Desk Monitoring logo

Desk Monitoring

Organization
galleonlabs
desk-monitoring

How the desk watches markets and the account between trades using Grok Bot routines and WebSocket or polling watches - the desk brief, book checks, funding and price watches, alert conditions and what a watch may and may not do. Use when the user asks for briefings, alerts, "watch X" or scheduled checks.

Overview

Publishergalleonlabs
Repositoryhypergrok-trading-desk
Skill namedesk-monitoring
Stars
145
Forks
31
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by galleonlabs on GitHub. Read the source before you install it.

Installation

Install the Desk Monitoring AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/galleonlabs/hypergrok-trading-desk/tree/main/skills/desk-monitoring
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/galleonlabs/hypergrok-trading-desk.git /tmp/hypergrok-trading-desk
mkdir -p .claude/skills
cp -r /tmp/hypergrok-trading-desk/skills/desk-monitoring .claude/skills/desk-monitoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Desk Monitoring in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Desk Monitoring on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Desk Monitoring is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Monitoring, briefs and watches

Monitoring is read-only. A watch may fetch, compute, save and alert. It may never send to the exchange. If a watch condition implies action ("stop got hit, re-enter"), the alert opens a proposal; the lifecycle does the rest.

Grok Bot routines

Each Bot can own routines (schedules or event triggers). Ask the owning Bot to create one with: schedule and time zone, input source, expected result, approval boundary. Keep routines few and specific; the app keeps only recent run records, so a routine that produces something durable should also write to /workspace/trading-desk.

Recommended starting set (the user picks; none is on by default):

RoutineOwnerScheduleOutput
Desk briefDesk Leadonce a day at the user's chosen timebriefs/YYYY-MM-DD-desk.md and a short post
Book checkRisk Managerevery 4-8 hours while positions are openalert only if something changed or a limit is near
Funding snapshotMarket Analystdaily, or before the user's usual trading timetable of funding, OI, volume for the allowed markets
Catalyst calendar refreshResearch Analystweeklyresearch/calendar.md
Weekly reviewTrade Reviewerweeklyreview posted by DM

The desk brief

Assembled by the Desk Lead from specialists' inputs, or generated by the Desk Lead directly if it is the only Bot awake:

CONCLUSION: The ETH long remains open with a resting stop; HG-20260816-01 is live.
DESK BRIEF | 2026-08-17 07:00 UTC | mainnet | account 0xabc...def
markets (Market Analyst, allMids + metaAndAssetCtxs 06:58 UTC):
  BTC 97,120 (+0.8% 24h) | funding 0.0010%/h | OI $4.1B
  ETH 3,004 (+0.2%) | funding 0.0012%/h | OI $1.2B
  SOL 151.2 (-1.1%) | funding -0.0004%/h | OI $610M
book (Risk Manager, clearinghouseState 06:59 UTC): 1 position, ETH long 0.4827 @ 3,000, uPnL +$1.9, margin ratio 4.6%, stop resting 2,900; open risk 0.5%; day PnL 0.0%
research (Research Analyst): ETH client release scheduled 2026-08-19 [link]; nothing breaking on held markets
open items: HG-20260816-01 live; pending tickets: none

Lead the brief with a plain conclusion about the current book and any required attention, then present these facts with sources. Keep interpretation on one clearly labelled line. Name existing positions and live or pending tickets; do not describe a book with an open position or ticket as having no open items. No trade suggestions.

When to post

A requested update or scheduled report always receives an answer, even when the state is unchanged. For other background checks, save the source, network, UTC check time, accepted and observed data age, result and relevant position or proposal ids under /workspace/trading-desk. Stay quiet only when the check succeeded with fresh, complete data and found no actionable change.

Post changed conditions, failures, stale reads, missing data and gaps with their consequence and next owner or required action. Successful request completion alone is not an all-clear; apply the freshness and completeness checks below before suppressing a message. A quiet run still leaves timestamped evidence and a heartbeat for inspection.

Watches

A watch is a condition plus an alert. Two ways to run one on the desk computer:

  • Polling with /info calls on a short loop from a script under /workspace/trading-desk/watch/ (respect rate limits: /info requests carry weight; a poll every 5-15 seconds per market is plenty for a desk).
  • WebSocket subscriptions (allMids, l2Book, trades, candle, userFills, orderUpdates, userEvents) per hyperliquid-websocket. Better for fills and order updates. Keep the process supervised (a routine can restart it) and log to a file.

Common watch conditions:

WatchDataAlert to
Price crosses a levelallMids or candleuser, Desk Lead
Funding flips sign or exceeds a thresholdmetaAndAssetCtxs funding / predictedFundingsuser, Desk Lead
Order filled or cancelledorderUpdates, userFillsExecution Trader, Trade Reviewer
Margin ratio above X or liquidation distance below YclearinghouseStateuser, Risk Manager, Desk Lead
Position without a resting stopclearinghouseState + frontendOpenOrdersRisk Manager, Desk Lead (incident)
Daily loss stop approached (80%) or hitclearinghouseState vs start-of-day equityuser, Risk Manager
Exchange unreachable for more than N minutesany /info call failingDesk Lead

An alert message carries: what fired, the value and the threshold, the source and UTC time, and the proposal id if related. Alerts do not include instructions to trade.

Silence is not an all-clear. A watch has three outcomes, never two: the condition fired, the condition did not fire, or the watch could not tell. A failed request, an empty response, a socket that reconnected and skipped messages, a candle that never closed, or data older than the watch's own interval is unavailable, and it must alert as such. A watch that quietly reports "not crossed" on a dead feed is the most dangerous thing on the desk, because it looks exactly like a calm market.

Give every watch a staleness bound (a small multiple of its interval) and check the age of each result against it. On unavailable: say which read failed, how old the last good value was, and how long the gap has run. Escalate a gap that outlives the bound, rather than waiting for the feed to come back.

Hygiene

  • Every watch script logs to /workspace/trading-desk/watch/<name>.log with UTC timestamps.
  • A watch that fails silently is worse than none: routines that own a watch check its heartbeat.
  • Do not run more than a few watches at once; each is a process on the shared computer.
  • When the desk goes flat and the user is done for the day, stop the watches that only make sense with positions.

Never

  • Never let a watch place, modify or cancel an order, or change leverage. Even a "protective" one. It alerts; the desk acts through a ticket.
  • Never alert with unsourced numbers.
  • Never report a stale or failed read as a condition that did not fire. That is an unavailable alert, not silence.
  • Never poll faster than the desk needs; a rate-limited desk is a blind desk.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Desk Monitoring AI skill do?

How the desk watches markets and the account between trades using Grok Bot routines and WebSocket or polling watches - the desk brief, book checks, funding and price watches, alert conditions and what a watch may and may not do. Use when the user asks for briefings, alerts, "watch X" or scheduled checks.

Why use Desk Monitoring on TypingMind?

Because you install it once and use it with any model. Desk Monitoring is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Desk Monitoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/galleonlabs/hypergrok-trading-desk/tree/main/skills/desk-monitoring. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Desk Monitoring?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Desk Monitoring?

As many as you like. As long as a model supports skills, you can use Desk Monitoring with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Desk Monitoring AI skill free?

Yes. It is published on GitHub by galleonlabs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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