How does Agent Cost Optimizer track costs?

It monitors token usage for every AI call in real-time and applies the latest provider pricing to calculate exact expenditures per task and session.

Does it support different Claude models?

Absolutely. It includes pricing data for Opus, Sonnet, and Haiku, and can automatically suggest or select the most cost-effective model based on task complexity.

How does the ROI measurement feature work?

It compares the cost and time spent on AI-assisted tasks against estimated manual developer hours to calculate net savings and value multipliers.

Can I set a monthly budget cap?

Yes, you can define monthly limits and warning thresholds (e.g., 80% warning). The skill can block operations that would exceed your defined budget.

Does it work with OpenAI and Google Gemini models?

Yes, the skill includes a pricing matrix for multiple providers including Anthropic, OpenAI, and Google to ensure accurate tracking across diverse AI stacks.

Agent Cost Optimizer

Name: Agent Cost Optimizer
Author: adaptationio

byadaptationio

Analíticas y Monitorización

Monitors and manages AI agent expenditures through real-time token tracking, budget enforcement, and ROI analysis.

Acerca de

Agent Cost Optimizer is a specialized tool designed to bring financial transparency and control to AI agent workflows. It enables developers to track token consumption across different models (like Claude 3.5 Sonnet or Opus), set hard budget caps to prevent unexpected overruns, and calculate the tangible ROI of AI-assisted tasks. By providing features like intelligent model selection and cost-effective caching, it ensures that AI operations remain efficient and sustainable while maximizing value delivery for enterprise and individual projects alike.

Características Principales

Intelligent model selection to balance performance and cost for every task
Real-time token usage and cost tracking across major AI providers
Advanced caching mechanism to reduce redundant API calls and expenses
Automated budget enforcement with custom warning thresholds and caps
0 GitHub stars
Detailed ROI reporting to quantify time and cost savings from AI usage

Casos de Uso

Benchmarking the cost-efficiency of different AI models for specific workflows
Preventing unexpected cloud bills during large-scale AI development projects
Generating business justification reports for enterprise AI spending

Acerca de

Características Principales

Intelligent model selection to balance performance and cost for every task
Real-time token usage and cost tracking across major AI providers
Advanced caching mechanism to reduce redundant API calls and expenses
Automated budget enforcement with custom warning thresholds and caps
0 GitHub stars
Detailed ROI reporting to quantify time and cost savings from AI usage

Casos de Uso

Benchmarking the cost-efficiency of different AI models for specific workflows
Preventing unexpected cloud bills during large-scale AI development projects
Generating business justification reports for enterprise AI spending