Cost Tracking
definition
Cost tracking monitors and attributes the token and API expenditure of agent systems, providing financial visibility into how much individual tasks, workflows, and users cost to serve. In agentic systems, costs are particularly unpredictable because the number of inference calls per task varies based on the model's reasoning path — a simple task might take 2 tool calls while a complex one generates 50, and without tracking you can't distinguish normal variation from runaway loops burning money.
Cost tracking monitors and attributes the token and API expenditure of agent systems, providing financial visibility into how much individual tasks, workflows, and users cost to serve. In agentic systems, costs are particularly unpredictable because the number of inference calls per task varies based on the model's reasoning path — a simple task might take 2 tool calls while a complex one generates 50, and without tracking you can't distinguish normal variation from runaway loops burning money. Effective cost tracking aggregates at multiple levels: per-call (raw token costs), per-task (total cost of completing a user request), and per-workflow (cost trends across similar tasks over time). This data is essential for pricing decisions, identifying optimization opportunities, and detecting anomalies like infinite loops or unexpectedly expensive model routing decisions. This concept connects to token economics for understanding the unit costs being tracked, latency optimization which often co-optimizes with cost, observability platforms for the infrastructure that captures cost data, and context caching for the primary cost reduction mechanism.