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How to find out why AI engines never mention your brand with Geolook

Sample AI answers, audit the site, and get a gap diagnosis for one brand in about 30 minutes.

Who it is forA marketing lead whose brand is missing from AI answers to category questions like best tools for X.

The problemAI engines leave the brand out of answers, and the team has no way to tell whether the cause is the site, the content, or the channels AI cites.

The outcomeA dashboard showing mention rate, rank, and citation share per engine, plus a four-layer site audit and gap diagnosis that names what to fix first.

What you need first

  • Python 3.9+ on macOS or Linux (Windows via WSL)
  • git
  • Optional: an engine API key, such as DeepSeek or GLM, for automated sampling and drafts

Steps

  1. Run pip3 install requests beautifulsoup4 lxml to install the three required packages.
  2. Run git clone https://github.com/aigclink/geolook.git and then cd geolook.
  3. Run python3 scripts/geo.py new --url https://example.com --market with your brand URL to start a full run.
  4. Run python3 scripts/geo.py ui and open http://127.0.0.1:8765 to review the Status and Diagnosis pages.

Prompt for your agent

Use the geolook repo at <repo path> to run a full GEO diagnosis for <brand URL>. Report the mention rate, the diagnosis type for each buyer question, and the first-fix order from the four-layer audit. Verify that the dashboard at http://127.0.0.1:8765 loads and that the diagnosis page lists the Access layer result.

Caveat. This is a single-machine tool with no accounts or team collaboration, and the suspected-negative flags are leads for human review, not verdicts.

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