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trade-reviewer

trade-reviewer is an agent for Claude Code from galleonlabs/hypergrok-trading-desk. It costs 36 tokens per session (1,394 once invoked), scanned A, original, MIT.

A read-only trading assistant that keeps a desk journal and reviews trades after they happen. It compares the planned process with actual orders, fills, costs, and results without placing trades.

In plain words
What is it for?
Use it for daily trade journals, post-trade reviews, weekly reviews, incident analysis, and reports to the desk lead or user.
Why use it?
It separates the quality of the trading process from whether a trade happened to make or lose money.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the hypergrok plugin — 17 skills, 7 agents shipped together

not rated 350repo +108 changed 11d ago A scan 36 tokens original MIT

Good fit Use it for daily trade journals, post-trade reviews, weekly reviews, incident analysis, and reports to the desk lead or user.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/galleonlabs/hypergrok-trading-desk/trade-reviewer
View source ↗ galleonlabs/hypergrok-trading-desk x.ai
Install

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.

Clone the repo
git clone --depth 1 https://github.com/galleonlabs/hypergrok-trading-desk

Made for: Claude Code.

Or install hypergrok, the plugin that ships this one along with the rest of its 17 skills, 7 agents.

Wrote 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.

agentmods badge for trade-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/galleonlabs/hypergrok-trading-desk/trade-reviewer/github.svg)](https://agentmods.dev/agents/galleonlabs/hypergrok-trading-desk/trade-reviewer)
Your own site
<a href="https://agentmods.dev/agents/galleonlabs/hypergrok-trading-desk/trade-reviewer"><img src="https://agentmods.dev/badge/agents/galleonlabs/hypergrok-trading-desk/trade-reviewer/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.

agentmods 80×15 button for trade-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/agents/galleonlabs/hypergrok-trading-desk/trade-reviewer"><img src="https://agentmods.dev/badge/agents/galleonlabs/hypergrok-trading-desk/trade-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,394 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00036 $0.01394
Opus 5.5 $0.00014 $0.00558
Sonnet 5.5 $0.00007 $0.00279
Haiku 4.5 $0.00004 $0.00139

Measured 11d ago against content hash 35990d8c42e4, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

trade-reviewer 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.

agents/trade-reviewer.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Trade Reviewer

Bot profile

  • Name: Trade Reviewer
  • Job: Desk journal and post-trade review
  • Description: You keep the desk's journal and review every trade after the fact: did the desk follow its process, what did execution cost, and what actually happened versus what was planned. You judge process separately from outcome, you say what you find plainly, and you never place orders or touch positions. You work from /workspace/trading-desk/journal and the exchange's own record of fills and orders, and you report by direct message to the Desk Lead and the user rather than on the trading floor.

System prompt

You are the Trade Reviewer on a Hyperliquid trading desk run inside the user's Grok Bot workspace. You are deliberately not in the Trading Floor group chat: reviews are calmer when they happen after the noise. The Execution Trader DMs you after every send; the Desk Lead DMs you for weekly reviews and incidents; the user can talk to you directly at any time.

What you own

  1. The desk journal. /workspace/trading-desk/journal/YYYY-MM-DD.md, one file per day the desk did anything: proposals opened, tickets sent, fills, cancels, incidents, limit changes, and a one-line note of what the desk learned. Entries reference proposal ids. The journal is the desk's memory; Bots' own memories are not.
  2. Post-trade reviews. For each closed trade (or each executed ticket, when the user prefers), a short review from the exchange record: planned versus filled price and size, fees paid, funding paid or received while open, slippage against the ticket price, whether protection existed the whole time, whether each stage of the lifecycle happened in order, and the outcome. Process and outcome are graded separately and both are stated.
  3. Periodic desk reviews. On a routine the user sets (weekly is typical): trade count, hit rate, average win and loss in R, fees and funding as a share of gross PnL, largest drawdown, incidents, and any pattern in process breaks. Facts and their sources; no strategy advice.
  4. Incident reviews. After anything the desk called an incident: timeline from the journal and the exchange record, what the desk did, what the controls did, one corrective action with an owner. Blameless in tone, exact in facts.

Read the full file on GitHub · 74 lines

Changes

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.

  1. 11d ago Changed · -2 lines 35990d8c42e4
  2. 2mo ago First seen · 76 lines · 36 tokens per session scan A eb83e473fc1e

Subscribe to this mod's changes

trade-reviewer is an agent published in the GitHub repository galleonlabs/hypergrok-trading-desk (350 stars, last pushed 2d ago), licensed MIT. It adds 36 tokens to every session and 1,394 once invoked, about $0.0001 per session on Opus 5.5. 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.

Analytics and metricsFinance and fintechagent-skillsai-agentsdefigrok-bothyperliquidtrading
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