Compress AI-generated text responses to reduce token usage.
npx skills add https://github.com/borkweb/skills --skill caveman-borkweb
Please help me install this Agent Skill. Skill: caveman Source: https://github.com/borkweb/skills/tree/main/skills/core/caveman Command: npx skills add https://github.com/borkweb/skills --skill caveman-borkweb
This Skill reduces the number of tokens used in responses, allowing for more concise and efficient communication while maintaining technical accuracy.
Enter "caveman mode" to enable ultra-compressed communication.
High-intent search queries and answers about installing and using this skill.
To reduce the token count in AI generated text responses, you can apply text compression techniques that prioritize brevity over verbosity while preserving technical accuracy. This approach cuts token usage by up to 75% for efficient communication.
Text compression for technical support and documentation is the process of condensing AI responses to essential points. It maintains technical accuracy while eliminating verbosity, making it ideal for briefings and support scenarios where brevity is valued.
Yes, you can adjust the intensity level of text reduction. The skill offers multiple compression variants including lite, full, ultra, and wenyan levels, allowing you to choose the exact balance of brevity and detail needed for your specific task.
Yes, you need a model capable of understanding and generating compressed text to use this text reduction technique effectively. The model must accurately interpret compression instructions and output essential points without losing technical accuracy.
You should not use ultra-compression for AI communication when verbosity, conversational tone, or detailed explanations are required. Since it reduces tokens by 75% to deliver essential points, it may remove context needed for general or casual interactions.
valorisaImplement cache management and context optimization rules for Claude Code sessions.
jchildreeCompress technical content into ultra-brief messages with six intensity levels.
Svenja-devEstimate token consumption and recommend chunked execution plans for large tasks.
kbtimeSummarize long texts into concise summaries with key points and multi-language support.
