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mikefutia/ai-visibility-audit

Analytics & monitoring
20 stars Quality 39 Trend 31

By · more Claude Code systems like this inside

Overview

By · more Claude Code systems like this inside When people ask AI for the best product in your category, does it recommend — or your competitors? This skill runs your category's buyer questions through , detects whether your brand is named/cited, shows , and scores your overall AI visibility — in a dashboard. Python stdlib only; one key (Apify). 1. Download this repo as a ZIP (). 2. Settings → Capabilities → Skills → → drop the zip. Then do the one-time token setup: follow (an Apify API token in a .env). Copy .env.example to .env and paste your token there — .env is gitignored, so it stays local. It asks two questions — your and your — 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/. - Being is the goal (that's a recommendation) — stronger than just being cited in the sources.

README

AI Visibility Audit (Claude skill)

By Mike Futia · more Claude Code systems like this inside SCALE AI

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 few minutes (AI engines are slow). ~$0.30–0.60 per audit.
  • Requires an Apify token (PLAYBOOK.md) + Python 3.

Example run

Run against HexClad (24 buyer questions, US, July 2026):

Result
Overall visibility 28%
Queries containing “HexClad” 100% (12/12)
Queries that don’t name the brand 12% (7/59)
hexclad.com cited as a source 4 of 71 answers
Named most instead All-Clad, Tramontina, GreenPan

A brand that spends heavily on ads was named every time a buyer already knew it, and almost never in the questions that start a purchase — which is the gap this skill is built to find.

Who built this

Made by Mike Futia.

I build production-grade Claude Code systems for ecommerce brands, creative agencies, and performance marketers, and I drop new workflows like this one every week inside my community.

Join 600+ brands and agencies in SCALE AI →

View the full README on GitHub

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Install

npx skillfish add mikefutia/ai-visibility-audit
New to MCP? Start with the mcpskill.org guide →