To learn about AI Agent architecture design using the analysis_claude_code project, you can follow the steps below:
- Start with a macro understanding: first read the project's README.md file to understand the overall system architecture and core findings
- Study the system architecture diagram: carefully analyze the system architecture panorama provided in the project to understand the collaboration between the user interaction layer, the Agent core scheduling layer, the tool execution and management layer, and the storage layer
- Read the technical analysis document: Study the 'Claude_Code_Agent_System_Complete_Technical_Analysis.md' document in detail, and master the working principle and implementation details of each component.
- Analyze the de-obfuscated code: Review the 102 de-obfuscated code modules in the chunks directory, focusing on the implementation of the Agent scheduling and message passing mechanisms.
- Run the analysis script: use the Node.js script provided with the project to try to format and analyze the code snippet
- Reference to the rebuild guide: using the open source rebuild guide and TypeScript framework template provided by the project, try to implement the core components of a similar system on your own
This systematic approach to learning can help you gain a deeper understanding of the design concepts and engineering practices of modern AI Agent systems.
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 " How to use the analysis_claude_code project to learn AI Agent architecture design?
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