Read-only Python engine that turns prediction-market trading ideas into backtests and live paper tests on public Kalshi and Polymarket data, then judges each strategy with one gate: it must beat the market price's Brier score and show paper profit after Kalshi's fees. It cannot place orders and never asks for an account key. The repo includes a test suite and write-ups of many strategy studies; study results are self-reported.
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Argus: read-only strategy-testing engine for Kalshi and Polymarket is an intermediate-level data & analytics project for Kalshi and Polymarket, published by calebschalesky-ops and built with Python, Kalshi public API, Polymarket public API, Brier scoring and GitHub Actions. Its source dates from Oct 23, 2026 and was last updated Oct 23, 2026. Data and analytics projects collect, store and visualize prediction-market data: historical prices, order books, trades and resolutions.
Read-only Python engine that turns prediction-market trading ideas into backtests and live paper tests on public Kalshi and Polymarket data, then judges each strategy with one gate: it must beat the market price's Brier score and show paper profit after Kalshi's fees. It cannot place orders and never asks for an account key. The repo includes a test suite and write-ups of many strategy studies; study results are self-reported. See the source for setup, usage and current status.
Tools: PythonKalshi public APIPolymarket public API+2
Difficulty: intermediate
Platforms: Kalshi · Polymarket
Read-only Python engine that turns prediction-market trading ideas into backtests and live paper tests on public Kalshi and Polymarket data, then judges each strategy with one gate: it must beat the market price's Brier score and show paper profit after Kalshi's fees. It cannot place orders and never asks for an account key. The repo includes a test suite and write-ups of many strategy studies; study results are self-reported. It is listed under Data & analytics in this directory.
According to its source, it works with Kalshi and Polymarket.
The source lists: Python, Kalshi public API, Polymarket public API, Brier scoring, GitHub Actions.
It was published by calebschalesky-ops. The public source is at github.com/calebschalesky-ops/argus.
This directory rates it intermediate (beginner, intermediate or advanced).
It had 0 GitHub stars as of Oct 24, 2026.
The repository was last updated on Oct 23, 2026, as checked on Oct 24, 2026. Check the source for current status.
Compare all data & analytics tools → · How to build a Kalshi bot · How to build a Polymarket bot
More data: Prediction market datasets and free Kalshi JSON downloads
Framework for collecting and analyzing prediction-market data, including a large public Kalshi prediction market dataset.
Dataset stat Becker Kalshi dataset: 7.68M markets; 23.9% of settled markets resolved YES. Method on detail page.
Scripts to collect Polymarket market and trade data for analysis.
Open-source app that compares Polymarket's price on daily stock questions (close above a level, up or down) with the probability implied by the options market, computed from implied volatility, and scores both with Brier scores on resolved markets. Includes a hosted site and an MCP server endpoint. Options data comes from the Unusual Whales API. Results and any trading returns are self-reported and not verified here.
Guides: Prediction market datasets · Kalshi data and stats · Kalshi trading bots and API examples · Polymarket trading bots · Kalshi vs Polymarket · Prediction market APIs
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