Overview

Slash your AI token costs and boost response speed with Caveman, a revolutionary Claude Code skill. This ingenious tool makes your AI agent communicate with the conciseness of a cave dweller, dramatically reducing output tokens by up to 75% while preserving 100% technical accuracy. Think of it as a powerful brain with a minimalist mouth – all the intelligence, none of the fluff.

Key Features

• Massive Token Reduction: Achieve an average of 65% output token savings, with some prompts seeing reductions as high as 87%. This translates directly to lower API costs and faster response times.
• Uncompromised Accuracy: Caveman meticulously preserves the technical precision of your AI's responses. Code, commands, and critical details remain intact.
• Multi-Level Compression: Choose your desired level of terseness: lite (removes filler), full (default caveman), ultra (telegraphic), or wenyan (classical Chinese for extreme brevity).
• Language Preservation: Caveman compresses the style, not the language. Your agent will grunt in Portuguese, Spanish, French, or any other language you use.
• Seamless Integration: Installs in seconds with a single command for a wide range of agents including Claude Code, Codex, Gemini, Cursor, Copilot, and dozens more.
• Versatile Skills: Beyond basic output compression, Caveman offers specialized commands like /caveman-commit for concise commit messages, /caveman-review for one-line PR feedback, /caveman-stats for token usage insights, and /caveman-compress to shrink memory files for persistent input token savings.
• Ecosystem Ready: Integrates with the broader Caveman ecosystem, including caveman-code (full terminal agents), cavemem (cross-agent memory), cavekit (build loop), and cavegemma (fine-tuned models).

Typical Use Cases

• Cost Optimization: Dramatically reduce API expenditures for LLM interactions, especially in high-volume applications.
• Performance Enhancement: Experience significantly faster response times from your AI agents, improving user experience and workflow efficiency.
• Enhanced Readability: Quickly grasp complex technical explanations and solutions due to the elimination of verbose phrasing.
• Developer Productivity: Generate concise commit messages, efficient code reviews, and streamlined technical documentation.
• Context Management: Utilize caveman-compress to permanently reduce the size of your agent's memory files, allowing for longer, more effective sessions.
• Agent Training & Fine-tuning: Leverage the principle of brevity to potentially improve model accuracy, as indicated by recent research suggesting conciseness can sometimes enhance performance.