ecomode

Route AI model calls to cheaper tiers to minimize token usage.

3|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/Tienching/oh-my-codebuddy --skill ecomode-tienching
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ecomode
Source: https://github.com/Tienching/oh-my-codebuddy/tree/main/skills/ecomode
Command: npx skills add https://github.com/Tienching/oh-my-codebuddy --skill ecomode-tienching

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Token-efficient model routing modifier for cost-conscious AI orchestration.

Core Features & Use Cases

  • Overrides default model selection to prefer cheaper tiers: THOROUGH -> STANDARD, THOROUGH only if essential; STANDARD -> LOW first, STANDARD if needed; LOW -> no change.
  • Supports combination with other modes: eco ralph, eco ultrawork, eco autopilot for cost-aware tradeoffs.
  • Provides delegation rules and governance to promote cost-effective execution.
  • Includes background execution guidance and state management considerations to ensure reliability and scalability.

Quick Start

Apply the ecomode modifier by prefixing commands with eco, for example eco ralph to run a low-cost Ralph loop.

Frequently Asked Questions about ecomode

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

FAQPage Schema
How do I optimize AI token usage across different delegation modes?

You can optimize AI token usage by applying a model routing modifier that overrides default selection, preferring cheaper model tiers like STANDARD or LOW across delegation modes to minimize costs.

What is cost-aware model routing in AI orchestration?

Cost-aware model routing is a technique that redirects AI model calls to cheaper execution tiers, downgrading tasks from THOROUGH to STANDARD or LOW whenever full processing power is not essential.

Can I combine cost optimization with existing execution modes like autopilot?

Yes, you can combine cost optimization with existing execution modes by prefixing commands, creating hybrid workflows like eco autopilot or eco ralph that balance operational costs with delegation behaviors.

How do I apply cheaper model tiers for background AI tasks?

Apply cheaper model tiers for background AI tasks by prefixing your commands with eco, which triggers state management rules that safely route operations to low-cost models without interrupting execution.

When should I avoid using lower model tiers for AI delegation?

You should avoid lower model tiers when tasks require deep reasoning or high accuracy, as downgrading from THOROUGH to STANDARD or LOW prioritizes token efficiency over comprehensive processing capabilities.