HubLens › Trending › drona23/claude-token-efficient
drona23

claude-token-efficient

AIClaudePrompt EngineeringLLMToken Optimization
View on GitHub
101
+340

// summary

This project guides the Claude model to reduce redundant polite phrases and unnecessary output by adding a CLAUDE.md file to the project root, thereby significantly lowering Token consumption. This solution is suitable for automated pipelines, code reviews, and high-frequency interaction scenarios, aiming to improve model response efficiency through streamlined instructions. Users can choose different preset configuration files according to specific needs to achieve cost optimization while maintaining output quality.

// use cases

01
Significantly reduce the number of output Tokens by removing redundant opening and closing remarks.
02
Provide structured and concise response formats for automated pipelines and Agent loop tasks.
03
Prevent the model from over-engineering code or providing unnecessary repetitive explanations through targeted project-level rules.