openclaw-options

Execute the OpenClaw Wheel strategy for selling cash-secured Puts on a 20-ticker universe.

2|1|Updated Apr 25, 2026

Search Tags:#risk management #options trading #OpenClaw #strategy execution #portfolio margin

Ready to run

npx skills add https://github.com/tongzhouliu-sys/awesome-claude-skills --skill openclaw-options

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: openclaw-options
Source: https://github.com/tongzhouliu-sys/awesome-claude-skills/tree/main/openclaw-options
Command: npx skills add https://github.com/tongzhouliu-sys/awesome-claude-skills --skill openclaw-options

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, pdf2image, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The openclaw-options skill solves the complex problem of executing the OpenClaw Wheel strategy, offering a disciplined framework for selling cash-secured Puts on a curated 20-ticker universe.

Core Features & Use Cases

Strategy Execution: Implements the OpenClaw Wheel strategy for selling cash-secured Puts.
Pre-screen Logic: Includes pre-screen Gate logic for data source hierarchy and degradation rules.
Signal Classification: Classifies signals based on scan output, selecting short Put targets and position sizing.
Greeks Awareness: Uses Greeks for risk management, ensuring decisions align with portfolio margin account characteristics.
Use Case: Ideal for institutional-grade AI systems to handle complex, multi-jurisdictional scenarios in options trading.

Quick Start

To execute the OpenClaw Wheel strategy, first run the scan script with the desired scope: python openclaw_scan.py --scope <scope>. Then, use the skill to analyze the results and generate signals.

Frequently Asked Questions about openclaw-options

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I execute the OpenClaw Wheel strategy for selling cash-secured puts?▼

To execute the OpenClaw Wheel strategy, run the scan script with a defined scope using `python openclaw_scan.py --scope <scope>`, then analyze the output to classify signals and generate short put targets.

What pre-screen gate logic is needed for options trading signal generation?▼

Options trading signal generation requires pre-screen gate logic to establish data source hierarchy and degradation rules. This ensures data integrity before classifying signals for short put targets and position sizing.

Does this options trading skill support portfolio margin risk management?▼

Yes, it supports portfolio margin risk management by using Greeks to ensure trading decisions align with portfolio margin account characteristics during signal classification and position sizing.

What data sources do I need to run the OpenClaw Wheel strategy scan?▼

Running the OpenClaw Wheel strategy scan requires data sources and parameters specifically defined in the 'data-system.md' and 'tickers-20pool.md' reference files to execute the curated 20-ticker universe screening.

How does signal classification work for a 20-ticker universe in options trading?▼

Signal classification for a 20-ticker universe works by processing scan outputs to select short put targets and determine position sizing, integrating Greeks for risk management within the OpenClaw Wheel framework.

Can I use this strategy execution framework for institutional-grade options trading?▼

Yes, the strategy execution framework is designed for institutional-grade AI systems to handle complex, multi-jurisdictional scenarios in options trading, providing disciplined cash-secured puts execution.