options-flow-analyzer
options-flow-analyzer是一款finance方向的AI技能，核心价值是Real vs lottery call separation for options P/C ratio analysis — prevents signal inversion from deep OTM noise，可用于解决开发者在finance领域的实际问题，帮助用户提升效率、自动化重复任务或优化工作流。
Real vs lottery call separation for options P/C ratio analysis — prevents signal inversion from deep OTM noise
mkdir -p ./skills/options-flow-analyzer && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/options-flow-analyzer/SKILL.md -o ./skills/options-flow-analyzer/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
Real vs lottery call separation for options P/C ratio analysis — prevents signal inversion from deep OTM noise
🎯 Best For
- Data analysts
- Business intelligence teams
- Claude users
- AI users
💡 Use Cases
- Finding patterns in customer data
- Creating automated dashboards
- Using options-flow-analyzer in daily workflow
- Automating repetitive finance tasks
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply options-flow-analyzer to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Can this connect to my database directly?
Most data skills accept CSV or JSON input. Database connectors are listed in the Works With section.
How do I install options-flow-analyzer?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/options-flow-analyzer/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Not validating data quality
AI analysis is only as good as your input data. Profile and clean data before analysis.
Not reading the full skill
Skills contain important context and edge cases beyond the quick start.