Generative Engine Optimization (GEO) Citation Benchmark Protocol
Measure, benchmark, and improve your brand's citation frequency and authoritative link presence across AI search engines (Perplexity, ChatGPT Search, Gemini).
Problem it addresses
Build an exhaustive GEO citation audit protocol repository containing: 1) Benchmark query matrix (50 Arabic and 50 English test queries for e-commerce, B2B, and travel), 2) Citation scoring rubric (Direct Link, Named Entity Mention, Sentiment Polarity, Hallucination Risk), 3) Markdown evaluation templates, 4) Python CLI script (geo_scorer.py) that calculates citation density from saved LLM output text files.
Who it is for
PRO operating in high-growth e-commerce, digital publishing, and direct-response marketing across Saudi Arabia, UAE, and Egypt.
What is inside
Key files listed in the README repository architecture:
examples/geo_audit_output.jsonexamples/sample-brand-audit.mdexamples/sample_llm.txtLICENSEprotocol/query-benchmarks-ar-en.jsonprotocol/scoring-rubric.mdREADME.mdtemplates/audit-sheet.mdtests/test_geo_scorer.pytools/geo_scorer.py
How to evaluate and use it
- Read the README first and confirm that the documented problem matches your use case.
- Inspect the listed files to find the data, tools, templates, and tests relevant to your task.
- Follow the repository’s Quick Start and check prerequisites before running commands.
- Compare outputs with documented examples and review limitations before using them in a decision or client workflow.
Quick Start from the README: python -m unittest discover -s tests · python tools/geo_scorer.py --help
Scope and limitations
- LLM Probabilistic Output: Generative engine optimization metrics represent observational heuristic frequencies of LLM citations across temperature settings, not algorithmic guarantees.
- Multi-Engine Volatility: Citation presence varies between Perplexity, ChatGPT Search, and Google Gemini depending on model versions and search index freshing.
- Neutral Attribution Auditing: Brand mentions are scored based on contextual prominence, authoritative source linking, and factual entity clustering.
This page summarizes the available documentation; it does not establish performance or business results. Verify data and prerequisites before use.