strategic-compact

Preventing arbitrary auto-compaction requires suggesting manual context compaction at logical intervals. This approach tracks tool calls and prompts you to compact at natural breakpoints, preserving task flow and retaining relevant information before context limits are hit.

Manual context compaction is the process of summarizing and clearing the AI context window at a chosen point. You should use it at natural task breakpoints, such as after research and before implementation, to ensure the most relevant information is retained.

Configuring context management thresholds involves setting environment variables for tool call limits and periodic intervals. You can adjust these settings and set up hook configurations in your user settings to control when manual compaction suggestions are triggered.

Yes, you can trigger context compaction suggestions at specific task phases. The system monitors your tool usage and prompts for manual compaction after a configurable threshold, allowing you to clear context after research phases and before writing code.

Arbitrary auto-compaction disrupts complex AI workflows by clearing the context window mid-task, which loses valuable information. Suggesting manual compaction at logical intervals prevents this by triggering prompts at natural breakpoints rather than arbitrary limits.