Token Usage Monitor#

Overview#

This skill provides comprehensive token usage monitoring and reporting capabilities for AI models. It helps you track token consumption in real-time, analyze historical usage patterns, and receive alerts when usage exceeds predefined thresholds. Ideal for optimizing prompt costs, controlling AI service expenses, and ensuring efficient use of model resources.

Core Capabilities#

1. Real-Time Token Usage Monitoring#

• Track token consumption per request, per session, and per model
• Monitor token usage speed (tokens per second/minute)
• View live usage metrics including prompt tokens, completion tokens, and total tokens

2. Historical Usage Analysis#

• Generate usage reports for specified time periods (daily, weekly, monthly)
• Analyze usage trends across different models and applications
• Identify peak usage times and cost drivers

3. Threshold Alerts#

• Set custom token usage thresholds for different models or sessions
• Receive notifications when usage exceeds defined limits
• Configure alert channels (chat, email, or system notifications)

4. Cost Estimation#

• Calculate approximate costs based on token usage and model pricing
• Compare costs across different models and providers
• Optimize prompts to reduce token usage and costs

Quick Start#

Monitor Current Session Usage#

bash

# Check current session token usage
python scripts/token_usage_tracker.py --session

Generate Daily Usage Report#

bash

# Generate report for today's usage
python scripts/token_usage_tracker.py --report --period day

Set Usage Threshold#

bash

# Set threshold of 100,000 tokens per day for GPT-4
python scripts/token_usage_tracker.py --set-threshold --model gpt-4 --limit 100000 --period day

Resources#

scripts/#

Create only the resource directories this skill actually needs. Delete this section if no resources are required.

scripts/#

• token_usage_tracker.py: Main script for tracking and reporting token usage

  Key features:

  • Tracks token usage per session, model, and time period
  • Generates daily usage reports with cost estimates
  • Supports custom usage thresholds and alerts
  • Provides real-time and historical usage analytics

Usage examples: bash

# Track a single usage event
python scripts/token_usage_tracker.py --track --model doubao-seed --prompt-tokens 100 --completion-tokens 200

# View current session usage
python scripts/token_usage_tracker.py --session

# Generate daily usage report
python scripts/token_usage_tracker.py --report --period day

# Set usage threshold (100,000 tokens/day for Doubao)
python scripts/token_usage_tracker.py --set-threshold --model doubao-seed --limit 100000

# View overall usage summary
python scripts/token_usage_tracker.py --summary

Note: The script automatically creates and manages a data file at ~/.openclaw/token_usage.json to store usage data.

references/#

Documentation and reference material intended to be loaded into context to inform Codex's process and thinking.

Examples from other skills:

• Product management: communication.md, context_building.md - detailed workflow guides
• BigQuery: API reference documentation and query examples
• Finance: Schema documentation, company policies

Appropriate for: In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working.

assets/#

Files not intended to be loaded into context, but rather used within the output Codex produces.

Examples from other skills:

• Brand styling: PowerPoint template files (.pptx), logo files
• Frontend builder: HTML/React boilerplate project directories
• Typography: Font files (.ttf, .woff2)

Appropriate for: Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output.

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Not every skill requires all three types of resources.