Execute position size updates based on analysis

Execute trades based on approved strategy signals

Extract tokens/symbols from agent messages

Filter tokens based on criteria

Calculates various metrics for a funding rate 'carry trade' or 'arbitrage': - total_cost: sum of slippage + fees - hourly_funding_rate: a

Generate a brief synopsis of the round's key points using Synopsis Agent

Generate trading signals Returns: dict: { 'token': str, # Token address 'signal'

Generate tweets from text input or file

Get current copy trading follow list

Get recent copy trading transactions

🌙 Moon Dev's Hyperliquid Data Fetcher Args: symbol (str): Trading pair symbol (e.g., 'BTC', 'ETH') timeframe (str): Cand

Get cryptocurrency global market data

Extract content from a trading idea URL or text

Get current market info for all coins on Hyperliquid

Get OHLCV data for the past 14 days in 4-hour intervals

Get total open interest data from API

Extract text from PDF URL

Get recent market data for a token

Get formatted string of recent round synopses

Calculate sentiment change from last run

Get and evaluate signals from all enabled strategies

Get all Solana tokens with market data

Get all token accounts for a specific wallet address

Get token addresses from API

Get trending search coins (Top-7) in the last 24 hours

Get tweets with proper error handling

Get transcript from YouTube video

Check and exit positions based on SELL or NOTHING recommendations

Initialize Anthropic client for default model

Initialize DeepSeek client with proper error handling

Initialize Twitter client using saved cookies

this function closes the position in full if the usd_size > 10k then it will chunk in 10k orders

Load previously discovered tokens

Load tokens from discovery script

Load or initialize historical OI data with change tracking

Load or initialize historical funding rate data

Load or initialize historical liquidation data

Load agent's memory from file

Load agent memory

Load current copybot portfolio data

Log portfolio value if not logged in past check period

Main function to run token discovery

Example usage of the calculator. Modify these parameters to test different scenarios.

Main function to run the risk agent

Main function to process ideas from file

Main function to run the trading agent every 15 minutes

Main function to run the multi-agent system

Main function to run the Listing Arb system

Package Agent: Ensures correct indicator packages are used

Parse the AI's allocation response and handle both string and TextBlock formats

Nicely format and print the results from funding_arbitrage_calculator().

Process transcript and provide focus assessment

Record audio for specified duration

Research Agent: Analyzes and creates trading strategy

Main function to run sentiment analysis

Run the funding arbitrage agent

Main loop for random focus monitoring

Run the chart analysis monitor continuously

Run the funding rate monitor continuously

Run the liquidation monitor continuously

Run all active agents in sequence

Run one complete analysis cycle with parallel processing

Async function to run sentiment analysis

Run one cycle of agent conversation

Run one monitoring cycle

Run one monitoring cycle checking all tokens

Run one monitoring cycle

Run one monitoring cycle

Run one monitoring cycle

Save discovered tokens to CSV

Save sentiment score to history

Save tweets to CSV file using pandas, appending new ones and avoiding duplicates

Wrapper for _announce to match base agent interface

Track token accounts for all wallets in the WALLETS_TO_TRACK list

Initialize the strategy

Initialize the Sentiment Agent

Initialize Dez the Whale Agent

Initialize the API handler

Initialize Moon Dev's Funding Arbitrage Agent