productivity-caveman

Compresses assistant responses into terse, high-signal language while preserving technical accuracy.

Updated Mar 19, 2026

Search Tags:#communication style #technical accuracy #brevity #token reduction #caveman mode #concise responses

Ready to run

npx skills add https://github.com/dragoscirjan/opencode-config --skill productivity-caveman

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: productivity-caveman
Source: https://github.com/dragoscirjan/opencode-config/tree/main/skills/productivity-caveman
Command: npx skills add https://github.com/dragoscirjan/opencode-config --skill productivity-caveman

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill cuts response length dramatically by removing filler, politeness, and extra phrasing while keeping the full technical meaning intact. It is useful when you want fast, compact answers that still preserve exact code, errors, and implementation details.

Core Features & Use Cases

Ultra-brief communication: Produces short, high-signal replies that reduce token usage.
Technical fidelity: Keeps terminology, code blocks, and error text exact.
Persistent style mode: Stays active after activation until you explicitly stop it.
Use case: Handy for debugging, status updates, quick explanations, and any workflow where brevity matters more than polish.

Quick Start

Tell the assistant to answer your next request in caveman mode with concise, technical wording.

Frequently Asked Questions about productivity-caveman

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I make chat responses more concise without losing technical accuracy?▼

To make chat responses more concise without losing technical accuracy, you can use a communication style that strips filler, hedging, and verbose transitions. This approach compresses replies into high-signal language while preserving exact terminology, code, and error text.

What is caveman mode for AI responses?▼

Caveman mode is a persistent communication style that compresses assistant responses into terse, high-signal language. It stays active until explicitly stopped, reducing token usage while maintaining full technical fidelity for code and error text.

How do I reduce token usage during debugging sessions?▼

You can reduce token usage during debugging by applying a terse response style that removes pleasantries and filler. This keeps the output compact and high-signal while retaining exact error text and implementation details.

Can I get brief technical explanations without removing code blocks?▼

Yes, you can get brief technical explanations without removing code blocks. This communication style preserves exact code, terminology, and error text while stripping away verbose transitions and pleasantries.

When should I use a terse communication style for AI replies?▼

You should use a terse communication style for AI replies when brevity and speed matter more than polish. It is ideal for debugging, status updates, and quick explanations where reducing response length and token usage is the priority.