Tool profile
JuliusBrussee/caveman
github.com
A skill and proxy that cuts token usage for AI coding agents by making them answer in terse caveman style.
What it does
JuliusBrussee/caveman
Caveman is a skill and proxy for coding agents like Claude Code, Codex and Gemini CLI that reduces token consumption by having the agent answer in short, caveman-style language while keeping code exact. It also shrinks logs, JSON, CSV and test output before the model reads them, and can pick the model and effort level per request. It is installed via an npx command, runs locally with your own keys and logins, and is written in Go.
PricingOpen source
RatingN/A
Bookmarks0
Tags
Categories
A concise summary has not been added yet.
FAQ
Frequently asked questions
- What is JuliusBrussee/caveman?
- Caveman is a skill and proxy for coding agents like Claude Code, Codex and Gemini CLI that reduces token consumption by having the agent answer in short, caveman-style language while keeping code exact. It also shrinks logs, JSON, CSV and test output before the model reads them, and can pick the model and effort level per request. It is installed via an npx command, runs locally with your own keys and logins, and is written in Go.
- How much does JuliusBrussee/caveman cost?
- JuliusBrussee/caveman uses a Open source pricing model. Check the official website for current plans.
- What is JuliusBrussee/caveman used for?
- JuliusBrussee/caveman is listed on TolsAI under: Open Source.
- Where can I use JuliusBrussee/caveman?
- JuliusBrussee/caveman is available on its official website, github.com.
Explore
More in Open Source
An open-source agentic harness for a self-improving AI agent that plans and executes tasks you describe.
A vectorless, reasoning-based RAG engine that indexes documents as trees and retrieves with LLM reasoning.
A PyTorch-like Python library to build and auto-optimize LLM workflows such as chatbots, RAG and agents.
A modular web UI for generating images, video and audio with AI models like Stable Diffusion, Flux and Wan.
A step-by-step guide to designing AI systems built on LLMs, RAG, and AI agents.
Open-source AI pipeline engine for building, debugging and deploying LLM workflows and agent orchestration from your IDE.
Discussion
Discussion
Log in to join the discussion
No comments yet. Start the discussion.