elite-longterm-memory

Elite Longterm Memory 🧠

The ultimate memory system for AI agents. Never lose context again.

Works With

Built for: Clawdbot • Moltbot • Claude Code • Any AI Agent

Combines 7 proven memory approaches into one bulletproof architecture:

• ✅ Bulletproof WAL Protocol — Write-ahead logging survives compaction
• ✅ LanceDB Vector Search — Semantic recall of relevant memories
• ✅ Git-Notes Knowledge Graph — Structured decisions, branch-aware
• ✅ File-Based Archives — Human-readable MEMORY.md + daily logs
• ✅ Cloud Backup — Optional SuperMemory sync
• ✅ Memory Hygiene — Keep vectors lean, prevent token waste
• ✅ Mem0 Auto-Extraction — Automatic fact extraction, 80% token reduction

Quick Start

# Initialize in your workspace
npx elite-longterm-memory init

# Check status
npx elite-longterm-memory status

# Create today's log
npx elite-longterm-memory today

Architecture

┌─────────────────────────────────────────────────────┐
│              ELITE LONGTERM MEMORY                  │
├─────────────────────────────────────────────────────┤
│  HOT RAM          WARM STORE        COLD STORE     │
│  SESSION-STATE.md → LanceDB      → Git-Notes       │
│  (survives         (semantic       (permanent      │
│   compaction)       search)         decisions)     │
│         │              │                │          │
│         └──────────────┼────────────────┘          │
│                        ▼                           │
│                   MEMORY.md                        │
│               (curated archive)                    │
└─────────────────────────────────────────────────────┘

The 5 Memory Layers

Layer	File/System	Purpose	Persistence
1. Hot RAM	SESSION-STATE.md	Active task context	Survives compaction
2. Warm Store	LanceDB	Semantic search	Auto-recall
3. Cold Store	Git-Notes	Structured decisions	Permanent
4. Archive	MEMORY.md + daily/	Human-readable	Curated
5. Cloud	SuperMemory	Cross-device sync	Optional

The WAL Protocol

Critical insight: Write state BEFORE responding, not after.

User: "Let's use Tailwind for this project"

Agent (internal):
1. Write to SESSION-STATE.md → "Decision: Use Tailwind"
2. THEN respond → "Got it — Tailwind it is..."

If you respond first and crash before saving, context is lost. WAL ensures durability.

Why Memory Fails (And How to Fix It)

Problem	Cause	Fix
Forgets everything	memory_search disabled	Enable + add OpenAI key
Repeats mistakes	Lessons not logged	Write to memory/lessons.md
Sub-agents isolated	No context inheritance	Pass context in task prompt
Facts not captured	No auto-extraction	Use Mem0 (see below)

Mem0 Integration (Recommended)

Auto-extract facts from conversations. 80% token reduction.

npm install mem0ai
export MEM0_API_KEY="your-key"

const { MemoryClient } = require('mem0ai');
const client = new MemoryClient({ apiKey: process.env.MEM0_API_KEY });

// Auto-extracts facts from messages
await client.add(messages, { user_id: "user123" });

// Retrieve relevant memories  
const memories = await client.search(query, { user_id: "user123" });

For Clawdbot/Moltbot Users

Add to ~/.clawdbot/clawdbot.json:

{
  "memorySearch": {
    "enabled": true,
    "provider": "openai",
    "sources": ["memory"]
  }
}

Files Created

workspace/
├── SESSION-STATE.md    # Hot RAM (active context)
├── MEMORY.md           # Curated long-term memory
└── memory/
    ├── 2026-01-30.md   # Daily logs
    └── ...

Commands

elite-memory init      # Initialize memory system
elite-memory status    # Check health
elite-memory today     # Create today's log
elite-memory help      # Show help

Links

• Full Documentation (SKILL.md)
• ClawdHub
• GitHub

Built by @NextXFrontier