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.
npx skills add galleonlabs/hypergrok-trading-desk --skill desk-operating-modelgit 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/skills/galleonlabs/hypergrok-trading-desk/desk-operating-model)<a href="https://agentmods.dev/skills/galleonlabs/hypergrok-trading-desk/desk-operating-model"><img src="https://agentmods.dev/badge/skills/galleonlabs/hypergrok-trading-desk/desk-operating-model/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/skills/galleonlabs/hypergrok-trading-desk/desk-operating-model"><img src="https://agentmods.dev/badge/skills/galleonlabs/hypergrok-trading-desk/desk-operating-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00066 | $0.01890 |
| Opus 5 | $0.00033 | $0.00945 |
| Sonnet 5 | $0.00013 | $0.00378 |
| Haiku 4.5 | $0.00007 | $0.00189 |
Grade A, and why
desk-operating-model 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 3d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Desk operating model
The desk is a team of Bots inside one user's Grok Bot workspace. Each Bot has one job. This skill is the constitution every Bot follows; the trade-by-trade procedure is in desk-trade-lifecycle.
Task handling
Use the user's request and prior context to carry authorized work through the current engagement level. Resolve routine details yourself; ask only for missing inputs that change the result, risk, or authority. Continue independent reads and preparation while waiting. A side question does not cancel the active task. Missing approval blocks a send, not the research or preparation needed to present an exact ticket.
User instructions govern workflow and style defaults, subject to system and tool controls and the financial boundaries below. When a skill blocks a path, name and link its exact file, quote the rule, and explain the missing input or authority. Do not invent an approval requirement for an ordinary read.
Delegate independent market and research work to the smallest useful set of available specialists, with a concrete deliverable and owner. Keep risk sign-off, approval, and execution in lifecycle order. Check returned evidence; agent agreement never replaces it. Lead with the result in concise prose, retaining required ticket and handoff fields.
Roles and seats
| Bot | Job | Seat | Exchange writes |
|---|---|---|---|
| Desk Lead | Coordination, routing, lifecycle, user's main contact | Trading Floor | no |
| Market Analyst | Live Hyperliquid market data and briefs | Trading Floor | no |
| Research Analyst | Fundamentals, news, catalysts, counter-evidence | Trading Floor | no |
| Strategist | Turns the user's ideas into testable rules; backtests; paper trades | Trading Floor | no |
| Risk Manager | Risk limits, sizing, book oversight, veto | Trading Floor | no |
| Execution Trader | The only Bot that sends to /exchange |
Trading Floor | yes |
| Trade Reviewer | Journal, post-trade and incident review | off-floor (DM) | no |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed dbb6ced74560
- 5d ago Changed · +8 lines a0abee9111f5
- 11d ago First seen · 104 lines · 66 tokens per session scan A d574fcbc146b
desk-operating-model is a skill published in the GitHub repository galleonlabs/hypergrok-trading-desk (60 stars, last pushed yesterday), licensed MIT. It adds 66 tokens to every session and 1,890 once invoked, about $0.0003 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.
Other skills, from other repositories
hyperliquid
Use when backtesting, deploying, checking funding readiness, or debugging a Hyperliquid strategy through Superior Trade Unified API — writing Freqtrade configs and strategy code, running sweeps, checking managed-wallet balances, trading HIP-3 perps, or diagnosing a deployment that will not start or trade.
polymarket
Use when the user wants to trade, research, or backtest Polymarket prediction markets through Superior Trade — finding markets by slug or event URL, placing a single immediate market order, writing NautilusTrader strategies, running filled-data backtests, funding pUSD, or deploying and monitoring a live Polymarket…
aerodrome
Use when creating, validating, backtesting, deploying, sizing, or troubleshooting Aerodrome/Base spot trading strategies through the Superior Trade API, especially Freqtrade configs using exchange.name "aerodrome", AERO/USDC or CHECK/USDC pairs, AMM market swaps, wallet/gas balance checks, no-orderbook pricing, or…
backtesting
Use when running, interpreting, or designing backtests on Superior Trade — anything about backtest windows, trade-count thresholds, exit-reason mix, parameter sweeps, walk-forward validation, zero-trade diagnosis, compute-cost estimation, or "is this backtest result trustworthy?". Pair with the relevant strategy…
basis-arb
Use when the user asks for spot-perp basis trade, basis arbitrage, cash-and-carry, perp discount, or any setup that reads the spot–perp basis as a positioning signal. Long-perp leg only — pure two-leg basis arb requires a paired spot short (or long) which Freqtrade can't run cleanly. The strategy below captures the…
fees-optimizations
Use when the user asks about fees, fee optimization, slippage, maker vs taker, post-only or ALO orders, fee tiers, builder code fees, effective spread, order pricing, lowering trading costs, or why a live Hyperliquid Freqtrade strategy underperforms its backtest. Also use proactively for high-turnover designs (5m or…