eco-mode

Reduce token usage and carbon emissions by compressing outputs and batching tool calls.

Updated Apr 23, 2026

Search Tags:#efficiency #token-saving #eco #carbon-footprint #AI-optimization

Ready to run

npx skills add https://github.com/pooriaarab/skills --skill eco-mode

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: eco-mode
Source: https://github.com/pooriaarab/skills/tree/main/eco-mode
Command: npx skills add https://github.com/pooriaarab/skills --skill eco-mode

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It helps minimize token consumption and carbon footprint during AI interactions by compressing outputs and optimizing tool calls.

Core Features & Use Cases

Token reduction: Compresses Claude's responses by dropping fillers, hedging, and pleasantries.
Batch processing: Combines multiple tool calls into single requests to save tokens.
Use Case: A user wants to analyze large documents efficiently; activate eco mode to limit token usage and environmental impact.

Quick Start

Say "enable eco mode" before starting your AI session to activate token and CO₂ savings.

Frequently Asked Questions about eco-mode

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

FAQPage Schema

How do I reduce token usage and carbon footprint when analyzing large documents with AI?▼

To reduce token usage and carbon footprint during AI interactions, activate eco mode to compress outputs by dropping fillers and pleasantries. This minimizes computational costs and environmental impact without degrading technical quality.

How do I enable eco mode for token reduction in my AI session?▼

To enable token reduction, simply say "enable eco mode" before starting your AI session. This activates output compression and batches tool calls to optimize computational resource consumption throughout your workflow.

Does compressing AI responses to save tokens affect output quality?▼

Compressing AI responses to save tokens does not affect output quality. The process safely drops hedging, fillers, and pleasantries while batching tool calls, ensuring consistent reduction of resource consumption without impacting technical accuracy.

What is the best way to batch tool calls for AI optimization and CO2 reduction?▼

The best way to batch tool calls for AI optimization and CO2 reduction is using eco mode, which combines multiple tool calls into single requests. This limits token usage and manages environmental impact efficiently.

Can I use token-saving compression for sustainable workflows on any AI model?▼

Token-saving compression for sustainable workflows provides model suggestions and precise output management. It is applicable in scenarios where minimizing computational costs is critical, ensuring safe and consistent resource reduction.

Why does batching tool calls help minimize computational costs in AI?▼

Batching tool calls helps minimize computational costs by combining multiple requests into a single operation. This reduces overall token consumption and carbon emissions, enabling efficient and sustainable AI workflows.