Skills fast-unified-memory

Skill: Fast Unified Memory

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/broedkrummen/fast-unified-memory" ~/.claude/skills/clawdbot-skills-fast-unified-memory && rm -rf "$T"
manifest: skills/broedkrummen/fast-unified-memory/SKILL.md
source content

Skill: Fast Unified Memory

A high-performance unified memory system that integrates OpenClaw memory with semantic memory storage using Ollama's nomic-embed-text model for ultra-fast embeddings.

Overview

This skill provides a unified memory layer that combines:

  • OpenClaw Memory: Standard file-based memory storage
  • Semantic Memory: Vector-based memory using Ollama embeddings

Features

  • Ultra-fast: ~130ms for combined search (embedding ~40ms + search ~90ms)
  • 🔒 Private: All processing done locally via Ollama
  • 💰 Free: No API costs - uses local Ollama instance
  • 🧠 Semantic: Uses nomic-embed-text for intelligent similarity matching

Requirements

  • Ollama installed and running
  • nomic-embed-text
    model pulled:
    ollama pull nomic-embed-text

Installation

# Install Ollama first
curl -fsSL https://ollama.ai/install.sh | sh

# Pull the embedding model
ollama pull nomic-embed-text

# Start Ollama
ollama serve

Usage

Commands

# Search both memory systems
node fast-unified-memory.js search "your query"

# Add a memory
node fast-unified-memory.js add "User prefers concise responses"

# List all memories
node fast-unified-memory.js list

# Show system stats
node fast-unified-memory.js stats

Architecture

┌─────────────────────────────────────────────┐
│           FAST UNIFIED MEMORY                │
│                                             │
│  ┌─────────────┐    ┌─────────────┐        │
│  │   OpenClaw  │    │   Semantic  │        │
│  │   Memory    │    │   Memory    │        │
│  │ (files)     │    │  (vectors) │        │
│  └─────────────┘    └─────────────┘        │
│           ↓                  ↓              │
│    [Keyword Match]   [Cosine Similarity]   │
│                                             │
│        Unified Results (ranked)             │
└─────────────────────────────────────────────┘

Performance

MetricValue
Embedding generation~40ms
Vector search~50ms
File search~40ms
Total search~130ms

Configuration

The skill uses these defaults:

  • Ollama URL:
    http://localhost:11434
  • Embedding model:
    nomic-embed-text
  • Memory storage:
    ~/.mem0/fast-store.json
  • OpenClaw memory:
    ~/.openclaw/workspace/memory/

Files

  • fast-unified-memory.js
    - Main CLI tool
  • SKILL.md
    - This documentation

Troubleshooting

Ollama not running:

ollama serve

Model not found:

ollama pull nomic-embed-text

Port conflict: The skill assumes Ollama is on port 11434. Update the

OLLAMA_URL
constant if using a different port.

License

MIT