AI ロボットを使ってムーンショットの新コインを狙う: 初心者でも科学者になれるのか?

出典: DeFiTracer

編集：Odaily Planet Daily Wenser

Editors note: As a competitor of ポンプ.楽しい , Moonshot, a one-click coin issuance platform released by デクスクリーナー , has attracted a lot of attention recently. DeFiTracer , a user of X platform, shared a tweet about building a Moonshot sniping robot with ChatGPT-4.0. According to him, he made a profit of $117,000 by sniping 17 new coins. Odaily Planet Daily will briefly compile his experience sharing for readers reference.

Note: This article is only for sharing ideas. The content of the tweet has been deleted. It does not constitute investment advice or platform endorsement. Please be sure to pay attention to the safety of your assets and operate with caution.

Moonshot is online, sniper robot opens up new ideas for PVP

It is understood that Tracer built a GPT-4.0 sniper robot after Moonshot went online, earning $117,831 by sniping 17 tokens. Previously, he tried 84 prompts before finally finding the trick to let the sniper robot find 100x coins. The following is a specific idea sharing:

Tracer’s profit interface

A keen sense of smell, discovering opportunities at the beginning of the launch of new platforms

Since the updated ChatGPT 4.0 provides the ability to automatically collect all metadata trends in the market, using the new Moonshot to snipe meme coins is a relatively simple task for AI bots. Currently, AI bots can bring thousands of dollars in revenue to creators every day through fully automated operations.

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

It’s worth noting that in just the past few days, Moonshot has listed dozens of tokens capable of earning millions of dollars:

• SC: The highest increase was 91 times;

• MC – maximum increase of 59 times;

• FIRST – Maximum increase of 104 times.

It is clear that the trend of wealth creation has just begun, and the projects incubated by Moonshot will show better results over time. Tracer started building sniper robots at the beginning of the platform. Although he missed FIRST, he successfully sniped the two projects MC そして SC , thus making a profit of more than $100,000.

ムーンショット インタフェース

Clarify the rules and determine the specific standards for sniping projects

The first step is to get the code that can parse the different tokens of the Moonshot platform;

In the second step, the token standard to be parsed is set to a token with a market value of 500 SOL. The following shows the existing tokens on the platform;

In the third step, according to the platform rules, tokens that can reach such a market value usually need to meet the following conditions to be successfully introduced to a larger market:

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

• Approximately 150-200 million tokens were destroyed;

• The liquidity pool is locked.

Only the tokens that meet these criteria are the ones we will snipe with our bots because they have the highest growth potential.

Moonshot Platform Rules

Human-machine collaboration: 6 steps to build an AI sniper robot

First, log in to ChatGPT and make the appropriate request. Ask ChatGPT to find the code that can parse Moonshot tokens in order from largest market cap to smallest market cap. The purpose of this step is to allow future robots to filter out tokens that do not meet the requirements and not waste time on low market cap tokens.

(The specific prompt is: 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 bot to check the security of the token contract. Usually, we don’t need to require a full audit algorithm, just check it through this website – https://rugcheck.xyz . This step requires ChatGPT to write a verification code using this platform.

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

Example interface

The third step is mainly token analysis, which can also be easily done by robots, and we can get the code through AI. The main inspection scenario for this step will be Twitter, so the robot needs to be assigned the task of using @TweetScout_io , which mainly checks the quality of followers of the token project and whether there are high-quality KOLs among the followers.

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

Example interface

Step 4, the final feature we need to secure, is the creation of a sniping bot. This is also done by making a pull request to ChatGPT, just explain that the token sniping scenario is happening on @dexscreener . Also, be sure to request the addition of slippage, price impact, and trade priority variables so that you can customize these action settings.

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

Example interface

Step 5. After getting the program code, set the variables as follows:

• Slippage = 30%

• Price impact = 30%

• TX Priority = High

These settings can help you snipe highly volatile tokens at a faster speed (of course, it also means greater risk).

Corresponding setting interface

The sixth step is to merge all the codes received from ChatGPT and ask to compile them into a complete robot project. In the end, you will get a token sniping robot that can parse and analyze token projects from Moonshot. In addition, based on the analysis, the robot will also automatically make buying and selling decisions, of course, you can also choose to do it manually. The specific code content can be seen in the tweet here .

(The content of the sample 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[baseTokenl[symbol] == SOL and pair[quoteTokenl

[symbol] == USNT)

return sol usdi air[priceUsd!）

Example interface

Thats all you need to create your Moonshot sniper bot.

This article is sourced from the internet: Using AI robots to snipe Moonshot new coins: Can a novice also become a scientist?

関連: 暗号通貨の世界における新たなコンプライアンスのマイルストーン: イーサリアムスポットETFがついに承認

原文｜Odaily Planet Daily 執筆者：jk 米国現地時間5月23日、米国証券取引委員会（SEC）はすべてのイーサリアムETFを正式に承認し、投資家に従来の金融チャネルを通じてイーサリアムに投資する新たな機会を提供しました。この決定は暗号通貨業界への大きな支持と見られており、スポットビットコインETFに続いてSECに承認された2番目の暗号通貨ETFとなります。ブラックロック、フィデリティ、グレイスケールを含む複数のイーサリアムスポットETFの19のb-4フォームが承認されていますが、ETF発行者は正式に取引を開始する前にS-1登録声明が有効になる必要があることに注意してください。SECは発行者とS-1フォームの議論を始めたばかりであり、複数回の改訂に時間がかかる可能性があります。それは…