Tracks and analyzes OpenRouter API consumption patterns to optimize costs and monitor performance metrics.
This skill provides a comprehensive framework for monitoring OpenRouter API interactions, enabling developers to instrument calls, store time-series metrics, and generate detailed reports. It is particularly useful for teams looking to control LLM spend, identify model popularity trends, analyze latency, and detect anomalies in token usage across various providers. By implementing this skill, users can build a robust observability layer for their AI-driven applications, ensuring cost-efficiency and reliable performance.
Key Features
01Aggregated reporting on token consumption and model popularity
02Automated anomaly detection and weekly usage summary reports
03Time-series data storage for historical usage and trend analysis
04Visual dashboard generation for spend and error rate monitoring
05Real-time API call instrumentation for cost and latency tracking
060 GitHub stars
Use Cases
01Generating internal billing reports for project-based resource allocation
02Optimizing LLM budgets by identifying high-spend models and inefficient usage
03Monitoring API performance and provider latency across OpenRouter's network
