caveman

Name: caveman
Availability: InStock
Author: Haohao

Compress responses to retain conclusions, constraints, next steps, and file references.

779|80|Updated Jun 20, 2025

Search Tags:#prompt optimization #technical accuracy #token reduction #session efficiency #concise writing #compression mode

Ready to run

npx skills add https://github.com/Haohao-end/openagent --skill caveman-haohao-end

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: caveman
Source: https://github.com/Haohao-end/openagent/tree/main/api/internal/core/skills/catalog/caveman
Command: npx skills add https://github.com/Haohao-end/openagent --skill caveman-haohao-end

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

When conversations get long or users explicitly want less output, caveman reduces token usage while preserving technical accuracy.

Core Features & Use Cases

Ultra-compressed responses: Produces shorter answers without removing necessary technical meaning.
Clarity-preserving constraints: Keeps conclusions, constraints, next steps, and required file references.
Avoids fluff: Removes greetings, repetition, and empty phrasing while staying precise.

Quick Start

Ask the assistant to respond in caveman mode to produce a concise, technically accurate answer with the key conclusion, constraints, and next steps.

Frequently Asked Questions about caveman

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

FAQPage Schema

How do I get shorter responses while maintaining technical accuracy in a long chat session?▼

To get shorter responses while maintaining technical accuracy, use a compression mode that removes filler and repetition while preserving conclusions, constraints, next steps, and necessary file references in the output.

What is token reduction and how does it preserve conclusions during output compression?▼

Token reduction is an optimization technique that reduces token usage by generating ultra-compressed answers. It preserves conclusions by stripping out empty phrasing and greetings while retaining necessary technical meaning.

How do I write concise technical answers without losing required file references and constraints?▼

To write concise technical answers without losing required file references, apply prompt optimization constraints that require direct answers retaining conclusions and constraints while removing ambiguity and fluff.

Can I use prompt optimization to avoid verbosity in ongoing chat sessions?▼

Yes, you can use prompt optimization to avoid verbosity in ongoing chat sessions by applying a compression mode that automatically triggers output compression when an ongoing session needs shorter outputs.

What are the limitations of using ultra-compressed responses for session efficiency?▼

The limitation of ultra-compressed responses for session efficiency is that removing too much context may increase ambiguity, requiring careful prompt optimization to ensure technical accuracy and necessary file references are not lost.