session

Claude Code session lifecycles are managed by orchestrating learning extraction and context compression tasks, ensuring reusable patterns are saved and context limits are safely handled across active sessions and transitions.

Context compression in AI assistant sessions reduces context size during checkpoint moments or transitions. It is needed when conversations become fragmented or approach context limits, ensuring continuity without losing critical patterns.

Reusable patterns are extracted from active Claude Code sessions by routing learning tasks to dedicated sub-skills. This process validates inputs and coordinates the extraction during checkpoint moments or session transitions.

Session management workflows support loading and resuming previous contexts to maintain continuity across conversations. This allows users to recover previous states and continue work without losing prior learning or progress.

Tasks are routed to specific sub-skills through deterministic routing, directing learning tasks and context compression tasks to dedicated modules while validating inputs and ensuring safe handling of context limits.

Session management tools handle context limits in Claude Code safely by applying context compression during active sessions and transitions, validating all inputs before routing to ensure no data is lost.