YizhiSong

FriesTrader — AI skill for Claude Code

AI community

Robinhood Agentic Trading agent — a fully automated AI trading bot placing real orders through Robinhood's Agentic Trading MCP, under mechanical, auditable risk rules the model cannot override.

How to install FriesTrader

This entry records only its repository, not the path inside it, so there is no exact command to give. Open YizhiSong/FriesTrader and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What FriesTrader does

Robinhood Agentic Trading agent — a fully automated AI trading bot placing real orders through Robinhood's Agentic Trading MCP, under mechanical, auditable risk rules the model cannot override. Able to run unattended on Claude Pro, no metered API spend. Not financial advice.

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README

FriesTrader

![License](https://img.shields.io/github/license/YizhiSong/FriesTrader) ![GitHub stars](https://img.shields.io/github/stars/YizhiSong/FriesTrader)

An AI trading agent built to run cheap and fully on its own, trading real orders on [Robinhood](https://robinhood.com) using its [Agentic Trading MCP server](https://robinhood.com/us/en/agentic-trading/). Once set up, it's able to run unattended on its own schedule every weekday, no manual triggering needed, and the actual safety mechanism is mechanical, auditable risk rules, not the model's judgment. Two short scheduled Claude Code sessions a day screen stocks, write out their reasoning, and (only under a narrow, explicit gate) place real trades, without a team of specialized sub-agents burning tokens on every decision. Because it's just two lean sessions instead of a multi-agent pipeline, it runs comfortably on a Claude Pro subscription (as low as $200/year on the annual plan), no Claude Max or metered API spend required.

This is a template/framework extracted from a real, live deployment. Adapt it, don't just run it blind — read "What this does and doesn't solve" below before pointing it at real money.

If you build on this, a star, a fork, or a link back to this repo is always appreciated.

Why this is safer than it sounds

"Fully autonomous" and "trading real money" together should make you nervous. Here's what actually stands between a thesis and an order:

  • Every trade passes through mechanical rules the LLM cannot override — position sizing, stop-loss, take-profit, loss limits, a wash-sale guard, each computed by a small stdlib-only Python script in scripts/ rather than the model doing arithmetic in prose. Same inputs always produce the same numbers, and a good story never cancels a stop-loss.
  • New deployments start in dry_run and stay there for a minimum number of cycles (dry_run_min_cycles_before_live) before a live order is even possible, so you can watch it