⚠️Install with caution. This skill has very few installs. Always review the source and verify it on clawhub.ai before installing. Community-built skills run with agent permissions — only install ones you trust.

🧠 Agent Memory

Memory LanceDB Setupv1.0.0

Name: Memory LanceDB Setup
Author: ssyvonne

memory-lancedb-setup

ssyvonne

Configure OpenClaw's memory-lancedb plugin to enable local semantic vector memory using LanceDB and an OpenAI-compatible embedding provider.

latest

Download Package View on ClawHub

Installs (all time)

Installs (current)

Downloads

830

Stars

CreatedMar 29, 2026

UpdatedMay 11, 2026

Install & Quick Start

Install via ClawdBot CLI:

clawdbot install ssyvonne/memory-lancedb-setup

Skill Package3 files

📋SKILL.mdmarkdown

Failed to load file.

Quality Score

B55/100

Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.

Market Validation4/35

· 409 downloads (low demand)
· No tracked installs (may still have real users via manual install)

Documentation18/25

· SKILL.md present
· Moderate documentation (≥1500 chars)
· Contains usage examples or trigger description
· Detailed summary

Package Completeness8/15

· skillAssets present (2 files)

Security Analysis

💙 Low Risk

UNDOCUMENTED_EXTERNALlow

Calls external URL not in known-safe list

https://aistudio.google.com

KNOWN_EXTERNALlow

Uses known external API (expected, informational)

googleapis.com

Audited Apr 17, 2026 · audit v1.0

💡

Usage Guide

Generated May 21, 2026

OpenClaw developers setting up vector memory for the first timeAI agent users experiencing module errors with LanceDBDevelopers migrating from flat-file memory to vector-based recallSystem administrators configuring embedding providers for OpenClawbeginner

💡 Application Scenarios

First-time vector memory setup for a personal AI assistantPersonal Productivity

A user configuring OpenClaw for the first time needs to enable semantic vector memory to store and recall conversation history. This skill installs LanceDB, configures a Gemini embedding API, and patches the native module for Apple Silicon. The assistant can then recall past interactions without loading the full context.

Migrating from flat-file MEMORY.md to vector-based recallSoftware Development

A developer with a large MEMORY.md file wants to improve recall performance by migrating key facts into a vector store. This skill provides steps to chunk MEMORY.md by topic, store each chunk via memory_store, and shrink MEMORY.md to a short index. The result is faster, relevance-ranked recall.

Fixing module not found errors for LanceDB in OpenClawIT Support

When OpenClaw fails with 'module not found: @lancedb/lancedb', this skill diagnoses the issue as missing native bindings. It provides platform-specific npm install commands (darwin-arm64, darwin-x64, linux-x64-gnu) and a Python patch for Apple Silicon to ensure the correct binary is loaded.

Configuring an OpenAI-compatible embedding provider for vector memoryEnterprise Software

An enterprise user wants to use a local embedding model compatible with OpenAI's API format. This skill shows how to configure the base URL, model name, API key, and dimensions for the memory-lancedb plugin. It enables flexible embedding provider choices beyond default options.

Scaling memory recall for a customer support AI agentCustomer Service

A customer support bot using OpenClaw needs to recall thousands of past interactions efficiently. This skill sets up LanceDB with high-dimensional embeddings (768) and optimizes recall via similarity search. The bot can quickly fetch relevant past tickets without full context reload.

💼 Business Models

Freemium AI Plugin MarketplaceSubscription ($10-50/month) or one-time upgrade fee ($100-500)

Offer the memory-lancedb setup skill as a free plugin in a marketplace, with premium add-ons like advanced embedding tuning or multi-node LanceDB clusters. Revenue comes from paid upgrades or subscription for enterprise features.

Managed AI Infrastructure ServiceMonthly service fee ($200-2000 depending on memory size/recall volume)

Provide a fully managed service where we install and configure vector memory for OpenClaw deployments. Includes monitoring, backup, and scaling. Revenue from monthly maintenance contracts.

Developer Education & ConsultingCourse ($50-200) + consulting ($150-300/hour)

Create premium video tutorials and consulting packages around OpenClaw vector memory optimization, migration from flat files, and embedding provider tuning. Revenue from course sales and hourly consulting.

💬 Integration Tip

Ensure OpenClaw is installed at the default path before starting. For Apple Silicon, run the patch script immediately after installing dependencies to avoid native binding errors.