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Official Verified productivity Safety 5/5

openclaw-memory-enhancer

Edge-optimized RAG memory system for OpenClaw with semantic search. Automatically loads memory files, provides intelligent recall, and enhances conversations with relevant context. Perfect for Jetson and edge devices (<10MB memory).

Why use this skill?

Give OpenClaw long-term memory with this edge-optimized RAG system. Enjoy private, local context-aware recall for Jetson and Raspberry Pi devices.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/henryfcb/openclaw-memory-enhancer
Or

What This Skill Does

The OpenClaw Memory Enhancer is a lightweight, privacy-focused RAG (Retrieval-Augmented Generation) system designed specifically for the OpenClaw agent. It grants your AI the ability to retain information across sessions, turning fleeting interactions into a structured, persistent knowledge base. At its core, the skill parses files within a local memory/ directory to create a semantic representation of your past data. When you converse with OpenClaw, the system intelligently recalls relevant snippets, providing context-aware responses without requiring massive computational resources. By utilizing both keyword and vector-based matching, it bridges the gap between raw data and meaningful intelligence, making it an essential component for any long-term interaction.

Installation

You can integrate this skill into your environment using the official ClawHub repository manager or via direct Git cloning. The recommended approach is to run clawhub install openclaw-memory-enhancer from your terminal, which handles path configurations automatically. If you prefer manual installation, clone the repository into ~/.openclaw/skills/openclaw-memory-enhancer. For edge devices like the Raspberry Pi or Jetson, no extra dependencies are required as it uses pure Python. For server-grade performance, install the optional requirements via pip install sentence-transformers numpy to enable higher-accuracy semantic embeddings.

Use Cases

  • Project Management: Track ongoing development tasks, user preferences, and project requirements across multiple coding sessions.
  • Personal Assistance: Remember user routines, recurring meeting agendas, or specific technical configurations for edge hardware.
  • Knowledge Management: Automatically ingest existing text files, logs, or markdown documentation to query them via natural language.
  • Resource-Constrained Environments: Deploy high-quality recall systems on IoT devices where memory overhead must remain strictly under 10MB.

Example Prompts

  1. "OpenClaw, search your memory for the API key setup steps I saved last week."
  2. "Add a memory that I prefer using dark mode for the CLI tools."
  3. "Summarize the project constraints stored in our memory database."

Tips & Limitations

To maximize the utility of the Memory Enhancer, maintain a clean memory/ directory with clear text or markdown files. While the 'Edge' version is highly efficient, it prioritizes performance over deep linguistic nuance; if you require high-level logical reasoning, consider switching to the 'Standard' version on your desktop. Be aware that the local nature of the storage means you are responsible for backing up your memory/ directory. The skill does not currently support real-time streaming updates from external cloud databases, focusing exclusively on local file-system sovereignty for total data privacy.

Metadata

Author@henryfcb
Stars2387
Views1
Updated2026-03-09
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-henryfcb-openclaw-memory-enhancer": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#rag#memory#edge-computing#vector-search#automation
Safety Score: 5/5

Flags: file-read, file-write