provider-storage

To persist AI agent conversation history across restarts, use a database-backed storage abstraction that reliably appends and loads conversation turns. This Skill uses SQLite or PostgreSQL to save conversation data so it remains retrievable after agent restarts.

Managing message queues for asynchronous AI agents requires a unified persistent storage interface that supports asynchronous enqueue and dequeue operations. This Skill provides that abstraction over a database backend to ensure message integrity during agent processing.

Yes, this persistent storage abstraction supports both PostgreSQL and SQLite as its database backend. You can choose SQLite for local development and scale up to PostgreSQL for robust, production-level agent data management.

To track AI agent sessions and store key-value documents, use a unified storage interface that manages both session tracking and document key-value operations. This Skill handles these tasks simultaneously alongside message queues and conversation history.

Yes, you can use a single interface for all your agent's data management needs. This Skill provides a unified storage abstraction that handles message queues, conversations, sessions, and documents asynchronously via one database backend.