Can I set up alerts for high AI spending?

Yes, the skill includes implementation patterns for monitoring daily usage and triggering notifications when spending exceeds a predefined threshold.

How do I calculate LLM costs with this skill?

The skill includes logic to define input and output token prices per model, allowing for real-time cost estimation at the point of generation.

Does this skill support automatic invoicing?

It provides code structures for Convex crons that aggregate usage data and generate invoices automatically at the end of each billing period.

What is Convex Agent Usage Tracking?

It is a Claude Code skill that helps developers monitor token consumption and costs for AI agents built on the Convex platform.

Convex Agent Usage Tracking

Name: Convex Agent Usage Tracking
Author: Microck

byMicrock

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Analytics & Monitoring

Monitors and logs LLM token consumption and usage costs across Convex agents for precise billing and performance optimization.

About

Convex Agent Usage Tracking provides a robust framework for managing the financial and operational aspects of LLM-powered applications. It enables developers to capture granular token counts for every model interaction, attribute costs to specific users or teams, and automate the generation of monthly invoices. By implementing specialized usage handlers and scheduled cron jobs, teams can gain deep visibility into resource consumption, set up proactive spend alerts, and optimize their AI infrastructure for maximum cost-effectiveness.

Key Features

Granular analytics for agent efficiency and user attribution
Real-time token consumption logging per agent and user
Automated cost calculation based on provider-specific pricing
High-usage alerting to prevent unexpected API spend
Monthly invoice generation and billing period management
81 GitHub stars

Use Cases

Creating usage dashboards to track resource consumption trends over time
Monitoring internal API costs to optimize model selection and prompt efficiency
Building a SaaS platform that bills users based on their AI usage

About

Key Features

Granular analytics for agent efficiency and user attribution
Real-time token consumption logging per agent and user
Automated cost calculation based on provider-specific pricing
High-usage alerting to prevent unexpected API spend
Monthly invoice generation and billing period management
81 GitHub stars

Use Cases

Creating usage dashboards to track resource consumption trends over time
Monitoring internal API costs to optimize model selection and prompt efficiency
Building a SaaS platform that bills users based on their AI usage