What you can do with Noraz Agent

4 use cases

• Get screened Robinhood Chain signal cards on chat

  Run five screening agents that post only 80%+ confidence call cards to Discord and Telegram.

  • Noraz Agent
  • Money
  • Intermediate
  View prompt

  Using the noraz-agent repo, set up the bot with DRY_RUN enabled and start it in development mode. Expected output: the bot runs and posts at least one call card or a status message to the configured Discord or Telegram channel. Verify that DRY_RUN is still true in the .env file before reporting success.

  Share Save

• Audit a Robinhood Chain token before buying

  Run a token audit from the terminal or Discord to check security before any trade decision.

  • Noraz Agent
  • Money
  • Intermediate
  View prompt

  Using the noraz-agent repo, run a live token audit on <token-address> through the Terminal TUI or the #audit-on-demand channel. Expected output: an audit summary that includes the GMGN and GoPlus security results. Verify that the audit result is shown before any buy or swap action is taken.

  Share Save

• Run the agent 24/7 on a VPS with health checks

  Deploy the PM2 daemon, check diagnostics, and update the agent on a Linux server.

  • Noraz Agent
  • Money
  • Advanced
  View prompt

  Using the noraz-agent repo on a Linux VPS, run `noraz deploy` and then `noraz doctor`. Expected output: PM2 shows noraz-agent as online and the doctor report lists no failed checks. Verify the result with `npx pm2 status` before reporting success.

  Share Save

• Write screening rules in plain English

  Describe the signals you want in one sentence and let the agent compile them into a strategy.

  • Noraz Agent
  • Money
  • Intermediate
  View prompt

  Using the noraz-agent repo, set a Custom Prompt strategy describing <your-screening-rule> and start the bot with `noraz run`. Expected output: a compiled strategy file or a logged fallback to the safe default. Verify that the 80% confidence gate and security gates are still listed as mandatory before reporting the setup as complete.

  Share Save

How to use Noraz Agent

1. Check you have what it needs: Node.js and npm installed; Git installed to clone the repository; API keys and chat credentials for the onboarding wizard (for example Discord or Telegram setup).
2. Open mogons/noraz-agent on GitHub and read the README and license.
3. Run git clone https://github.com/runesatsdev/noraz-agent.git and then cd noraz-agent (the README clone URL differs from the repository URL given, so confirm the source first).
4. Run bash setup.sh on Linux or macOS, or .\setup.bat on Windows.
5. Run npm run wizard (or noraz onboard) and set your API keys, AI models, and TP/SL values.
6. Run npm run dev (or noraz run) to start the live bot.

These steps come from our top use case, Get screened Robinhood Chain signal cards on chat, which also has a copy-paste agent prompt.

Noraz Agent alternatives · Best AI repos for Money

About this repo

• Who it is forCrypto traders and developers on Robinhood Chain who want screened signal cards and on-demand token audits, with execution kept under manual control.
• Why it is hot
• LanguageTypeScript
• Sourcegithub.com/mogons/noraz-agent · Back to Hot repos

Requirements

• Node.js and npm installed
• Git installed to clone the repository
• API keys and chat credentials for the onboarding wizard (for example Discord or Telegram setup)
• Familiarity with a terminal on Windows, Linux, or macOS

Related repos

• Trended earlier Finathink Finathink is a local-first Python workbench that turns user data, evidence, factors, backtests, risk checks and paper portfolios into a traceable research record with offline HTML reports.
• Trended earlier Northcinder NorthCinder is an open-source MCP server that compares products from stores you choose, explains its ranking, and asks for your approval before any purchase.
• Trended earlier Qanat Qanat is a Python data platform for investment research that screens companies on the numbers they had published as of any past date and serves that data to AI agents over MCP.