usage

Track token usage and estimate costs across sessions, users, and models.

71|22|Updated Apr 6, 2020
One-click install
npx skills add https://github.com/nirholas/agenti --skill usage-nirholas
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: usage
Source: https://github.com/nirholas/agenti/tree/main/packages/protocols/x402-cloddsbot/src/skills/bundled/usage
Command: npx skills add https://github.com/nirholas/agenti --skill usage-nirholas

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Token usage tracking, cost estimation, and usage analytics.

Core Features & Use Cases

  • Track session and user usage across models to optimize AI spend.
  • Generate per-model and per-user insights for budgeting and governance.
  • Use Case: Analyze monthly token consumption across teams to identify cost-saving opportunities.

Quick Start

Start by initializing the usage system and recording a sample event to verify data collection.

Frequently Asked Questions about usage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track token usage and estimate costs for AI models across different sessions?

Track token usage and estimate costs by recording consumption events across sessions, users, and models. The system analyzes AI consumption to provide detailed insights for optimizing budgeting and spend.

What is the best way to generate usage reports for monthly AI token consumption?

Generate usage reports by querying recorded token consumption summaries across specific time ranges. This provides per-model and per-user insights to identify cost-saving opportunities and support budgeting governance.

Can I analyze per-user token consumption to identify cost-saving opportunities?

Analyze per-user token consumption to identify cost-saving opportunities by implementing a structured API surface. It queries usage summaries and generates detailed reports for budgeting and governance.

How does token usage tracking handle errors and safe data access when recording events?

Token usage tracking implements robust error handling and safe data access when recording events and querying summaries. This ensures reliable data collection and detailed usage insights across sessions.

Do I need to initialize the system before recording a sample usage event?

Initialize the usage system before recording a sample event to verify data collection. This setup enables accurate tracking of token usage, cost estimation, and analysis of AI consumption across models.

What limitations exist when analyzing AI consumption across different time ranges?

Analyzing AI consumption across time ranges requires structured API queries for summaries and reports. Limitations depend on safe data access protocols and robust error handling during usage tracking operations.