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How to track how often AI engines cite your site each week with Geo Score

Run a fixed question set weekly and compare cited rates and share of voice.

Credentials. Weekly runs spend your own API credits on each engine, so store keys securely and set a spending limit with each provider.

Who it is forA growth or SEO lead who needs to show whether changes to content or site structure move AI citations over time.

The problemA single query shows a moment in time, and it is hard to tell a real change in citations from noise.

The outcomeA weekly report with cited rate and a 95% interval, share of voice against competitors and sources, and a diff that calls a change only when a paired test supports it.

What you need first

  • Python with pip, to install geo-score==1.8.3 from PyPI (the release pinned in the README)
  • A website domain to score; no key is needed for the free score
  • For citation checks (levels 2 and 3): your own API key for at least one of OpenAI, Perplexity, Gemini, Anthropic or OpenRouter

Steps

  1. Install the pinned release: pip install geo-score==1.8.3 (inferred, check the README)
  2. Write a fixed question list for your buyers and set your own API keys for the engines you use.
  3. Run the watch command on the question set: geo_score.py watch run
  4. Schedule the same command weekly with your scheduler of choice.
  5. Compare reports with the diff function so you only act on changes the paired test supports.

Prompt for your agent

Using the geo-score repo at jianruntech/geo-score, run `geo_score.py watch run` against the question set for <target-domain> using my own API keys. Expected output: a weekly report with cited rate, its 95% interval and share of voice. Verify that the diff between this week and last week is labelled as a real change only when the paired test supports it.

Caveat. Sponsors have not been tested for citation measurements, and levels 2 and 3 need each engine's own search-enabled API, so results depend on the keys you provide.

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