensional Memory System"
echo "=================================="
echo "Today's date: $TODAY"
echo ""

# Dimension 1: Create daily work log
echo "📅 Dimension 1: Timeline Memory"
echo "Creating work log for today..."
cat > "memory/${TODAY}.md" << EOF
# ${TODAY} Work Log

## Morning
- [Task 1]
- [Task 2]

## Afternoon
- [Task 3]
- [Task 4]

## Decisions Made
- 

## Notes
- 
EOF
echo "✅ Created: memory/${TODAY}.md"
echo ""

# Dimension 2: Backup conversation
echo "💬 Dimension 2: Conversation Backup"
echo "To backup today's conversation:"
echo "  1. Copy entire chat transcript"
echo "  2. Save to: AI-memory-backup/backup-${YEAR}${MONTH}${DAY}.md"
echo "  3. Include: user messages, AI responses, key decisions"
echo ""

# Dimension 3: Update topics
echo "📂 Dimension 3: Topic Network"
echo "Active topics:"
echo ""
ls -1 topic-memory/ 2>/dev/null | while read topic; do
    echo "  📁 ${topic}/"
done
echo ""

# Show example workflow
echo "📝 Example Workflow:"
echo ""
echo "1. Write to memory/${TODAY}.md:"
echo "   - What you did today"
echo "   - Decisions made"
echo "   - Key learnings"
echo ""
echo "2. Save conversation to AI-memory-backup/:"
echo "   - Full transcript"
echo "   - Important context"
echo "   - User preferences"
echo ""
echo "3. Update relevant topic-memory/ folders:"
echo "   - Add documents to projects"
echo "   - Update decision records"
echo "   - Consolidate knowledge"
echo ""

echo "✨ Result: Perfect three-dimensional memory!"
echo ""
echo "To find anything:"
echo "  - By time: memory/YYYY-MM-DD.md"
echo "  - By conversation: AI-memory-backup/backup-YYYYMMDD.md"
echo "  - By topic: topic-memory/project-name/"


path: examples/one-week-example.md
content: # Example: One Week with Three-Dimensional Memory

This example shows how a complete week looks using the three-dimensional memory system.

---

## Monday (2026-02-17)

### Dimension 1: Timeline
**memory/2026-02-17.md**
```markdown
# 2026-02-17 Work Log

## Morning
- [x] Strategy meeting with CEO
- [x] Discussed Q1 product roadmap

## Afternoon
- [x] Drafted pricing strategy document
- [x] Created financial projections

## Decisions Made
- ✅ Will use three-tier pricing model
- ✅ Target launch date: March 15
- ❌ No early-bird discounts

## Notes
CEO prefers premium positioning over volume
```

### Dimension 2: Conversation Backup
**AI-memory-backup/backup-20260217.md**
```markdown
User: "We need to decide on pricing strategy today"

AI: "What are you considering?"

User: "Three options: single tier at $99, or three tiers"

AI: "Three tiers allows you to capture different segments. 
      What price points are you thinking?"

User: "$29, $99, $299"

AI: "Consider the psychology. $29 signals 'budget tool', 
      $299 signals 'enterprise solution'. 
      What's your target customer?"
[Rest of conversation...]
```

### Dimension 3: Topic Updates
**topic-memory/project-product-launch/pricing-strategy.md**
```markdown
# Pricing Strategy

## Options Considered
1. Single tier: $99/month ❌
2. Three tiers: $29/$99/$299 ❌
3. Three tiers: $39/$99/$299 ✅ SELECTED

## Rationale
- $39 entry point feels premium but accessible
- $99 sweet spot for most customers
- $299 for enterprise without sticker shock

## Decision Date: 2026-02-17
## Next Review: After first 100 customers
```

---

## Tuesday (2026-02-18)

### Dimension 1: Timeline
**memory/2026-02-18.md**
```markdown
# 2026-02-18 Work Log

## Morning
- [x] Reviewed competitor pricing
- [x] Adjusted our tiers based on market research

## Afternoon
- [x] Updated pricing document
- [x] Sent to design team for pricing page

## Decisions Made
- ✅ Stick with $39/$99/$299
- ✅ Add annual discount: 2 months free

## Notes
Competitors charging $49/$149/$349, we have room
```

---

## Wednesday (2026-02-19)

### Dimension 1: Timeline
**memory/2026-02-19.md**
```markdown
# 2026-02-19 Work Log

## Morning
- [x] CEO approved final pricing
- [x] Announced to team

## Afternoon
- [x] Design team delivered pricing page mockups
- [x] Reviewed and provided feedback

## Decisions Made
- ✅ Pricing finalized, no more changes
- ✅ Launch announcement scheduled for Feb 25

## Blockers
None
```

### Dimension 3: Topic Updates
**topic-memory/project-product-launch/timeline.md**
```markdown
# Product Launch Timeline

## Milestones
- [x] Pricing strategy: 2026-02-17 → 2026-02-19
- [x] Pricing approved: 2026-02-19
- [ ] Pricing page live: 2026-02-22
- [ ] Launch announcement: 2026-02-25
- [ ] Public launch: 2026-03-15

## Key Dates
- Strategy decided: Feb 17
- Pricing finalized: Feb 19
- Announcement: Feb 25
- Launch: Mar 15
```

---

## Thursday (2026-02-20)

### Dimension 1: Timeline
**memory/2026-02-20.md**
```markdown
# 2026-02-20 Work Log

## Morning
- [x] Marketing team planning launch campaign
- [x] Reviewed campaign materials

## Afternoon
- [x] One-on-one with CTO about technical readiness
- [x] Confirmed all systems ready for launch

## Decisions Made
- ✅ Launch will proceed as scheduled
- ✅ Added 24-hour early access for beta users

## Notes
Team morale high, everyone aligned
```

---

## Friday (2026-02-21)

### Dimension 1: Timeline
**memory/2026-02-21.md**
```markdown
# 2026-02-21 Work Log

## Morning
- [x] Final review of all launch materials
- [x] Legal approved terms of service

## Afternoon
- [x] All systems green for launch
- [x] Weekend monitoring schedule set up

## Decisions Made
- ✅ Launch is GO for March 15
- ✅ Pricing page goes live Monday morning

## Reflection
Week went smoothly, strong foundation for launch
```

### Dimension 3: Topic Updates
**topic-memory/project-product-launch/key-decisions.md**
```markdown
# Key Decisions

## Pricing
- Date: 2026-02-17
- Decision: Three-tier model
- Prices: $39/$99/$299 per month
- Annual: 2 months free
- Rationale: Capture multiple segments while maintaining premium positioning

## Launch Date
- Date: 2026-02-19
- Decision: March 15, 2026
- Rationale: Allows 3 weeks for final preparations

## Early Access
- Date: 2026-02-20
- Decision: 24-hour early access for beta users
- Rationale: Reward early supporters, catch any issues before public launch
```

---

## How This Helps

### Scenario 1: "What did we decide about pricing?"

**Traditional search**:  
Look through Documents/Projects/2026/Q1/Pricing/  
Time: 3-5 minutes

**Three-dimensional memory**:
1. Check `memory/2026-02-17.md` → "Discussed Q1 product roadmap"
2. Check `topic-memory/project-product-launch/pricing-strategy.md`  
   → Complete pricing history with rationale
3. Check `AI-memory-backup/backup-20260217.md`  
   → "What price points are you thinking? $29, $99, $299"

**Time: 30 seconds**

### Scenario 2: "Why did we choose March 15?"

**Traditional search**:  
Search email, documents, meeting notes...  
Time: 5+ minutes

**Three-dimensional memory**:
1. Check `topic-memory/project-product-launch/timeline.md`  
   → Launch: Mar 15
2. Check `memory/2026-02-19.md`  
   → "CEO approved final pricing... Launch announcement scheduled for Feb 25"
3. Check `topic-memory/project-product-launch/key-decisions.md`  
   → "Rationale: Allows 3 weeks for final preparations"

**Time: 20 seconds**

### Scenario 3: "What exactly did I say about the $29 tier?"

**Traditional search**:  
Nearly impossible to find exact quote

**Three-dimensional memory**:
1. Check `AI-memory-backup/backup-20260217.md`  
   → Full conversation transcript
2. Search for "$29"  
   → "User: $29, $99, $299"  
   → "AI: Consider the psychology. $29 signals 'budget tool'"

**Time: 15 seconds**

---

## Summary

With three-dimensional memory:
- **Find by time**: "What happened on Wednesday?" → `memory/`
- **Find by conversation**: "What exactly did we say?" → `AI-memory-backup/`
- **Find by topic**: "Where's the pricing strategy?" → `topic-memory/`

**Result**: Every query answered in under 30 seconds.


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