Agent Memory

Overview

AI agents forget everything between sessions. This skill builds persistent memory systems — from simple file-based approaches to full vector-search architectures — so agents retain context, learn from past interactions, and make better decisions over time.

When to Use

• User wants the agent to remember decisions, preferences, or project context
• Building a coding assistant that needs to recall past conversations
• Creating a knowledge base the agent can query semantically
• Agent needs to learn from mistakes and not repeat them
• Implementing memory consolidation (daily notes → long-term memory)

Instructions

Strategy 1: File-Based Memory (Zero Dependencies)

The simplest approach — write memories to structured markdown files. No database, no embeddings, no API keys. Works with any agent that can read/write files.