How asarchitects/kalshi-trade-bot works
This repository snapshot contains no application source files, so the architecture below reflects the README’s documented workflow rather than verified module-level calls. The README describes a TypeScript bot, while requirements.txt lists Python dependencies; the implementation language and actual wiring therefore remain unverified.
Main entry points: .env.example Trading configuration
Components 18
Market monitoring
- Trading configuration
.env.example - Bot workflow
- Market matching
- Price monitoring
Arbitrage strategy
- Opportunity detection
- Betted-price analysis
- Trade sizing
Trading lifecycle
- Position tracking
- Trade execution
- Market resolution
- Automatic redemption
Platform integrations
- Polymarket markets
- Kalshi markets
- Polymarket trading
- Kalshi trading
Other components
- Operator
- Polymarket
- Kalshi
Connections 23
- Operator → Trading configuration: sets
- Trading configuration → Bot workflow: configures
- Bot workflow → Polymarket markets: requests markets
- Bot workflow → Kalshi markets: requests markets
- Polymarket markets → Polymarket: fetches from
- Kalshi markets → Kalshi: fetches from
- Bot workflow → Market matching: matches markets
- Bot workflow → Price monitoring: monitors prices
- Price monitoring → Polymarket: reads prices
- Price monitoring → Kalshi: reads prices
- Bot workflow → Opportunity detection: checks opportunities
- Opportunity detection → Betted-price analysis: evaluates direction
- Bot workflow → Trade sizing: sizes trades
- Bot workflow → Trade execution: executes trades
- Trade execution → Polymarket trading: places orders
- Trade execution → Kalshi trading: places orders
- Polymarket trading → Polymarket: trades on
- Kalshi trading → Kalshi: trades on
- Bot workflow → Position tracking: tracks positions
- Bot workflow → Market resolution: checks resolution
- Bot workflow → Automatic redemption: redeems winners
- Automatic redemption → Polymarket: redeems on
- Automatic redemption → Kalshi: redeems on