Context Window Analytics — Monitor Usage, Cost & Quality

I will build a context window analytics system — tracking token consumption by context component (system prompt, history, retrieved content, user input), cost attribution, context utilisation efficiency, and output quality correlation with context volume — giving you the visibility needed to make informed decisions about context strategy and budget allocation. Context window analytics surfaces insights that intuition cannot — which context components contribute most to output quality versus which consume tokens with minimal quality benefit, whether long conversations actually need full history or whether a summarised history performs equally well, and whether retrieved context is actually being used by the model or is invisible to model attention.

The system covers per-request context component logging, token consumption breakdown by component, cost attribution dashboard, context-quality correlation analysis, utilisation efficiency metrics, and a weekly context analytics report.