Minimize token usage in AI responses with adjustable intensity levels.
npx skills add https://github.com/g-lok/gs-dotfiles --skill caveman-g-lok
Please help me install this Agent Skill. Skill: caveman Source: https://github.com/g-lok/gs-dotfiles/tree/main/install.d/dotfiles/ai_skills/.agents/skills/caveman Command: npx skills add https://github.com/g-lok/gs-dotfiles --skill caveman-g-lok
Minimize token usage in AI responses while preserving essential technical accuracy.
Activate caveman mode and respond in terse, technically accurate terms.
High-intent search queries and answers about installing and using this skill.
You can minimize token usage while keeping technical accuracy by applying article omission rules and structured communication patterns. This enforces concise, predictable outputs for technical chats and code reviews without losing critical details.
The best way to get concise AI responses for rapid code reviews is to enforce a fixed pattern like "[thing] [action] [reason]. [next step]." This structured approach guarantees clarity and brevity while preserving essential technical context.
Yes, you can adjust the intensity of token efficiency modes using a simple switch mechanism. Variants include lite, full, ultra, and wenyan, allowing you to control response density and length based on your specific technical discussion needs.
Applying article omission rules does not affect the clarity of dense technical explanations when paired with a structured pattern. This combination actively reduces length while enforcing predictable, terse outputs that maintain precise technical meaning.
tianjianjiangDefine and enforce prompt engineering standards for AGENTS.md and caching workflows.
Soham407Enforce ultra-compressed technical responses using an action-reason-next-step pattern.
MicrockEnforce sequential task execution and terse responses for Claude Code.
ari-ayvazyanCompress responses by removing filler while preserving technical terms.
