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Three-Dimensional Memory

Manages AI assistant memory by organizing files across three dimensions: timeline logs, full conversation backups, and topic-based project folders for easy r...

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Manages AI assistant memory by organizing files across three dimensions: timeline logs, full conversation backups, and topic-based project folders for easy r...

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
README.md, SKILL.md, _meta.json, examples/daily-workflow.sh, examples/one-week-example.md

Validation

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  • Review SKILL.md after the package is downloaded.
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New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.

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Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 15 sections Open source page

three-dimensional-memory

Three-Dimensional Memory System for AI Assistants โ€” ไบบ็ฑปๆ€็ปดๆ–นๅผ็š„ๆ–‡ไปถ่ฎฐๅฟ†็ฎก็† A memory management system that mirrors human cognition: organized by time, conversation, and topics.

๐ŸŽฏ 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.

Dimension 1: Timeline Memory

memory/ โ”œโ”€โ”€ 2026-02-21.md โ† What happened today โ”œโ”€โ”€ 2026-02-22.md โ† What happened today โ””โ”€โ”€ 2026-02-23.md โ† 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/ โ”œโ”€โ”€ backup-20260221.md โ† Complete conversation transcript โ”œโ”€โ”€ backup-20260222.md โ† Complete conversation transcript โ””โ”€โ”€ backup-20260223.md โ† 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/ โ”œโ”€โ”€ project-product-launch/ โ”‚ โ”œโ”€โ”€ proposal-v1.md โ”‚ โ”œโ”€โ”€ proposal-v2.md โ”‚ โ””โ”€โ”€ final-version.md โ”‚ โ”œโ”€โ”€ decision-org-restructure/ โ”‚ โ”œโ”€โ”€ options-considered.md โ”‚ โ”œโ”€โ”€ final-decision.md โ”‚ โ””โ”€โ”€ implementation-plan.md โ”‚ โ””โ”€โ”€ knowledge-market-analysis/ โ”œโ”€โ”€ competitor-research.md โ””โ”€โ”€ trend-report.md Purpose: Project-centric information aggregation Update frequency: As projects evolve Content: All documents, decisions, and knowledge related to a specific topic

๐Ÿ“ Recommended File Structure

workspace/ โ”‚ โ”œโ”€โ”€ memory/ โ† Dimension 1: Timeline โ”‚ โ”œโ”€โ”€ 2026-02-21.md โ”‚ โ”œโ”€โ”€ 2026-02-22.md โ”‚ โ””โ”€โ”€ 2026-02-23.md โ”‚ โ”œโ”€โ”€ AI-memory-backup/ โ† Dimension 2: Conversation โ”‚ โ”œโ”€โ”€ backup-20260221.md โ”‚ โ”œโ”€โ”€ backup-20260222.md โ”‚ โ””โ”€โ”€ backup-20260223.md โ”‚ โ”œโ”€โ”€ topic-memory/ โ† Dimension 3: Topics โ”‚ โ”œโ”€โ”€ project-[name]/ โ”‚ โ”œโ”€โ”€ decision-[name]/ โ”‚ โ”œโ”€โ”€ system-[name]/ โ”‚ โ””โ”€โ”€ knowledge-[name]/ โ”‚ โ”œโ”€โ”€ skills/ โ† AI capabilities โ”‚ โ”œโ”€โ”€ MEMORY.md โ† AI's long-term identity โ”œโ”€โ”€ SOUL.md โ† AI's personality โ””โ”€โ”€ USER.md โ† User preferences

Step 1: Initialize Structure

Create the three directories in your workspace: mkdir -p memory mkdir -p AI-memory-backup mkdir -p topic-memory

Step 2: Daily Workflow

Every day, the AI should: Write to memory/YYYY-MM-DD.md Summary of today's work Decisions made Tasks completed Backup conversation to AI-memory-backup/backup-YYYYMMDD.md Full transcript Important context User preferences learned 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?" โ†’ Check memory/ Find by context: "What exactly did I say about pricing?" โ†’ Check AI-memory-backup/ Find by topic: "Where's the product launch plan?" โ†’ Check topic-memory/project-product-launch/

Scenario: Product Strategy Meeting

  • Dimension 1 - memory/2026-02-23.md:
  • # 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
  • โœ… Adopt tiered pricing (Basic/Pro/Enterprise)
  • โœ… Delay launch from March 1 โ†’ March 15
  • โŒ Do not offer early-bird discounts
  • Dimension 2 - AI-memory-backup/backup-20260223.md:
  • # 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/:
  • # 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)

For Users

Review daily logs weekly - Quick scan of what happened Search conversation backups - Find exact quotes and context Use topic folders - Navigate by project, not by file type Keep MEMORY.md updated - AI's identity and your preferences

For AI Assistants

Update all three dimensions daily - Don't skip any Be consistent with naming - Use clear, searchable topic names Cross-reference - Link between dimensions when relevant Maintain the index - Keep a master index of active topics

๐Ÿ” Troubleshooting

"I can't find a file" โ†’ Check all three dimensions. If it's not in timeline or topic, search conversation backup. "There's duplicate information" โ†’ That's by design! Timeline shows when, topic shows what, conversation shows why. "The AI forgot what we discussed" โ†’ Check AI-memory-backup/. The full context is there.

๐ŸŒŸ Why It Works

Traditional file management: "Where did I save that document?" Three-dimensional memory: "We discussed pricing in yesterday's meeting" โ†’ Check memory/2026-02-23.md โ†’ Find reference to topic-memory/project-pricing/ โ†’ Open latest version Result: Find files in 10 seconds instead of 5 minutes.

๐Ÿ“„ 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."

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
3 Docs1 Scripts1 Config
  • SKILL.md Primary doc
  • examples/one-week-example.md Docs
  • README.md Docs
  • examples/daily-workflow.sh Scripts
  • _meta.json Config