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.mdsource 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
model pulled:nomic-embed-textollama 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
| Metric | Value |
|---|---|
| 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
- Main CLI toolfast-unified-memory.js
- This documentationSKILL.md
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