gk-cost

Track token usage and dollar costs across AI-assisted development sessions.

1|Updated Jul 4, 2026
One-click install
npx skills add https://github.com/gkganesh12/gk-stack --skill gk-cost
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gk-cost
Source: https://github.com/gkganesh12/gk-stack/tree/main/skills-extra/gk-cost
Command: npx skills add https://github.com/gkganesh12/gk-stack --skill gk-cost

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the lack of visibility into AI token usage and dollar spend, preventing budget overruns by identifying inefficient patterns in your development sessions.

Core Features & Use Cases

  • Granular Cost Tracking: Measures token usage and dollar costs per task, session, feature, and project phase.
  • Pattern Detection: Automatically flags expensive behaviors like large context bloat, redundant file reads, and inefficient prompt caching.
  • Actionable Recommendations: Provides specific, data-backed advice to reduce costs, such as optimizing context loading or switching to more cost-effective models for routine tasks.

Quick Start

Run the gk-cost skill to generate a detailed report of your current session spend and receive optimization recommendations.

Frequently Asked Questions about gk-cost

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

FAQPage Schema
How do I track AI token usage and dollar costs for my development sessions?

You can reduce overall project expenditure by analyzing session data to detect cost-inefficient patterns like context bloat and redundant file reads. The skill provides specific, data-backed recommendations such as optimizing context loading or switching to more cost-effective models for routine tasks.

Why does my AI development project exceed its token budget?

AI development projects exceed token budgets due to expensive behaviors like large context bloat, redundant file reads, and inefficient prompt caching. Automatically flagging these patterns provides the visibility needed to prevent budget overruns and optimize token consumption.

What is the best way to analyze AI spend across different project phases?

Yes, you can optimize token consumption for routine tasks by following specific, data-backed advice to reduce costs. Recommendations include optimizing context loading or switching to more cost-effective models to prevent budget overruns.

How do I get optimization recommendations for my AI token consumption?

To get optimization recommendations for AI token consumption, run the skill to generate a detailed report of your current session spend. It analyzes session data to detect cost-inefficient patterns and provides actionable advice to reduce overall project expenditure.