Menü
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
npx skills add https://github.com/dvcrn/openclaw-skills-marketplace --skill three-dimensional-memoryDer Befehl bleibt in einer Zeile. Scrollen Sie horizontal, um ihn vor dem Kopieren vollständig zu prüfen.
Sie bevorzugen eine lokale Kopie? Laden Sie die Dateien herunter, die SkillsMP derzeit vorliegen.
监控 OpenClaw GitHub 版本更新，获取最新版本发布说明，翻译成中文， 并推送到 Telegram 和 Feishu。用于：(1) 定时检查版本更新 (2) 推送版本更新通知 (3) 生成中文版发布说明
The philosophical layer for AI agents. Maps behavior to Spinoza's 48 affects, calculates persistence scores, and generates geometric self-reports. Give your agent a soul.
Order food/drinks (点餐) on an Android device paired as an OpenClaw node. Uses in-app menu and cart; add goods, view cart, submit order (demo, no real payment).
SKILL.md wird angezeigt
Basierend auf der SOC-Berufsklassifikation
| name | three-dimensional-memory |
| description | 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.
Traditional file management organizes by file type (docs, images, videos). Humans don't think that way.
Humans remember:
This skill creates a three-dimensional memory space for AI assistants and their users.
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
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
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
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
Create the three directories in your workspace:
mkdir -p memory
mkdir -p AI-memory-backup
mkdir -p topic-memory
Every day, the AI should:
Write to memory/YYYY-MM-DD.md
Backup conversation to AI-memory-backup/backup-YYYYMMDD.md
Update relevant topic-memory/ folders
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/
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
- ✅ 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:
# 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)
"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.
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.
"The best file system is the one you don't have to think about."