add-memory-strategy

What problem does it solve?

This skill enables you to design and integrate custom memory strategies for KAgentic agents by implementing the AgentMemory interface, enabling persistent, cached, or specialized conversation state management.

Core Features & Use Cases

• Implement any memory strategy by implementing the AgentMemory interface to manage stores, retrievals, and full history in a thread-safe manner.
• Support special keys such as "user_input" and "agent_response" to automatically build and update conversation history, plus a "history" view for formatted outputs.
• Leverage a range of patterns (in-memory, file persistence, Redis, databases) to suit persistence, scalability, and performance needs.
• Enable advanced capabilities like TTL-based expiration, metrics, and search over conversation history for analytics and debugging.
• Typical use cases include persistent conversation history across restarts, multi-instance agent coordination, and custom memory behaviors for specialized workflows.

Quick Start

Create a simple custom memory by implementing AgentMemory and wiring it into an AgentFramework to track user inputs and agent responses.