LLMQuant

LLMQuant / skills

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Reusable Skills for LLMQuant Agent, Claude Code, Claude.ai, Cursor, Hermes Agent, OpenClaw and Codex, grounded in LLMQuant Data

llmquantdata.comagent agent-skills ai-agents claude-code codex cursor
28
1
80% credibility
Found May 31, 2026 at 28 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

LLMQuant Skills is a library of ready-made financial analysis tools that connect to AI assistants. It offers 18 specialized categories covering equities, options, ETFs, commodities, crypto, macro trends, credit analysis, risk management, and investor strategies. Each skill acts like a knowledgeable finance assistant, routing your questions to the right analytical workflow and ensuring every answer is backed by real market data. Think of it as giving your AI assistant a finance degree.

How It Works

1
💬 Hear about AI that does financial research

You discover that AI assistants can help analyze stocks, options, crypto, and more - with real market data.

2
🔍 Find LLMQuant Skills

You come across a collection of finance-focused tools that plug into your AI assistant to make it smarter about money topics.

3
✨ Install skills with one click

You connect the finance tools to your AI assistant - choosing from stocks, options, crypto, macro trends, risk, and more - all in seconds.

4
Choose your financial topic
📈
Equities

Research stocks, compare companies, analyze valuations

📉
Options

Explore volatility, strategy building, Greeks analysis

₿
Crypto

Monitor token markets, funding rates, leverage

🌍
Macro

Track central banks, yields, FX carry trades

5
💭 Ask your AI assistant

You describe what you want to know - like 'Analyze Apple's latest risks' or 'Show me crypto market regimes' - and the AI uses the right skill to help.

🎯 Get professional-grade insights

Your AI assistant delivers grounded financial analysis with verified data - research memos, risk scores, strategy playbooks, and more.

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AI-Generated Review

What is skills?

LLMQuant Skills is a library of reusable finance-focused prompts that turn AI agents into domain-expert analysts. Instead of crafting prompts from scratch, you get 18 pre-built skill categories covering equities, options, macro, crypto, credit, risk, and more. Each skill routes an agent to the right workflow and enforces that every claim traces back to LLMQuant Data. Install it with a single command: `npx skills add LLMQuant/skills`, and it works across Claude Code, Codex, Cursor, and other agents. The skills describe data needs in plain language, so the agent figures out which LLMQuant Data tools to call.

Why is it gaining traction?

The hook is cross-agent portability. Most prompt libraries lock you into one tool. LLMQuant Skills installs with one CLI command across multiple agent platforms, which is rare. The finance-specific workflows are the other draw. Instead of generic "analyze this stock," you get structured playbooks like five-lens equity analysis, IV rank tracking, or yield curve trade lenses. The data grounding also matters: skills require evidence from LLMQuant Data, so agents don't hallucinate prices or ratios.

Who should use this?

Quantitative analysts building AI-assisted research pipelines. Portfolio managers who want AI agents that can actually discuss positions without making up numbers. Developers integrating AI into trading systems or fintech products. If you're working with financial data and want agents that know the difference between a credit spread and a convertible bond, this saves weeks of prompt engineering.

Verdict

The concept is solid and the cross-agent design is genuinely useful. At 28 stars, this is early-stage and the 0.800000011920929% credibility score reflects that. Documentation is thorough for a small project, but test coverage and community feedback are minimal. Worth watching if you're in quantitative finance, but wait for more traction before betting a production system on it.

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