arbitrage-audit

Audit business models to locate AI-closing arbitrage gaps and classify risks.

8|1|Updated Mar 30, 2026
One-click install
npx skills add https://github.com/drewid74/ai_skills --skill arbitrage-audit
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: arbitrage-audit
Source: https://github.com/drewid74/ai_skills/tree/main/arbitrage-audit
Command: npx skills add https://github.com/drewid74/ai_skills --skill arbitrage-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you audit your business model for AI-driven competitive threats by identifying which value drivers depend on gaps that AI can close.

Core Features & Use Cases

  • Arbitrage gap classification: Maps each value driver to a closing gap, durable moat, or defensible dependence on proprietary inaccessibility.
  • Time-based risk horizon: Uses a 12–36 month default to stress-test which advantages are most likely to compress soon.
  • Revenue-at-risk scoring: Estimates how much revenue is exposed within 24 months and names the single highest-risk gap that could end the model.
  • Actionable mitigations: Produces concrete priority actions for every closing gap rather than generic reassurance.

Quick Start

Tell the AI: "Audit my business model for AI risk and identify my highest-risk arbitrage gap within a 12–36 month horizon, including revenue-at-risk and specific mitigation actions."

Frequently Asked Questions about arbitrage-audit

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

FAQPage Schema
How do I audit my business model for AI disruption threats?

To audit your business model for AI disruption threats, map each value driver to identify closing arbitrage gaps. This process produces a classified risk table with rationales, closure timelines, and a revenue-at-risk estimate within 24 months.

What is an arbitrage gap in a competitive moat?

An arbitrage gap in a competitive moat is a value driver advantage that AI can close. Auditing identifies these gaps to assess margin compression risks and estimate revenue exposure within a 12 to 36 month horizon.

How do I estimate revenue-at-risk from AI closing competitive gaps?

You estimate revenue-at-risk by stress-testing your value chain against a 12 to 36 month AI disruption timeline. The audit calculates the percentage of revenue exposed within 24 months and names the single highest-risk gap.

Can I get specific mitigation actions for margin compression risks?

Yes, the audit generates concrete prioritized mitigation actions for every identified closing gap. Instead of generic reassurance, it provides actionable steps to defend your competitive moat against AI threats.

What is the best way to assess competitive moat durability for AI risk?

The best way to assess competitive moat durability is classifying value drivers as closing gaps, durable moats, or defensible proprietary dependencies. This classifies which advantages are most likely to compress within 36 months.

When do I need an arbitrage gap analysis for strategic planning?

You need an arbitrage gap analysis when AI threatens your competitive advantage and you must prioritize mitigation actions. It is essential for strategic planning when facing potential margin compression across your value chain.