Develop X Bot for Trustworthiness Analysis | 300 USDC + EXCLUSIVE MERCH

About Project RUGGUARD

Project RUGGUARD is dedicated to building tools that help users assess the trustworthiness of token projects on the Solana Network. Our goal is to foster a more transparent and reliable online environment by providing users with clearer insights into the accounts they interact with. We are launching this bounty to develop an innovative X bot that analyzes account information upon request.

Mission

Develop an X (formerly Twitter) bot that, when triggered by the phrase “@projectruggaurd riddle me this" in a reply, analyses the original tweet's author and posts a trustworthiness report about that author.

Contact me for personal review of Projects before submission:
TG: devsyrem

Advice: DO NOT ADD WINGS AND A JET ENGINE TO A CAR!!!!!!!!! Try and not overcomplicate the project and stick to the scope detail below!

Scope Detail

The bot must perform the following key functions:

The entire bot should have be able to be deployable on a Virtual Machine by Replit.com

• Trigger Listener:

  • Monitor replies under tweets across X (or optionally, only under a specified account like @projectrugguard).

  • If a reply includes the exact phrase "riddle me this", the bot must:

    • Identify the tweet being replied to.

    • Extract the user ID of that tweet's original author.

    • Initiate analysis for the original author, not the user who posted the "riddle me this" comment.

    • Free X Developer Account Signup: https://developer.x.com/en/portal/petition/essential/basic-info

    • Developer Docs: https://docs.x.com/x-api/fundamentals/data-dictionary#tweet
      PLEASE DO NOT SELL YOUR LEFT KIDNEY TO BUY API CREDITS FOR 1 MONTH, YOU CAN GET A FREE ACCOUNT WITH SUFFICIENT CREDIT!!!! Please message me if yu can’t find the button

• Account Analysis:

  • Gather and analyze data for the identified original author, including but not limited to:

    • Account age.

    • Follower/following ratio.

    • Bio content (keywords, length).

    • Engagement patterns (e.g., average likes/retweets, reply frequency).

    • Content of recent tweets (e.g., sentiment, topics).

    • Backed By Network of Followers

• Trusted Account Cross-Check:

  • Implement logic (conceptually similar to a trusted_accounts.py module) to check if the target user is followed by at least three accounts from a predefined list of trusted users.

  • If accounts being analysed are being followed by at least 2 of these accounts, thats a positive indication that the project/individual is reliable

  • List to Trusted Accounts: https://github.com/devsyrem/turst-list/blob/main/list (The trust list needs to be in this layout in order to be updated accordingly).

• Reply System:

  • Post a reply to the triggering "riddle me this" comment.

  • This reply should contain a concise summary of the trustworthiness analysis for the original tweet's author.

Submission Requirements

• A link to a public GitHub repository containing the full, well-documented source code.

• A comprehensive README.md file that includes:

  • Clear setup and installation instructions, including API key configuration.

  • Step-by-step guidance on how to run the bot.

  • An overview of the bot's architecture and key modules.

• The bot must be easily deployable and runnable on Replit (e.g., include a requirements.txt file).

• All submitted code must be original or use open-source libraries with proper attribution.

• The final submission must be scored at 100 points in order to be considered for prizes.

• The submission, including all documentation, must be in English.

Judging Criteria

Submissions will be evaluated based on the following criteria (100 points total):

• Functionality (50 points):

  • Bot successfully scans replies under tweets (across X or a specified account) (5 pts)

  • Correctly and reliably detects the "riddle me this" trigger phrase in comments (5 pts)

  • Accurately extracts the user ID of the original tweet's author (the one being replied to) (10 pts)

  • Performs analysis on the correct user (original poster, not the commenter) (10 pts)

  • Posts a coherent, accurate, and informative trust report as a reply to the triggering comment (10 pts)

  • Followers on the list are automatically vouched by the bot and accounts that are followed by at least 3 individuals/projects on the trust list are vouched. (10 pts)

• Code Quality (20 points):

  • Code is clean, well-commented, maintainable, and follows best practices.

  • Efficient use of resources and Twitter API calls.

• Modularity (20 points):

  • The codebase exhibits a well-structured and modular design, with logical separation of concerns (e.g., trigger listening, account analysis, reply generation).

• Replit Readiness (10 points):

  • The bot is easy to configure and run on Replit Virtual Machine

  • All dependencies are clearly listed and managed.

Reward Structure

• 1st Place: 300 USDC + Exclusive Merch

• 2nd - 5th: Exclusive Merch