Compress technical responses into terse, fragment-based communication.
npx skills add https://github.com/ntk148v/skills --skill caveman-ntk148v
Please help me install this Agent Skill. Skill: caveman Source: https://github.com/ntk148v/skills/tree/main/skills/caveman Command: npx skills add https://github.com/ntk148v/skills --skill caveman-ntk148v
It reduces token usage and verbosity while preserving technical correctness when you need fast, concise answers.
Ultra-compressed communication: Drops filler, pleasantries, and articles while keeping technical meaning intact.
Rules-based terse style: Enforces abbreviations, fragment-friendly phrasing, and causal arrow patterns (X -> Y) for clarity under tight length constraints.
Safety/clarity override: Temporarily suspends the caveman style for security warnings, irreversible confirmations, and multi-step sequences where ordering could be misunderstood.
Tell your AI to use caveman mode to answer your question with the same technical accuracy but far fewer tokens.
High-intent search queries and answers about installing and using this skill.
Token optimization in technical writing is achieved by dropping filler words, enforcing abbreviations, and allowing sentence fragments to compress responses while preserving core technical meaning.
Concise debugging guidance uses a terse prompting style that employs causal arrow patterns (X -> Y) and fragment-friendly phrasing to deliver troubleshooting steps with strict filler removal and low token count.
Token optimization works for commit messages and technical documentation by enforcing ultra-compressed communication that drops articles and pleasantries while retaining technical correctness for doc-like exchanges.
You should not use ultra-brief responses for security warnings, irreversible confirmations, or multi-step sequences where ordering could be misunderstood, as these require a temporary safety and clarity override.
Making AI responses use fewer tokens requires a rules-based terse style that prefers abbreviations and fragments, cutting verbose communication overhead while preserving the exact technical details requested.
A concise prompting style supports step-by-step technical guidance by allowing fragment-friendly phrasing, but temporarily suspends terseness for multi-step sequences where ordering could be misunderstood to ensure safety.
samhvw8Transform verbose prompts into concise, XML-structured versions for multiple AI models.
silva2kandGenerate standardized commit messages from git staged changes.
serguei9090Compress communication style into concise, accurate responses across technical conversations.
chekosEnforce Google's technical-writing guidelines for tutorials, API docs, and system documentation.
