session-management

To manage AI session context, monitor token usage thresholds and use pruning strategies to reduce context size. This skill provides automated alerts at 70%, 85%, and 95% capacity to trigger context consolidation and maintain performance.

You can retrieve past AI session history using built-in session tools. Commands like list_sessions, read_session, search_session, and summarize_session allow you to extract, review, and condense past interactions for efficient context transfer.

You should start a new AI session when token thresholds approach capacity limits. The skill guides users on exactly when to initiate new sessions and how to transfer essential context strategically to maintain performance and control costs.

The best way to transfer context between AI sessions is through strategic data extraction and summarization. This approach prunes unnecessary data, consolidating only essential information to maintain workflow performance without exceeding token limits.

Context pruning improves AI workflow performance by reducing context window size. By strategically extracting and summarizing essential data, it prevents token overload and helps maintain efficient session management and lower operational costs.