AI Visibility Audit — Security skill for Claude Code

AI Visibility Audit (Claude skill)

By **[Mike Futia](https://www.skool.com/scale-ai/about)** · more Claude Code systems like this inside **[SCALE AI](https://www.skool.com/scale-ai/about)**

When people ask AI for the best product in your category, does it recommend **you** — or your competitors? This skill runs your category's buyer questions through **Google AI Overview, ChatGPT, and Perplexity**, detects whether your brand is named/cited, shows **who AI recommends instead**, and scores your overall AI visibility — in a dashboard. Python stdlib only; one key (Apify).

Install

**Claude Code**

git clone https://github.com/mikefutia/ai-visibility-audit.git ~/.claude/skills/ai-visibility-audit

**Claude Desktop**

1. Download this repo as a ZIP (Code → Download ZIP).
2. Settings → Capabilities → Skills → Upload skill → drop the zip.

Then do the one-time token setup: follow **PLAYBOOK.md** (an Apify API token in a `.env`). Copy `.env.example` to `.env` and paste your token there — `.env` is gitignored, so it stays local.

Use

**run the ai visibility audit**

It asks two questions — your **brand + website** and your **category** — then generates the buyer questions, queries the AI engines, and opens a dashboard with your visibility score, per-engine breakdown, the competitor leaderboard, and how to fix the gaps. Output lands in `./ai-visibility/`.

What's inside

ai-visibility-audit/
├── SKILL.md                 the runbook Claude follows
├── PLAYBOOK.md              one-time Apify token setup
├── .env.example             copy to .env, add your Apify token
├── .gitignore               keeps .env and run output out of git
└── scripts/
    ├── run_audit.py         queries the AI engines, detects brand presence (Apify, stdlib)
    └── render_dashboard.py  renders the dark dashboard (stdlib)

Notes

• Being named in the answer is the goal (that's a recommendation) — stronger than just being cited in the sources.
• Runs take a