Monitor Kalshi

Name: Monitor Kalshi
Availability: InStock
Author: @aaronjmars

Monitor Kalshi prediction markets for 24h price and liquidity changes.

626|225|Updated Mar 4, 2026

Search Tags:#market research #market monitoring #liquidity #volatility #kalshi #prediction markets #implied probability

Ready to run

npx skills add https://github.com/aaronjmars/aeon --skill monitor-kalshi-aaronjmars

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Monitor Kalshi
Source: https://github.com/aaronjmars/aeon/tree/main/skills/monitor-kalshi
Command: npx skills add https://github.com/aaronjmars/aeon --skill monitor-kalshi-aaronjmars

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns raw Kalshi market data into a ranked, decision-ready digest that highlights which prediction markets moved meaningfully over the last 24 hours and why those moves matter.

Core Features & Use Cases

Watchlist-driven monitoring: Tracks a configurable list of event tickers for 24h price moves, volume shifts, and liquidity changes.
Signal-based ranking and suppression: Ranks markets by decision value using move magnitude weighted by meaningful volume, while filtering noise.
Liquidity/conviction context: Uses orderbook spread and depth-derived metrics to label conviction and to prioritize non-thin-book moves.
Change detection across days: Compares against prior logs to demote repeated stories and flag genuinely new movers.

Quick Start

Run the Monitor Kalshi skill with an empty watchlist and let it discover and notify about the top-volume open events for this run only.

Frequently Asked Questions about Monitor Kalshi

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I monitor Kalshi prediction markets for meaningful price moves?▼

To monitor Kalshi prediction markets for meaningful price moves, you need a system that tracks 24h volume-weighted price changes and liquidity shifts. This skill ranks markets by move magnitude and orderbook conviction, filtering noise to highlight actionable events.

What is implied probability in prediction market monitoring?▼

Implied probability in prediction market monitoring is the likelihood of an event derived from current market prices. This skill calculates these probabilities and tracks their intraday percentage point changes to identify significant market shifts and actionable trading signals.

How do I track liquidity and volatility changes on Kalshi markets?▼

You can track liquidity and volatility changes on Kalshi markets by analyzing orderbook spread and depth. This skill uses these metrics to label market conviction, ensuring that only volume-backed moves with sufficient liquidity are prioritized in your daily research digest.

Can I get automated daily market briefs for Kalshi prediction markets?▼

Yes, you can get automated daily market briefs for Kalshi prediction markets by running this skill unattended. It optionally discovers top-volume open events or monitors a configured watchlist, summarizing ranked movers and generating event-level alerts for decision-making.

How do I filter out noise when tracking prediction market movers?▼

To filter out noise when tracking prediction market movers, apply suppression gates and cross-day continuation checks against prior memory logs. This skill demotes repeated stories and highlights genuinely new movers by comparing current data with historical change logs.

Do I need a predefined watchlist to monitor Kalshi events?▼

No, you do not need a predefined watchlist to monitor Kalshi events. This skill can automatically discover and notify you about the top-volume open events for the current run, allowing you to track significant market moves without prior configuration.