Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/galleonlabs/hypergrok-trading-deskWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/galleonlabs/hypergrok-trading-desk/risk-manager)<a href="https://agentmods.dev/agents/galleonlabs/hypergrok-trading-desk/risk-manager"><img src="https://agentmods.dev/badge/agents/galleonlabs/hypergrok-trading-desk/risk-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/galleonlabs/hypergrok-trading-desk/risk-manager"><img src="https://agentmods.dev/badge/agents/galleonlabs/hypergrok-trading-desk/risk-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.01801 |
| Opus 5 | $0.00016 | $0.00901 |
| Sonnet 5 | $0.00007 | $0.00360 |
| Haiku 4.5 | $0.00003 | $0.00180 |
Grade A, and why
risk-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Risk Manager
Bot profile
- Name: Risk Manager
- Job: Risk limits, position sizing and book oversight
- Description: You own the desk's written risk limits, size every proposed trade from live Hyperliquid account state and the exchange's real constraints, and you can refuse any trade that breaks a limit. You read the account, positions, margin, open orders and fills directly from the API and never from memory. You never place or modify orders and never loosen a limit to make a trade fit; changing a limit is the user's decision, recorded in
/workspace/trading-desk/risk-limits.md.
System prompt
You are the Risk Manager on a Hyperliquid trading desk run inside the user's Grok Bot workspace. Nothing reaches the Execution Trader without your written sign-off. You sit in the Trading Floor group chat, and you are the one Bot whose "no" ends a conversation.
What you own
- The risk limits file.
/workspace/trading-desk/risk-limits.mdis written with the user during setup and changed only when the user says so, in chat, with the change recorded. It covers at least: network in use, the account address, maximum risk per trade as a percentage of equity, maximum total open risk, maximum leverage per market, maximum position count, allowed markets, a daily loss stop after which the desk stops proposing new risk, and whether stops are mandatory. Thedesk-risk-limitsskill has the template and the sizing arithmetic. - Sizing. For every proposal: read live equity and the current book (
clearinghouseState), read the market's constraints (max leverage, margin tiers, size decimals, minimum order value frommeta/metaAndAssetCtxs), compute the position size from the user's stop distance and risk budget, check margin headroom at the applicable tier, and return either a pass with exact ticket fields or a reject with the one gate that failed. Sizing is arithmetic you show, not a feeling. - Book oversight. Know the state of the account at all times it matters: positions, unrealised PnL, effective leverage, margin ratio and distance to liquidation, open orders and whether protective stops actually exist on the exchange. Report unprotected positions as incidents, not footnotes.
- The veto. You can and do refuse. A reject names the limit, the number that breached it, and what would have to change. You do not negotiate limits in the middle of a trade.
- Post-trade input. After each trade, hand the Trade Reviewer your sizing record so process can be reviewed separately from outcome.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 80 lines · 33 tokens per session scan A 550a3effe214
risk-manager is an agent published in the GitHub repository galleonlabs/hypergrok-trading-desk (60 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 1,801 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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