LoRA fine-tune Gemma 4 31B to speak caveman-mode natively. Style: github.com/JuliusBrussee/caveman
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Updated
May 17, 2026 - Python
LoRA fine-tune Gemma 4 31B to speak caveman-mode natively. Style: github.com/JuliusBrussee/caveman
OpenCode package for Caveman: terse AI responses, slash commands, compact reviews, commit messages, and markdown memory compression.
Caveman prompting, measured. A two-channel evaluation protocol scoring what input and output compression actually cost LLMs in dollars, accuracy, and surface-text fidelity across seven models and five benchmarks.
🪨 Cut LLM token costs 40-75%. Works with Claude Code, Gemini CLI, Codex, aider. No API key needed.
Terse, token-efficient communication skill for Kimi Code CLI. Cut 60-75% of output tokens while keeping full technical accuracy.
Caveman mode for pi: ultra-compressed agent responses, terse commits, reviews, and memory compression.
Caveman-compressed reasoning trace curator for token-efficient SFT datasets
Make caveman worse by giving it Claptrap personality. Same 75% token savings. Personality more annoying. 🤖
Caveman terse communication mode for Pi and Codex
Reduce LLM token usage by 40–75 percent with this CLI tool and SDK. Optimize prompts for Claude, OpenAI, and other models without needing an API key.
Save tokens with persistent code memory and structural navigation for Claude Code
MCP server tools for Claude-Desktop app, for reducing token consumption, the input tokens are reduced by MCP server tools and the output tokens are reduced by Caveman skill
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