traderbot 0.14.75

Autonomous prediction market investment toolkit for Kalshi

TraderBot

Autonomous prediction market investment toolkit for Kalshi.

TraderBot provides the data pipeline, statistical analysis, risk enforcement, simulation, and execution layer that an AI agent needs to trade prediction markets.

Core Principle

Dumb pipe with smart guards. The toolkit handles the how (API calls, data normalization, risk limits, execution) but never the why (what to trade, when, how much). The agent decides strategy; the toolkit ensures execution is safe, correct, and auditable.

This separation is deliberate: it eliminates emotional bias from the execution layer. Even if the agent's LLM "decides" to go all-in on a hunch, hard-coded risk guards reject the order before it reaches the exchange.

Install

From PyPI (recommended)

pip install traderbot

From source

git clone https://github.com/JsonDaRula69/TraderBot.git
cd TraderBot
uv sync  # or: pip install -e .

One-Liner Install (Linux/macOS)

curl -fsSL https://raw.githubusercontent.com/JsonDaRula69/TraderBot/main/install/traderbot-installer.sh | bash

Requires Python 3.12 and Kalshi API credentials (sign up at kalshi.com and generate an API key + RSA key pair).

Quick Start

# Store Kalshi credentials in your OS keyring
traderbot auth set-kalshi

# Scan available weather markets
traderbot scan --category weather

# Analyze a specific market
traderbot analyze KXHIGHNY-26JUN02-T72

# Paper trade with a strategy
traderbot paper momentum

# View your positions
traderbot positions

# Check for updates
traderbot update --check

Using with OpenClaw AI Agents

TraderBot integrates with OpenClaw for autonomous agent operation:

# Create a profile for your agent
traderbot profile create --name weather-agent --category weather

# Assign the profile token
traderbot profile assign --agent weather-agent --token $(traderbot profile token weather-agent)

The agent runs three autonomous loops: decision (every 5 min), heartbeat (every 30 min), and news/sentiment (event-driven). See docs/architecture.md for details.

CLI Overview

Command	Description
traderbot scan	List open markets across categories
traderbot analyze TICKER	Orderbook depth + implied probability
traderbot signals	Active trading signals
traderbot trade	Place an order through risk checks
traderbot positions	View open positions with live pricing
traderbot audit	Decision history with filters
traderbot performance	P&L and win-rate metrics
traderbot paper	Run a paper trading session
traderbot backtest	Run backtests against historical data
traderbot compare	Compare profiles across strategies
traderbot halt	Check circuit breaker status
traderbot resume	Clear circuit breaker halt state
traderbot heartbeat	Self-review cycle
traderbot learnings	List and promote learned patterns
traderbot data forecasts	Weather forecasts with NWS + GFS/ECMWF/GEM ensemble
traderbot data bias CITY	Historical forecast bias for a city
traderbot news-context	News context for a category
traderbot auth	Credential management
traderbot profile	Multi-agent profile management
traderbot cron	Register heartbeat cron jobs with OpenClaw
traderbot update	Check for and apply updates

Project Structure

src/traderbot/
├── kalshi/           # Kalshi exchange adapter
├── analysis/         # Statistical computation engine
├── risk/             # Immutable risk enforcement
├── simulation/       # Backtesting & paper trading
├── news/             # News & sentiment pipeline
├── data/             # Weather & market data providers
├── db/               # SQLite persistence
├── profiles/         # Multi-agent profile system
├── cli/              # Typer CLI entry point and sub-commands
├── experiment/       # Experiment design and evaluation
├── heartbeat.py      # Self-review cycle
├── auth.py           # Credential management
├── learning.py       # Learning log manager
└── updater.py        # Version management

Documentation

Document	Scope
docs/architecture.md	Three-loop system, components, data flow
docs/kalshi.md	Kalshi API reference
docs/risk.md	Risk guards, circuit breakers, position sizing
docs/simulation.md	Backtest engine, paper trading
docs/profiles.md	Profile system, tokens, multi-agent
docs/deployment.md	Production deployment
docs/api.md	Full CLI reference

License

MIT