How does this help with billing users?

The skill attributes every usage record to a specific user ID and provides automated logic to group these records into monthly billing periods for invoice generation.

Can I customize the pricing for different models?

Yes, the skill includes a mutation handler where you can define specific pricing logic (e.g., cost per million tokens) to match your LLM provider's rates.

Does it support automated high-usage alerts?

Yes, it includes patterns for setting up scheduled actions that check daily spend thresholds and can trigger notifications when usage limits are exceeded.

What metrics does this skill track?

It tracks input tokens, output tokens, total tokens, model names, provider metadata, and calculated dollar costs for every agent interaction.

Convex Agents Usage Tracking

Name: Convex Agents Usage Tracking
Author: Activer007

byActiver007

分析与监控

Monitors and logs LLM token consumption to facilitate precise billing, cost analysis, and resource optimization within Convex applications.

关于

This skill provides a comprehensive framework for tracking LLM usage metrics across agents and users within the Convex ecosystem. It enables developers to record token usage at the moment of generation, calculate costs using provider-specific pricing, and manage monthly billing cycles. By providing granular data on input and output tokens, it helps teams understand which users or specific agents consume the most resources, making it an essential tool for production-grade AI applications that require cost attribution, invoice generation, or performance monitoring.

主要功能

Real-time token consumption logging via usage handlers
Detailed usage attribution by user, agent, and LLM model
Automated cost calculation based on configurable provider pricing
0 GitHub stars
Support for daily usage alerts and performance dashboards
Monthly invoice generation and billing period management

使用场景

Implementing a usage-based billing model for AI-powered SaaS platforms
Analyzing agent efficiency to optimize prompt engineering and model selection
Monitoring LLM API expenses to prevent unexpected cost overruns

关于

主要功能

Real-time token consumption logging via usage handlers
Detailed usage attribution by user, agent, and LLM model
Automated cost calculation based on configurable provider pricing
0 GitHub stars
Support for daily usage alerts and performance dashboards
Monthly invoice generation and billing period management

使用场景

Implementing a usage-based billing model for AI-powered SaaS platforms
Analyzing agent efficiency to optimize prompt engineering and model selection
Monitoring LLM API expenses to prevent unexpected cost overruns