Creating an Autonomous Bot for Arbitrage Monitoring

You want to automate the search and tracking of arbitrage opportunities (price differences, cheap assets) between different platforms or markets. This will allow you to catch profitable deals 24/7 without your constant involvement.

3 stepа 3 views 0 votes 26.02.2026
1
Design the bot…
2
Write and test…
3
Launch and aut…
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Step 1: Design the bot logic

Claude Free+

Go to the claude.ai website or open the app → create a new chat → describe in detail the task of creating an autonomous bot for monitoring. Ask to design the architecture: what data to collect (prices, availability), from where (exchange APIs, marketplaces), how often to check, what conditions trigger an alert (% difference), where to send notifications (Telegram, email).

Prompt — copy and paste:
You are a senior developer of automated monitoring and arbitrage systems. I need an autonomous AI bot for 24/7 monitoring of arbitrage windows (price differences for the same assets/goods between different platforms, e.g., crypto exchanges or marketplaces). Please design a detailed architecture and logic for such a bot. In your response, provide: 1. **Goal:** A clear description of what the bot should do (e.g., track the price of BTC on Binance, Bybit, and Kraken, calculate the spread, send an alert when the threshold is exceeded). 2. **System Components:** - Data collection module (which APIs to use, how to parse, request frequency). - Analysis module (formula for calculating the arbitrage window, threshold values). - Alert module (Telegram Bot API, email, webhook). - Logging and history storage module. 3. **Technology Stack:** Recommended languages (Python), libraries (requests, pandas, ccxt for crypto), deployment methods (server, cloud function). 4. **Data Flow:** Step-by-step scheme from data request to alert sending. 5. **Code Example:** A template of the main monitoring loop in Python with comments. Response format: A structured plan with headings and code.
Open Claude
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Step 2: Write and test the code

Cursor Free+

Install and open Cursor → create a new project → use the plan from Claude as the technical specification. Using the AI assistant in Cursor, start writing the bot code in Python. First, set up the connection to the APIs of the selected platforms (use the ccxt library for crypto or requests for others), then implement the price comparison logic and alert conditions. Test the operation on demo data.

Task for the coding tool:
Task: Create an autonomous Python bot for monitoring arbitrage windows. Initial data: - Architecture and plan from Claude (see context above). - Goal: The bot should every 30 seconds request the price of an asset (e.g., BTC/USDT) from three exchanges (Binance, Bybit, Kraken) using the ccxt library, calculate the spread between the maximum and minimum price, and if the spread exceeds 0.5%, send a message to a Telegram bot with details (exchanges, prices, spread, potential profit). Technical requirements: - Language: Python 3.10+ - Libraries: ccxt, requests, python-telegram-bot, schedule, logging. - Project structure: main.py (main loop), config.py (API keys, settings), utils.py (calculation functions), alerts.py (Telegram sending). Please generate: 1. Complete code for the config.py file with an example structure for storing API keys (leave empty) and settings (list of exchanges, ticker, spread threshold, Telegram chat ID). 2. Code for a function in utils.py that takes a dictionary of prices from exchanges and returns the calculated spread and the exchanges with min/max price. 3. Code for a function in alerts.py for sending a formatted message to Telegram. 4. The main loop in main.py that uses schedule for periodic monitoring runs, handles exceptions, and logs events. The code should be ready to run after filling the config with real keys.
Open Cursor
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Step 3: Launch and automate

Browse AI Free+

If your arbitrage windows are on websites (not via API), use Browse AI. Go to browse.ai → create a new robot → select 'Monitor websites and extract data' → specify the URL of the site to monitor (e.g., a product page). Train the robot to highlight the necessary data on the page (price, availability). Set up a check schedule (every 5 minutes) and notifications to Slack or email when data changes. This will give you autonomous monitoring without programming.

Open Browse AI

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