The intelligent context management system developed by Claude Code innovatively solves the Token consumption problem for large language models. The system realizes efficient management of contexts through dynamic policies.
Core technologies include:
- Automatic compression algorithm: triggered when Token usage reaches 92%
- CLAUDE.md file: Enabling persistent storage of long-term memory
- Dynamic window resizing: optimize context length based on task type
- Intelligent summary extraction: retaining key information and removing redundancy
Performance of the system's effects:
- Reduce average Token consumption by 40-60%
- Stabilizes memory usage for long conversations
- Ensure retention of critical information in excess of 95%
- Significantly increased the completion rate of tasks over a long period of time
This technique provides an important reference for optimizing the resource utilization of LLM.
This answer comes from the articleanalysis_claude_code: a library for reverse engineering Claude Code.The
May not be reproduced without permission:AI productivity tools " Smart Context Management Technology Optimizes Token Usage Efficiency for Claude Code
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