Claude Automatic Context Compaction for Long-Running AI Agents
Claude Automatic Context Compaction: Keep Long-Running AI Agents Working Beyond Context Limits Long-running AI agents can perform impressive multi-step tasks, but they face a practical limitation: their conversation history keeps growing. Every instruction, model response, tool request and tool result occupies space in the context window. In a tool-heavy workflow, this information can accumulate quickly. Eventually, the agent may become slower, consume significantly more tokens or approach its context limit. Anthropic’s Claude Cookbook presents a solution called automatic context compaction . Instead of carrying the complete conversation history through every step, Claude can summarize the important information, remove unnecessary historical details and continue the task using a smaller, focused context. What Is Automatic Context Compaction? Automatic context compaction is a context-management technique for long-running Claude agent workflows. It monitors the number of tokens bei...