What LLM providers does this skill support?

It is designed to work with any provider integrated into Convex agents, such as OpenAI or Anthropic, by capturing standard usage metadata from the LLM response.

How does it handle high-usage alerts?

The skill includes an action pattern to check daily spending against predefined thresholds and can trigger notifications via email or Slack when limits are exceeded.

Can I set custom pricing for different AI models?

Yes, the skill provides implementation patterns for defining specific input and output token rates for any model, allowing for precise cost calculation.

Where is the usage data stored?

All usage records, invoices, and metrics are stored directly in your Convex database for high-performance querying and full data ownership.

Does this skill integrate with payment gateways?

It manages the data logic for usage tracking and invoice generation within Convex; you can easily connect the generated invoice data to providers like Stripe.

Convex Agent Usage Tracking

Name: Convex Agent Usage Tracking
Author: Activer007

byActiver007

Analytics & Monitoring

Tracks LLM token consumption and costs for Convex agents to enable accurate billing and performance monitoring.

About

This skill provides a comprehensive framework for monitoring and managing LLM costs within the Convex ecosystem. It allows developers to log token usage per user or agent, calculate real-time costs based on provider-specific pricing, and automate the generation of monthly invoices. By implementing robust tracking, automated crons, and alerting systems, teams can optimize agent efficiency, prevent budget overruns, and provide transparent usage reporting to their end-users.

Key Features

Performance analytics for comparing efficiency across agents
Scheduled usage alerts to prevent unexpected API spend
Monthly invoice generation and billing period management
Automated cost calculation based on model-specific pricing
Real-time token consumption logging per agent and user
0 GitHub stars

Use Cases

Monitoring and optimizing API costs across a fleet of specialized agents
Building a SaaS platform that bills customers based on their specific AI usage
Generating detailed monthly cost reports for internal team accountability

About

Key Features

Performance analytics for comparing efficiency across agents
Scheduled usage alerts to prevent unexpected API spend
Monthly invoice generation and billing period management
Automated cost calculation based on model-specific pricing
Real-time token consumption logging per agent and user
0 GitHub stars

Use Cases

Monitoring and optimizing API costs across a fleet of specialized agents
Building a SaaS platform that bills customers based on their specific AI usage
Generating detailed monthly cost reports for internal team accountability