
mikefutia/ai-visibility-audit
Analytics & monitoringBy · 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
- Download this repo as a ZIP (Code → Download ZIP).
- 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.
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Install
npx skillfish add mikefutia/ai-visibility-audit