Function Calling Analytics — Monitor Tool Usage & Costs

I will build a function calling analytics system — tracking tool selection frequency by function, parameter distribution for each function, execution success and failure rates, execution latency per function, token cost attribution to function calls, and function selection accuracy through sampling and human evaluation. Function calling applications deployed without analytics are flying blind — you cannot identify which functions are called most frequently (and therefore most worth optimising), which functions have the highest failure rates (and therefore most urgently need improved error handling), or whether your function selection schemas are reliably routing to the right tools.

The system covers function call logging for all production requests, selection frequency dashboard, parameter distribution analysis, success/failure rate tracking per function, latency percentile monitoring, token cost attribution, and a weekly function performance report.