JuliusBrussee/caveman-code
Frozen — terminal coding agent measured at 1.93× fewer tokens than Codex CLI. Still works; active development moved to JuliusBrussee/caveman (caveman wrap).
What it solves
Caveman Code is a terminal-based coding agent designed to drastically reduce LLM token usage and costs. It addresses the "waffle" (excessive filler text) produced by AI agents and the massive token overhead from tool outputs (like long git diffs or build logs) that are typically fed back into the model's context window.
How it works
The project employs a four-layer compression system to minimize token consumption:
- Caveman Mode: Forces the model to respond in terse, technical fragments without filler or hedging.
- Tool Budgets: Implements line caps for tool outputs (e.g., bash, grep, read) and strips ANSI colors and blank lines.
- Read Dedup: Fingerprints files per session so that repeated reads of the same file return a stub rather than the full content.
- RTK (Rust Token Killer): An optional external Rust binary that further compresses bash output before it enters the context.
Who it’s for
Developers who want a cost-effective, high-performance coding agent in their terminal that supports a wide range of LLM providers via API keys or OAuth (including Claude, ChatGPT, Gemini, and others).
Highlights
- Autonomous Goal Loop: A "Ralph-style" autopilot that can work toward a goal autonomously with state tracking and budget caps.
- Architect/Editor Split: Uses a slow, high-reasoning model for planning and a fast, cheap model for execution to reduce costs.
- Plan Mode: A read-only mode where the agent explores the codebase and produces a plan without making edits.
- Extensive Provider Support: Integration with over 20 providers and 6 OAuth flows for easy authentication.
- Session Management: Supports session branching, forking, and git-like checkpoints for rolling back code and conversation history.
- MCP Compatibility: Fully compatible with Model Context Protocol (MCP) servers and Claude Code's configuration formats.
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