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ai-discoverability-audit

Audit brand representation across AI search and recommendation systems.

Updated Apr 6, 2026
Search Tags:#brand-audit#ai-search#competitor-benchmarking#re-audit#ai-discoverability#brand-visibility
One-click install
npx skills add https://github.com/mohamednegm0/Musahm-Vault-GTM --skill ai-discoverability-audit-mohamednegm0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-discoverability-audit
Source: https://github.com/mohamednegm0/Musahm-Vault-GTM/tree/main/.claude/skills/ai-marketing-claude-code-skills/ai-discoverability-audit
Command: npx skills add https://github.com/mohamednegm0/Musahm-Vault-GTM --skill ai-discoverability-audit-mohamednegm0

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audit how a brand appears in AI-powered search and recommendations, identify gaps, and define an actionable improvement plan with a re-audit schedule.

Core Features & Use Cases

  • Structured 4-phase workflow including pre-audit hypothesis, direct brand queries, category queries, and competitive benchmarking.
  • Cross-platform testing across ChatGPT, Perplexity, Claude, and Gemini to measure recognition, accuracy, sentiment, and authority.
  • Actionable roadmap with prioritized fixes and a 90-day re-audit plan to monitor progress.

Quick Start

Provide your company name, website, target audience, geography, and top competitors to begin the audit.

Frequently Asked Questions about ai-discoverability-audit

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

FAQPage Schema
How do I audit my brand visibility in AI search engines?▼

To audit brand visibility in AI search, you provide your company name, URL, target audience, geography, and top competitors. The skill runs structured tests across direct and category queries to produce a scored report with prioritized fixes.

What is the best way to benchmark my brand against competitors in AI recommendations?▼

Benchmarking brand visibility against competitors in AI recommendations involves testing across platforms like ChatGPT, Perplexity, Claude, and Gemini. This competitive benchmarking measures recognition, accuracy, sentiment, and authority to highlight gaps.

How does an AI discoverability audit work for category queries?▼

An AI discoverability audit for category queries works by testing how your brand appears in broad industry searches within AI systems. It measures whether AI models recommend your brand when users ask for relevant products or services.

Can I track AI brand representation improvements over time?▼

You can track AI brand representation improvements using a 90-day re-audit plan. After implementing prioritized fixes from the initial audit, the re-audit measures progress in recognition, accuracy, sentiment, and authority across AI platforms.

What inputs do I need to test my brand's visibility in AI search?▼

To test brand visibility in AI search, you need your company name, website URL, target audience, geography, and top competitors. These inputs allow the audit to run pre-audit hypotheses and direct brand queries effectively.

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