Real-time institutional-grade trading intelligence for US Stocks and Options powered by squeeze detection, insider intel, and macro analysis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install alpha-quant-intelligence
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install alpha-quant-intelligence using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Alpha Quant Intelligence?
Alpha Quant Intelligence brings institutional-grade trading intelligence directly to retail traders and automated agent workflows. Originally derived from Shubh's Alpha Quant Bot, which manages over $2k in paper trading, this advanced intelligence skill generates high-confidence trading signals for US Stocks and Options. By analyzing squeeze detection, insider intelligence, and macro-economic factors, it enables AI agents to deliver highly actionable market insights directly within your terminal and development environment.
As one of the specialized Openclaw Skills, Alpha Quant Intelligence bridges the gap between sophisticated financial modeling and programmatic execution. It helps developers, quantitative enthusiasts, and automated agents query market opportunities, backtested to achieve a 65%+ win rate across top sectors like Technology, Semiconductors, and Clean Energy.
Alpha Quant Intelligence Use Cases
- Automated daily trading signal generation to discover the top alpha pick of the day.
- Real-time ticker analysis for US Stocks and Options to identify high-confidence squeeze and insider intelligence indicators.
- Programmatic integration of institutional-grade financial signals into AI-driven trading systems and automated portfolios.
How Alpha Quant Intelligence Works
- The AI agent or user triggers the script to fetch institutional-grade signals or the top daily alpha pick.
- The underlying analytical engine processes market data, tracking squeeze indicators, insider transactions, and macro trends.
- High-confidence trading signals are formatted and returned to the terminal or agent workspace.
- Developers can integrate the signal stream programmatically into larger automated portfolios via the x402 API.
Alpha Quant Intelligence Setup
To get started with Alpha Quant Intelligence, clone or download the skill repository and configure your environment.
# Install the required dependencies and command-line tool
pip install -r requirements.txt
# Run the command to fetch the daily top pick
python alpha_quant.py daily-top
# Query a specific stock ticker for active trading signals
python alpha_quant.py signal --ticker AAPL
Ensure that you have access to the necessary API keys if utilizing the x402 programmatic signal stream.
Alpha Quant Intelligence Data Schema & Taxonomy
Alpha Quant Intelligence structures its analytical output into highly readable and structured schema formats. Below is a representation of the signal and pick data schemas.
Query Output Schema
| Field | Type | Description |
|---|---|---|
ticker |
String | The US Stock or Option symbol (e.g., AAPL, TSLA) |
signal_type |
String | Buy, Sell, Hold, or Squeeze Alert |
confidence |
Float | Confidence interval of the signal (0.00 to 1.00) |
derived_from |
String | Underlying analysis factor (e.g., macro, insider, squeeze) |
timestamp |
String | ISO 8601 timestamp of signal generation |
CLI Commands
alpha_quant.py signal --ticker <TICKER>: Fetches specific real-time trading metrics.alpha_quant.py daily-top: Outputs the current #1 daily alpha pick.
Alpha Quant Intelligence Advanced Features
- Programmatic x402 API access allowing direct integration of the signal stream into external automated trading systems.
- Squeeze detection algorithms combined with macro analysis to filter out low-probability market noise.
- Automated tracking of insider transactions to add high-conviction fundamental context to technical triggers.
- Tailored support for high-momentum sectors such as Tech, Semiconductors, and Clean Energy.
SKILL.md
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