consensus-divergence-monitor

You can monitor Kalshi cross-venue pricing divergences automatically by fetching market data via the Kalshi connector, scoring contract spreads, and ranking the largest consensus breaks to generate a structured desktop summary.

Cross-venue divergence monitoring identifies consensus breaks by comparing Kalshi contract pricing across multiple venues, scoring the gaps, and ranking the largest spreads to highlight significant pricing discrepancies.

Yes, you can track changes since your last scan because the monitoring process diffs the current divergence scan with prior runs, summarizes what changed, and persists ranked observations for trend comparison.

You rank Kalshi market divergences by applying transform helpers to score contract spreads, sorting the largest gaps for priority review, and routing lower-conviction breaks into a structured market watchlist.

Kalshi divergence monitoring requires no external dependencies, but it relies on the Kalshi connector to fetch market data and transform helpers to score and rank cross-venue pricing spreads.

The best way to triage large consensus breaks is to scan Kalshi venues, score divergences via transform helpers, rank the largest gaps for immediate review, and assign lower-conviction breaks to a watchlist.