DexScreener + ChatGPT = legal money printer I built a bot that turned 0.5 $SOL into 281 $SOL in 6 days It uses DexScreener HIDDEN data and works through Telegram Here’s how to build it yourself (or just use mine) 🧵👇

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Memecoins are printing money but most of them are scams Some traders made millions on $Ani $VINE and etc. by getting in early I built a bot that scans new tokens using DexScreener data Now I’m using it to spot hidden gems faster than ever 👇

1. Let's start creating a bot, to do this go to and sign in Install the latest version (4.5) and ask him to create a bot that will interact with Dexscreener Prompt: “Create a modular Python bot that streams real‑time token data from the Dexscreener API, refreshes a database every 30 seconds, and exposes basic query endpoints.”

2. The next step is to integrate the ability to use hidden data into our bot It will use Filters, Insider Wallets, Blacklist and SECRET data from the token Prompt: “Add an IntelligenceLayer that leverages hidden Dexscreener fields to apply custom filters, detect insider wallets, enforce a blacklist, and surface any SECRET token metadata.”

3. Now he can find tokens, at this point it is important to add functionality that can perform deep analysis It is needed to eliminate the risk of rug pull, for this purpose ask him to create a database that will check tokens for fresh wallets and fake volumes. Prompt: “Implement a RiskDB microservice that stores enriched token metrics, detects clusters of freshly funded wallets and wash‑trade‑inflated volume using heuristic and statistical rules, assigns a continuously updated rug‑risk percentile score, and serves fast async read/write access to the rest of the bot.”

4. Let's continue adding analyzing tools to our bot Integrate two platforms @Rugcheckxyz and @bubblemaps, with their help we can check CA token and Clusters among holders. The bot should check the token contract and get the result 'GOOD', then through Bubble check holders on related wallets and flag if something is wrong Prompt: “Integrate RugcheckXYZ and Bubblemaps APIs so each candidate token is first contract‑checked for a ‘GOOD’ rating, then its holder graph is scanned for suspicious concentration; flag or reject failures in the database, broadcast alerts, and prevent them from entering the trading queue.”

5. In order to trade through the bot in the future, we need to add functionality for buying and selling tokens To do this, we integrate @gmgnai using its API Prompt: “Embed fully authenticated GMGN trading capabilities—including limit‑ and market‑order placement with configurable slippage and gas caps, status polling with exponential back‑off, automatic re‑quotes on partial fills, secure key management via environment variables, and detailed post‑trade logging into the central database.”

6. The final step is to compile all the obtained functions into one bot To do this, ask GPT to compile all received modules into one Bot Prompt: “Consolidate all prior modules into a cohesive, production‑ready trading‑bot package, generate an installable pyproject.toml, and create a one‑command bootstrap script that loads env vars, migrates the database, spawns background workers, and launches the main strategy loop.”

7. For the convenience of working with the bot, we will make it possible to work with Telegram Ask GPT to write an additional script that will work with TG and send notifications of all trades. You can find full bot in my TG - Prompt: “Add a Telegram integration that authenticates with a bot token, buffers outbound messages to respect rate limits, and pushes real‑time trade alerts, contract‑risk warnings, insider‑wallet detections, and nightly PnL summaries to a configurable chat ID.”