by galleonlabs
Turn your Grok Bot into a 7-agent Hyperliquid trading desk. Roles, system prompts and skills your Bots use to research, size, execute and review.
# Add to your Claude Code skills
git clone https://github.com/galleonlabs/hypergrok-trading-deskGuides for using ai agents skills like hypergrok-trading-desk.
hypergrok-trading-desk is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by galleonlabs. Turn your Grok Bot into a 7-agent Hyperliquid trading desk. Roles, system prompts and skills your Bots use to research, size, execute and review. It has 50 GitHub stars.
hypergrok-trading-desk's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/galleonlabs/hypergrok-trading-desk" and add it to your Claude Code skills directory (see the Installation section above).
hypergrok-trading-desk is primarily written in Python. It is open-source under galleonlabs on GitHub, so you can review or fork the full source.
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Add the public Desk Lead to Grok Bot. It opens with a live, zero-key Hyperliquid market snapshot, builds research, risk, execution and review as separate agents, then proves the floor is ready. They brief you on markets, size your trades, send what you approve and tell you honestly how it went. You bring the ideas. Let them cook.
Click Add to Grok Bot, then send HyperGrok Desk Lead one message:
Start the desk.
That is the supported one-click, one-message install. The public template carries all seventeen reviewed skills as version-pinned pointers, with no memories, routines or plugins.
If the public template is unavailable, open Grok Bot and paste this to any Bot:
Set up the HyperGrok trading desk from https://github.com/galleonlabs/hypergrok-trading-desk/blob/v1.4.0/skills/hypergrok-bootstrap/SKILL.md. Follow the bootstrap skill, use https://github.com/galleonlabs/hypergrok-trading-desk/blob/v1.4.0/SETUP.md for the complete runbook, and finish with its evidence receipt.
The desk starts in research mode. The first demo uses only Hyperliquid's public /info endpoint: no wallet, account read or order. Add a testnet API wallet when you want to practise with play money, and a mainnet one when you are ready.
The first thing the Desk Lead shows is useful, live output—not a configuration form:
python3 scripts/opening_bell.py --coin ETH
It reports source and UTC time, mid/mark/oracle, 24-hour change and volume, hourly funding, open interest, spread and depth at 5/10/25 bps. Twenty book levels stop a few bps from the mid on a liquid perp, so it re-reads the book at a coarser nSigFigs page until each band is measured, names the page every figure came from, and still marks a band no page reaches as a floor rather than a total. scripts/desk_doctor.py then checks the release, team files, desk folders and public connectivity. Both are read-only and standard-library Python.
| Bot | What they do for you |
|---|---|
| Desk Lead | Your main contact. Runs the floor, keeps every trade moving through the same clean process. |
| Market Analyst | Live Hyperliquid data on demand: price, depth, funding, open interest, candles. Timestamped and sourced. |
| Research Analyst | What is happening and what is scheduled: fundamentals, news, catalysts, onchain and social context. |
| Strategist | Turns your idea into explicit rules, backtests it honestly on Hyperliquid history, paper-trades it on testnet. |
| Risk Manager | Keeps your written limits, sizes every trade from your live account, watches the book, and can say no. |
| Execution Trader | The one Bot with the keys. Sends the ticket you approved, once, and reconciles it from the exchange record. |
| Trade Reviewer | Keeps the desk journal and grades every trade on process and outcome, separately. |
Six sit together on the Trading Floor group chat; the Trade Reviewer works by DM. Every trade follows the same path:
idea -> evidence -> risk sign-off -> your approval -> one send -> reconciliation -> review
"Brief me on ETH." The Market Analyst pulls mid, mark, funding, open interest, 24h volume and depth at 5/10/25 bps from the exchange, and posts a brief with sources and UTC times.
"I want to long ETH at 3,000 with a stop at 2,900." The Desk Lead opens HG-20260816-01, the Risk Manager reads your account live and comes back with a ticket:
TICKET HG-20260816-01 | mainnet
market ETH-PERP side buy size 0.4827 ETH (~$1,448)
entry limit 3,000 Gtc stop sell 0.4827 @ 2,900 market (sent with the entry)
risk $51.00 = 0.5% of equity $10,200 (clearinghouseState 14:11 UTC) R = 100
sized on a stressed stop: 100 + 3.00 slippage + 2.65 fees = 105.65 per ETH
approve with: "approve HG-20260816-01"
You type approve HG-20260816-01. The Execution Trader sends entry and stop in one grouped order, reads the exchange response, confirms it on the book, and reports the order ids. When it closes, the Trade Reviewer tells you what it cost, whether the process was clean, and one thing worth keeping.
"Can we test whether funding extremes mean-revert?" The Strategist writes the rules with you, pulls a year of candles and funding, runs a backtest with fees and an out-of-sample split, and reports the trade distribution, not a headline number. Like it? Paper-trade it on testnet through the same desk.
"Watch ETH and tell me if funding flips negative." A routine on the desk computer watches the WebSocket feed and pings you when it happens.
Seventeen skills, in the portable SKILL.md format, shared by all your Bots.
Bootstrap - pinned release install, Opening Bell, team construction, desk doctor and a receipt that distinguishes what happened from what still needs a manual step.
Hyperliquid - setup and API wallets, market data, account state, orders (limit, IOC, take-profit and stop-loss with grouping, client order ids), positions and margin, WebSocket feeds, advanced actions (dead-man's switch, TWAP, spot), and a compact API reference. Copy-pasteable curl for reads; the official Python SDK and @nktkas/hyperliquid for anything that signs.
Desk - how the team works: operating model, the trade lifecycle and ticket, risk limits and sizing arithmetic, the execution protocol, monitoring and routines, post-trade review, incident playbooks, and the strategy lab.
Perpetual futures can liquidate an account. HyperGrok is documentation and instructions, not financial advice.
The same agents/, skills/ and rules/ load as a plugin: seventeen skills, and the seven roles as subagents.
In Claude Code, install it from this repository:
/plugin marketplace add galleonlabs/hypergrok-trading-desk
/plugin install hypergrok@hypergrok
In Grok Build and Cursor, open the repository and enable the plugin.
The same pack installs as a skill:
npm exec --package=skills@1.5.23 -- skills add galleonlabs/hypergrok-trading-desk
Live listings: skills.sh · cursor.directory · botdirectory.ai
Either way, run /desk-operating-model to begin.
SETUP.md what your Grok Bot follows to build the desk
agents/ seven roles: Bot profile card + full system prompt
skills/ seventeen skills (bootstrap, hyperliquid-*, desk-*)
template/ exact public Grok Bot profile and skill hashes
scripts/ zero-key Opening Bell, desk doctor and release checks
docs/ how it works, FAQ, provenance
assets/ the mascot - use it as your Bots' avatar
| Doc | |
|---|---|
| How the desk works | roles, files, trust boundaries |
| FAQ | keys, approvals, testnet, customising the team |
| Skills index | every skill and who uses it |
| Grok Bot template | public profile, publish contract and clean-install evaluation |
| Provenance | sources and licences |
| Contributing · Security · Changelog |
MIT. Built by Galleon Labs.