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Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vib...
---
name: elite-longterm-memory
version: 1.2.3
description: "Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready."
author: NextFrontierBuilds
keywords: [memory, ai-agent, ai-coding, long-term-memory, vector-search, lancedb, git-notes, wal, persistent-context, claude, claude-code, gpt, chatgpt, cursor, copilot, github-copilot, openclaw, moltbot, vibe-coding, agentic, ai-tools, developer-tools, devtools, typescript, llm, automation]
metadata:
openclaw:
emoji: "🧠"
requires:
env:
- OPENAI_API_KEY
plugins:
- memory-lancedb
---
# Elite Longterm Memory 🧠
**The ultimate memory system for AI agents.** Combines 6 proven approaches into one bulletproof architecture.
Never lose context. Never forget decisions. Never repeat mistakes.
## Architecture Overview
```
┌─────────────────────────────────────────────────────────────────┐
│ ELITE LONGTERM MEMORY │
├─────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ HOT RAM │ │ WARM STORE │ │ COLD STORE │ │
│ │ │ │ │ │ │ │
│ │ SESSION- │ │ LanceDB │ │ Git-Notes │ │
│ │ STATE.md │ │ Vectors │ │ Knowledge │ │
│ │ │ │ │ │ Graph │ │
│ │ (survives │ │ (semantic │ │ (permanent │ │
│ │ compaction)│ │ search) │ │ decisions) │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ │ │ │ │
│ └────────────────┼────────────────┘ │
│ ▼ │
│ ┌─────────────┐ │
│ │ MEMORY.md │ ← Curated long-term │
│ │ + daily/ │ (human-readable) │
│ └─────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────┐ │
│ │ SuperMemory │ ← Cloud backup (optional) │
│ │ API │ │
│ └─────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
```
## The 5 Memory Layers
### Layer 1: HOT RAM (SESSION-STATE.md)
**From: bulletproof-memory**
Active working memory that survives compaction. Write-Ahead Log protocol.
```markdown
# SESSION-STATE.md — Active Working Memory
## Current Task
[What we're working on RIGHT NOW]
## Key Context
- User preference: ...
- Decision made: ...
- Blocker: ...
## Pending Actions
- [ ] ...
```
**Rule:** Write BEFORE responding. Triggered by user input, not agent memory.
### Layer 2: WARM STORE (LanceDB Vectors)
**From: lancedb-memory**
Semantic search across all memories. Auto-recall injects relevant context.
```bash
# Auto-recall (happens automatically)
memory_recall query="project status" limit=5
# Manual store
memory_store text="User prefers dark mode" category="preference" importance=0.9
```
### Layer 3: COLD STORE (Git-Notes Knowledge Graph)
**From: git-notes-memory**
Structured decisions, learnings, and context. Branch-aware.
```bash
# Store a decision (SILENT - never announce)
python3 memory.py -p $DIR remember '{"type":"decision","content":"Use React for frontend"}' -t tech -i h
# Retrieve context
python3 memory.py -p $DIR get "frontend"
```
### Layer 4: CURATED ARCHIVE (MEMORY.md + daily/)
**From: OpenClaw native**
Human-readable long-term memory. Daily logs + distilled wisdom.
```
workspace/
├── MEMORY.md # Curated long-term (the good stuff)
└── memory/
├── 2026-01-30.md # Daily log
├── 2026-01-29.md
└── topics/ # Topic-specific files
```
### Layer 5: CLOUD BACKUP (SuperMemory) — Optional
**From: supermemory**
Cross-device sync. Chat with your knowledge base.
```bash
export SUPERMEMORY_API_KEY="your-key"
supermemory add "Important context"
supermemory search "what did we decide about..."
```
### Layer 6: AUTO-EXTRACTION (Mem0) — Recommended
**NEW: Automatic fact extraction**
Mem0 automatically extracts facts from conversations. 80% token reduction.
```bash
npm install mem0ai
export MEM0_API_KEY="your-key"
```
```javascript
const { MemoryClient } = require('mem0ai');
const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY });
// Conversations auto-extract facts
await client.add(messages, { user_id: "user123" });
// Retrieve relevant memories
const memories = await client.search(query, { user_id: "user123" });
```
Benefits:
- Auto-extracts preferences, decisions, facts
- Deduplicates and updates existing memories
- 80% reduction in tokens vs raw history
- Works across sessions automatically
## Quick Setup
### 1. Create SESSION-STATE.md (Hot RAM)
```bash
cat > SESSION-STATE.md << 'EOF'
# SESSION-STATE.md — Active Working Memory
This file is the agent's "RAM" — survives compaction, restarts, distractions.
## Current Task
[None]
## Key Context
[None yet]
## Pending Actions
- [ ] None
## Recent Decisions
[None yet]
---
*Last updated: [timestamp]*
EOF
```
### 2. Enable LanceDB (Warm Store)
In `~/.openclaw/openclaw.json`:
```json
{
"memorySearch": {
"enabled": true,
"provider": "openai",
"sources": ["memory"],
"minScore": 0.3,
"maxResults": 10
},
"plugins": {
"entries": {
"memory-lancedb": {
"enabled": true,
"config": {
"autoCapture": false,
"autoRecall": true,
"captureCategories": ["preference", "decision", "fact"],
"minImportance": 0.7
}
}
}
}
}
```
### 3. Initialize Git-Notes (Cold Store)
```bash
cd ~/clawd
git init # if not already
python3 skills/git-notes-memory/memory.py -p . sync --start
```
### 4. Verify MEMORY.md Structure
```bash
# Ensure you have:
# - MEMORY.md in workspace root
# - memory/ folder for daily logs
mkdir -p memory
```
### 5. (Optional) Setup SuperMemory
```bash
export SUPERMEMORY_API_KEY="your-key"
# Add to ~/.zshrc for persistence
```
## Agent Instructions
### On Session Start
1. Read SESSION-STATE.md — this is your hot context
2. Run `memory_search` for relevant prior context
3. Check memory/YYYY-MM-DD.md for recent activity
### During Conversation
1. **User gives concrete detail?** → Write to SESSION-STATE.md BEFORE responding
2. **Important decision made?** → Store in Git-Notes (SILENTLY)
3. **Preference expressed?** → `memory_store` with importance=0.9
### On Session End
1. Update SESSION-STATE.md with final state
2. Move significant items to MEMORY.md if worth keeping long-term
3. Create/update daily log in memory/YYYY-MM-DD.md
### Memory Hygiene (Weekly)
1. Review SESSION-STATE.md — archive completed tasks
2. Check LanceDB for junk: `memory_recall query="*" limit=50`
3. Clear irrelevant vectors: `memory_forget id=<id>`
4. Consolidate daily logs into MEMORY.md
## The WAL Protocol (Critical)
**Write-Ahead Log:** Write state BEFORE responding, not after.
| Trigger | Action |
|---------|--------|
| User states preference | Write to SESSION-STATE.md → then respond |
| User makes decision | Write to SESSION-STATE.md → then respond |
| User gives deadline | Write to SESSION-STATE.md → then respond |
| User corrects you | Write to SESSION-STATE.md → then respond |
**Why?** If you respond first and crash/compact before saving, context is lost. WAL ensures durability.
## Example Workflow
```
User: "Let's use Tailwind for this project, not vanilla CSS"
Agent (internal):
1. Write to SESSION-STATE.md: "Decision: Use Tailwind, not vanilla CSS"
2. Store in Git-Notes: decision about CSS framework
3. memory_store: "User prefers Tailwind over vanilla CSS" importance=0.9
4. THEN respond: "Got it — Tailwind it is..."
```
## Maintenance Commands
```bash
# Audit vector memory
memory_recall query="*" limit=50
# Clear all vectors (nuclear option)
rm -rf ~/.openclaw/memory/lancedb/
openclaw gateway restart
# Export Git-Notes
python3 memory.py -p . export --format json > memories.json
# Check memory health
du -sh ~/.openclaw/memory/
wc -l MEMORY.md
ls -la memory/
```
## Why Memory Fails
Understanding the root causes helps you fix them:
| Failure Mode | Cause | Fix |
|--------------|-------|-----|
| Forgets everything | `memory_search` disabled | Enable + add OpenAI key |
| Files not loaded | Agent skips reading memory | Add to AGENTS.md rules |
| Facts not captured | No auto-extraction | Use Mem0 or manual logging |
| Sub-agents isolated | Don't inherit context | Pass context in task prompt |
| Repeats mistakes | Lessons not logged | Write to memory/lessons.md |
## Solutions (Ranked by Effort)
### 1. Quick Win: Enable memory_search
If you have an OpenAI key, enable semantic search:
```bash
openclaw configure --section web
```
This enables vector search over MEMORY.md + memory/*.md files.
### 2. Recommended: Mem0 Integration
Auto-extract facts from conversations. 80% token reduction.
```bash
npm install mem0ai
```
```javascript
const { MemoryClient } = require('mem0ai');
const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY });
// Auto-extract and store
await client.add([
{ role: "user", content: "I prefer Tailwind over vanilla CSS" }
], { user_id: "ty" });
// Retrieve relevant memories
const memories = await client.search("CSS preferences", { user_id: "ty" });
```
### 3. Better File Structure (No Dependencies)
```
memory/
├── projects/
│ ├── strykr.md
│ └── taska.md
├── people/
│ └── contacts.md
├── decisions/
│ └── 2026-01.md
├── lessons/
│ └── mistakes.md
└── preferences.md
```
Keep MEMORY.md as a summary (<5KB), link to detailed files.
## Immediate Fixes Checklist
| Problem | Fix |
|---------|-----|
| Forgets preferences | Add `## Preferences` section to MEMORY.md |
| Repeats mistakes | Log every mistake to `memory/lessons.md` |
| Sub-agents lack context | Include key context in spawn task prompt |
| Forgets recent work | Strict daily file discipline |
| Memory search not working | Check `OPENAI_API_KEY` is set |
## Troubleshooting
**Agent keeps forgetting mid-conversation:**
→ SESSION-STATE.md not being updated. Check WAL protocol.
**Irrelevant memories injected:**
→ Disable autoCapture, increase minImportance threshold.
**Memory too large, slow recall:**
→ Run hygiene: clear old vectors, archive daily logs.
**Git-Notes not persisting:**
→ Run `git notes push` to sync with remote.
**memory_search returns nothing:**
→ Check OpenAI API key: `echo $OPENAI_API_KEY`
→ Verify memorySearch enabled in openclaw.json
---
## Links
- bulletproof-memory: https://clawdhub.com/skills/bulletproof-memory
- lancedb-memory: https://clawdhub.com/skills/lancedb-memory
- git-notes-memory: https://clawdhub.com/skills/git-notes-memory
- memory-hygiene: https://clawdhub.com/skills/memory-hygiene
- supermemory: https://clawdhub.com/skills/supermemory
---
*Built by [@NextXFrontier](https://x.com/NextXFrontier) — Part of the Next Frontier AI toolkit*
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