sage-session-management

To persist and restore conversation sessions in Rust, this Skill provides a typed Rust data model and storage abstractions that save session state, messages, and metadata to a backend, enabling resume from breakpoints. It supports creating an in-memory SessionManager to manage the lifecycle.

Session branching saves snapshots of conversations to explore different paths safely. You need session branching when switching between exploration routes or merging outcomes in multi-session environments, ensuring recoverable and auditable conversational workflows without losing prior context.

Yes, you can use custom storage backends for Sage conversation persistence. The Skill defines storage abstractions that decouple the persistence layer from the typed Rust data model, allowing you to integrate your preferred backend while maintaining auditable and recoverable conversations.

No, this Skill requires zero external dependencies to manage session lifecycles. It self-contains the typed Rust data model, storage abstractions, and lightweight cache needed for session creation, resume, branch snapshots, and recent-session tracking.

The primary limitation of in-memory session management is data loss upon process termination. To retain state, messages, and metadata across restarts, you must persist sessions to a configured storage backend, as the in-memory SessionManager only supports temporary session lifecycle operations.