Compaction

Managing conversation context size with compaction

As conversations grow, they consume more of the model’s context window. Compaction reduces context size while preserving important information, keeping your conversations responsive and cost-effective.

Approaches

Approach	Speed	Context Preservation	Cost	Reversible
Start Here	Instant	Intelligent	Free	Yes
/compact	Slower (uses AI)	Intelligent	Uses API tokens	No
/clear	Instant	None	Free	No
/truncate	Instant	Temporal	Free	No
Auto-Compaction	Automatic	Intelligent	Uses API tokens	No

When to compact

• Proactively: Before hitting context limits, especially on long-running tasks
• After major milestones: When you’ve completed a phase and want to preserve learnings without full history
• When responses degrade: Large contexts can reduce response quality

Next steps

• Manual Compaction — Commands for manually managing context
• Automatic Compaction — Let mux compact for you based on usage or idle time