Can I use this for all Claude models?

Yes, the skill provides strategies applicable across the Claude 3 and 3.5 families, including logic for routing tasks to the most cost-effective model like Haiku for simple classifications.

What is the 'effort parameter' mentioned in this skill?

The effort parameter allows you to adjust the reasoning depth of models like Claude 3.5 Opus. Using 'low' or 'medium' effort for simpler tasks can reduce token usage by 20-70% while maintaining accuracy.

How much can I save using these optimization techniques?

Users typically see reductions of 10-90% depending on the implementation. Techniques like prompt caching and context editing offer the highest savings for long-running conversations and repeated content.

Does this skill require access to the Anthropic Admin API?

Usage tracking and baseline measurement features utilize the Admin API for comprehensive metrics, but the optimization patterns (caching, model selection, context editing) can be applied to standard API implementations.

Claude Cost Optimization

Name: Claude Cost Optimization
Author: adaptationio

byadaptationio

分析と監視

Optimizes production Claude deployments by tracking token usage, identifying expensive patterns, and implementing advanced cost-saving techniques.

概要

The Claude Cost Optimization skill provides a comprehensive framework for managing and reducing expenses in production-grade Claude environments. It enables developers to establish a cost baseline via the Admin API, analyze expensive interaction patterns, and apply sophisticated optimization strategies—including prompt caching, context editing, and strategic model selection. By integrating ROI calculation tools and budget forecasting, this skill ensures that AI integrations remain economically viable while maximizing efficiency through techniques like effort parameter tuning and tool search optimization.

主な機能

Admin API integration for real-time token and expenditure tracking
Strategic model selection and effort parameter tuning for task-specific savings
Prompt caching implementation strategies to reduce costs on redundant inputs
0 GitHub stars
Advanced context editing and tool optimization to minimize conversation bloat
ROI and payback period calculators for business value reporting

ユースケース

Reducing operational overhead for high-volume agentic workflows and reasoning loops
Forecasting API budgets and setting up cost alerts for production scaling
Implementing cost-efficient classification and data processing pipelines using Haiku

概要

主な機能

Admin API integration for real-time token and expenditure tracking
Strategic model selection and effort parameter tuning for task-specific savings
Prompt caching implementation strategies to reduce costs on redundant inputs
0 GitHub stars
Advanced context editing and tool optimization to minimize conversation bloat
ROI and payback period calculators for business value reporting

ユースケース

Reducing operational overhead for high-volume agentic workflows and reasoning loops
Forecasting API budgets and setting up cost alerts for production scaling
Implementing cost-efficient classification and data processing pipelines using Haiku