Source: DeFiTracer

Compiled by: Odaily Planet Daily Wenser

Editor's Note: As a competitor to pump.fun, the one-click coin issuance platform Moonshot released by Dexscreener has recently attracted a lot of attention. A user on the X platform, DeFiTracer, shared a tweet about building a Moonshot sniping robot using ChatGPT-4.0, claiming to have made a profit of $117,000 by sniping 17 new coins. Odaily Planet Daily will provide a brief compilation of his experience sharing for readers' reference.

Note: This article is only for sharing ideas. The promotional content in the tweet has been edited out. It does not constitute investment advice or endorsement. Please be sure to pay attention to asset security and operate with caution.

Moonshot Launches, Sniping Robots Open up New PvP Ideas

It is understood that Tracer built a GPT-4.0 sniping robot on Moonshot and earned $117,831 by sniping 17 tokens. Prior to this, he tried 84 prompts before finally finding the trick to allow the sniping robot to find tokens with hundredfold potential. Here are the specific ideas shared:

Tracer's Profit Interface

Sharp Sensibility, Identifying Opportunities at the Beginning of a New Platform Launch

Due to the updated ChatGPT 4.0 providing the ability to automatically collect all market metadata trends, using the new Moonshot to snipe meme coins is a relatively simple task for the AI robot. Currently, the AI robot can bring in thousands of dollars in income for the creator through fully automated operation every day.

Background Information: Moonshot is a new feature of @dexscreener platform, aiming to compete with @pumpdotfun. In the past 24 hours, the platform has issued 124,000 token projects, far exceeding other similar competitors.

It is worth mentioning that in the past few days, Moonshot has already launched dozens of tokens that can earn millions of dollars:

• SC: highest increase of 91 times;

• MC: highest increase of 59 times;

• FIRST: highest increase of 104 times.

Clearly, the trend of wealth creation is just beginning, and the projects incubated by Moonshot will show better results over time. Tracer started building the sniping robot at the beginning of the platform launch. Although he missed FIRST, he successfully sniped the MC and SC projects, thus gaining over $100,000 in profit.

Moonshot Interface

Clear Rules, Determining Specific Standards for Sniping Projects

The first step is to obtain the code that can parse different tokens on the Moonshot platform;

The second step is to set the standard for tokens to be parsed as those with a market value of 500 SOL or more, as shown below are the existing tokens on the platform;

The third step is to follow the platform rules, tokens that can achieve this market value usually need to meet the following conditions to successfully push into a larger market:

• Establish a liquidity pool on @RaydiumProtocol and send the remaining tokens there;

• Approximately 1.5-2 billion tokens are burned;

• The liquidity pool is locked.

Only tokens that meet these conditions are the ones we will snipe with the robot, as they have the highest growth potential.

Moonshot Platform Rules

Human-Machine Collaboration, 6 Steps to Build an AI Sniping Robot

First, log in to ChatGPT and make appropriate command requests. Ask ChatGPT to find tokens that can be parsed by the sniping robot in order of market value from highest to lowest. The purpose of this step is to allow the future robot to filter out tokens that do not meet the requirements and not waste time on low-market-value tokens.

(The specific prompt words are: create python code for parsing tokens from this site.https://dexscreener.com/moonshot. The bot should select tokens that have already reached 70%+ of the market capitalization target)

Example Interface

The second step is to use ChatGPT to create a robot to check the security of token contracts. Usually, we do not need to request a complete audit algorithm, just a check through this website—https://rugcheck.xyz. This step requires ChatGPT to use this platform to write the verification code.

(The specific prompt words are: create python code to check contract on rugheck.xyz)

Example Interface

The third step is mainly token analysis, which the robot can easily accomplish, and we can obtain the code through AI. The main checking scene for this step will be Twitter, so we need to assign tasks for the robot to use @TweetScout_io to mainly check the quality of followers of token projects and whether there are high-quality KOLs among the followers.

(The specific prompt words are: create python code to check twitter score on https://app.tweetscout.io/)

Example Interface

The fourth step is to ensure the final functionality, which is to create a sniping robot program. This is also done by making a request to ChatGPT, simply explaining that the sniping token scenario is happening on @dexscreener. Also, be sure to request the addition of variables for slippage, price impact, and transaction priority so that you can customize these settings.

(The specific prompt words are: create python code to snipe sol tokens from https://dexscreener.com/. Be sure to add 3 variables, namely Slippage, Price Impact, and TX Priority so that the user can customize them.)

Example Interface

The fifth step is to set the variables as follows after obtaining the program code:

• Slippage = 30%

• Price Impact = 30%

• TX Priority = High

These settings can help you snipe highly unstable tokens at a faster pace (of course, also implying greater risk).

Corresponding Settings Interface

The sixth step is to merge all the code received from ChatGPT and request it to be compiled into a complete robot project. In the end, you will have a token sniping robot that can parse and analyze token projects from Moonshot. Additionally, based on the analysis, the robot will also automatically make buying and selling decisions, but of course, you can also choose to operate manually. A glimpse of the specific code content can be seen in this tweet.

(The content of the example interface is:

Combine all these code fragments into one complete bot

Snipe on Dexscreener:

import requests

from solana.rpc.api import Client

from solana,transaction import Transaction

from solana.keypair import Keypair

from solana.publickey import PublicKey

from solana.rpc.types import TxOpts

# User configuration

SLIPPAGE=0.01 #1%

PRICE IMPACT=0.02 #2%

TX_PRlORITY= "high" # options: low, medium, high

# Initialize Solana clientclient= Client("https://api.mainnet-beta,solana.com")

# Function to get current price from Dexscreener

def get price from dexscreener():

response =

requests.get("https://api.dexscreener.io/latest/dex/pairs/solana"

data = response,ison()

# Parse the JsON to get the price of sOL/usDT pair

sol_usdt _pair = next(pair for pair in data['pairs"] if

pair["baseToken"l['symbol'] == 'SOL' and pair['quoteToken"l

['symbol'] == 'USNT')

return sol usdi air['priceUsd"!）

Example Interface

This is all the content needed to create a Moonshot sniping robot.)

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