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Memory Lancedb Pro Skill

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Description

Agent skills for AI coding assistants (Antigravity)

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

🧠 memory-lancedb-pro Skill

**An AI Coding Assistant Skill for maintaining and upgrading the [memory-lancedb-pro](https://github.com/win4r/memory-lancedb-pro) plugin**

Give your AI assistant deep understanding of the plugin's architecture, retrieval pipeline, and configuration system — enabling efficient maintenance and feature development of this OpenClaw long-term memory plugin.

[![OpenClaw Plugin](https://img.shields.io/badge/OpenClaw-Plugin-blue)](https://github.com/openclaw/openclaw) [![LanceDB](https://img.shields.io/badge/LanceDB-Vectorstore-orange)](https://lancedb.com) [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)

[简体中文](README_CN.md) | **English**


What Is This?

This is an **Agent Skill** — a structured knowledge package designed for AI coding assistants to maintain and upgrade the [memory-lancedb-pro](https://github.com/win4r/memory-lancedb-pro) OpenClaw plugin.

When an AI coding assistant loads this skill, it gains comprehensive understanding of the plugin, including:

  • 🏗️ Plugin Architecture — Responsibilities, exports, and relationships of all 12 source files
  • 🔍 Retrieval Pipeline — RRF fusion, cross-encoder reranking, exact math formulas for 6 scoring stages
  • 💾 Storage Layer — LanceDB schema, FTS indexing, CRUD operation implementations
  • 🔐 Scope System — 5 scope types, access control logic
  • 🛠️ Development Workflows — Step-by-step guides for 7 common development scenarios
  • 🐛 Troubleshooting — Installation, configuration, retrieval quality tuning, development pitfalls

File Structure

memory-lancedb-pro-skill/
├── SKILL.md                                  # Main skill file (architecture, workflows, design decisions)
├── references/
│   ├── retrieval_pipeline.md                 # Retrieval pipeline deep dive
│   ├── storage_and_schema.md                 # Storage layer & data model
│   ├── embedding_system.md                   # Embed