Vector Memory Hack

Fast semantic search for AI agent memory files using TF-IDF and SQLite. Enables instant context retrieval from MEMORY.md or any markdown documentation. Use when the agent needs to (1) Find relevant context before starting a task, (2) Search through large memory files efficiently, (3) Retrieve specific rules or decisions without reading entire files, (4) Enable semantic similarity search instead of keyword matching. Lightweight alternative to heavy embedding models - zero external dependencies, <

Model-Selector

A powerful model routing skill that analyzes query intent and cost-efficiency to select the optimal LLM (Elite/Balanced/Basic) before execution.

PostgreSQL

Write efficient PostgreSQL queries and design schemas with proper indexing and patterns.

Brain CMS

Neuroscience-based multi-layer memory system for OpenClaw agents that improves context efficiency using semantic schemas, vector stores, and sleep cycle cons...