l3lackcurtains

l3lackcurtains / trading-ops

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📈 Framework-driven trading workspace in Claude Code — one slash command scans stocks, crypto, FX, indices & commodities with structured verdicts and audit trails 🤖

ai algorithmic-trading claude-code crypto forex
14
4
100% credibility
Found May 06, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A lightweight AI-powered workspace for generating structured, framework-based trading analyses on stocks, crypto, indices, FX, and commodities, saving everything as local Markdown files.

How It Works

1
📖 Discover the trading helper

You stumble upon this handy workspace on GitHub that promises simple, structured insights for trading stocks, crypto, or other assets.

2
🛠️ Set it up quickly

You grab a copy and follow the easy steps to prepare it on your computer, including a virtual space for its tools—no fancy subscriptions needed.

3
🚀 Wake up your AI assistant

Open the folder in your AI coding chat, and suddenly slash commands like /scan appear, ready to analyze anything you name.

4
🔍 Run your first market check

Type /scan-macro to get the big-picture market mood, saved neatly as a readable note in your new trading folder.

5
📊 Dive into a specific asset

Command /scan AAPL (or BTC, gold, whatever), and it pulls fresh data to create a clear report with buy/sell/wait advice, price levels, and trade ideas.

6
Grow your watchlist
⭐
Top picks emerge

Spot strong setups marked as 'Top Pick' across timeframes, ready for your trades.

🔄
Stay updated

Rescan daily to see what flipped, building your personal archive of insights.

🏆 Your trading desk thrives

You now have an organized collection of dated analyses, verdicts, and plans—yours to review, versioned, and always improving your decisions.

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Star Growth

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AI-Generated Review

What is trading-ops?

Trading-ops is a framework-driven trading workspace built for Claude Code, where one slash command like `/scan AAPL` or `/scan BTCUSDT` delivers structured verdicts (LONG/SHORT/WAIT/SKIP), ASCII price ladders, and trade tables across stocks, crypto, FX, indices, and commodities. It solves scattered research by producing dated Markdown analyses with audit trails—greppable, version-controlled, and yours—while pre-computing data from free sources like Yahoo Finance and CoinGecko. Python scripts handle the heavy lifting, keeping scans fast and keyless by default.

Why is it gaining traction?

Unlike ad-hoc TradingView notes or pricey platforms, it enforces a data-driven framework with no-prose verdicts, multi-horizon tiers (positional/swing/day), and delta-comparisons on rescans—perfect for repeatable trading ops workflows. Developers hook in broker APIs or TradingView charts via MCP servers without touching the core, and commands like `/discover cheap semis` anchor screens to macro regimes. The lean boundary—research only, execution yours—avoids overreach while enabling 24/7 automation on a VPS.

Who should use this?

Trading ops analysts, engineers, or interns at Citadel-style funds evaluating framework-driven setups; solo traders scanning crypto/commodities/indices for structured audit trails; or Reddit-sourced trading ops specialists building data-driven github workflows without subscriptions. Ideal for those defining "trading ops meaning" through slash commands in Claude Code.

Verdict

Try it if you're in trading ops (salary ~$150k+ entry-level) and want a Claude-native research anchor—docs are solid, setup is npm-simple, but 14 stars and 1.0% credibility signal early maturity, so pair with your own risk checks. Solid prototype for framework-driven scans.

(198 words)

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