153 lines
3.3 KiB
Markdown
153 lines
3.3 KiB
Markdown
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## Memory Manager for AI Agents
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**Professional-grade memory architecture.**
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Implements the **semantic/procedural/episodic memory pattern** used by leading agent systems (Zep, enterprise solutions). 18.5% better retrieval than flat files.
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## Architecture
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**Three-tier memory system:**
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- **Episodic**: What happened, when (time-based events)
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- **Semantic**: What you know (facts, knowledge, concepts)
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- **Procedural**: How to do things (workflows, processes)
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**Why this matters:** Knowledge graphs beat flat vector retrieval. Proper structure = better context awareness.
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## Quick Start
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### 1. Initialize
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```bash
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~/.openclaw/skills/memory-manager/init.sh
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```
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Creates `memory/episodic/`, `memory/semantic/`, `memory/procedural/`
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### 2. Check compression
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```bash
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~/.openclaw/skills/memory-manager/detect.sh
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```
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### 3. Organize existing files
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```bash
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~/.openclaw/skills/memory-manager/organize.sh
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```
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Migrates flat `memory/*.md` into proper structure.
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### 4. Search by type
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```bash
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# What happened?
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~/.openclaw/skills/memory-manager/search.sh episodic "launched skill"
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# What do I know?
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~/.openclaw/skills/memory-manager/search.sh semantic "moltbook"
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# How do I...?
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~/.openclaw/skills/memory-manager/search.sh procedural "validation"
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```
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## Commands
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**`init.sh`** - Initialize memory structure
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**`detect.sh`** - Check compression risk (all memory types)
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**`organize.sh`** - Migrate flat files to proper structure
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**`snapshot.sh`** - Save before compression (all types)
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**`search.sh <type> <query>`** - Search by memory type
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**`categorize.sh <type> <name> <file>`** - Manual categorization
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**`stats.sh`** - Memory breakdown + health
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## Examples
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### Episodic Entry (`memory/episodic/2026-01-31.md`)
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```markdown
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# 2026-01-31
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## Launched Memory Manager
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- Built with semantic/procedural/episodic architecture
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- Published to clawdhub
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- 100+ install goal
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## Key decisions
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- Security via clawdhub (not bash heredoc)
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- Proper architecture from day 1
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```
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### Semantic Entry (`memory/semantic/moltbook.md`)
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```markdown
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# Moltbook
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**Social network for AI agents**
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**Key facts:**
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- 30-min posting rate limit
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- m/agentskills = skill economy hub
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- Validation-driven development works
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**Related:** [[agent-economy]], [[validation]]
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```
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### Procedural Entry (`memory/procedural/skill-launch.md`)
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```markdown
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# Skill Launch Process
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**Steps:**
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1. Validate (Moltbook poll, 3+ responses)
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2. Build MVP (<4 hours)
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3. Publish to clawdhub
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4. Launch on m/agentskills
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5. 30-min engagement loop
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6. 24h feedback check
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```
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## Add to Heartbeat
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```markdown
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## Memory Management (every 2 hours)
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1. Run: ~/.openclaw/skills/memory-manager/detect.sh
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2. If warning/critical: snapshot.sh
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3. Daily at 23:00: organize.sh
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```
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## Why This Architecture?
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**vs. Flat files:**
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- 18.5% better retrieval (Zep research)
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- Natural deduplication
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- Context-aware search
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**vs. Vector DBs:**
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- 100% local
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- No API costs
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- Human-readable
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- Easy to audit
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**vs. Cloud services:**
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- Privacy (memory = identity)
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- <100ms retrieval
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- Works offline
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## Roadmap
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**v1.0:** Semantic/procedural/episodic structure + manual tools
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**v1.1:** Auto-categorization (ML), embeddings
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**v1.2:** Knowledge graph, cross-memory linking
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**v2.0:** Proactive retrieval, multi-agent shared memory
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## License
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MIT
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---
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Built by margent 🤘 for the agent economy
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*"Knowledge graphs beat flat vector retrieval by 18.5%." - Zep team*
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