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                "level": 2,
                "text": "Minimum report contract"
            },
            {
                "level": 2,
                "text": "Comparison rule"
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                "text": "Generative Engine Optimization"
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        "markdown": "---\ntitle: Reporting AI Search Performance | NRLC.ai\ndescription: How to report citation rate and mention rate with the engine, prompt set, denominator, and observation window required for comparison.\norganization: Neural Command LLC\ncanonical: https://nrlc.ai/en-us/ai-search-measurement/reporting-ai-search-performance/\n---\n\n← Back to measurement\n\n← Back to Measuring Visibility in AI Search\n\nMethod status: This reporting contract is an NRLC operational convention designed to keep repeated observations interpretable.\n\nEach reported number needs four labels: engine, prompt-set identifier, start date, end date. Without those labels, a reader cannot distinguish a site change from prompt-set drift using the reported number alone.\n\nUse citation rate as the primary line. Under the NRLC measurement convention, citation rate = C / P. C is the number of eligible prompts with a qualifying citation; P is the total number of eligible prompts evaluated. Every reported rate must identify the engine, prompt set, denominator, and observation window. Put mention rate second. Put GSC impressions last, as query association, not as citation proof.\n\n## Minimum report contract\n\n- Scope: engine, interface or mode, account state when relevant, and market or language.\n- Prompt set: immutable version identifier, eligible prompt count P, and logged exclusions.\n- Observation window: start date, end date, run cadence, and number of completed runs.\n- Outcomes: citation-positive count C, citation rate C / P, mention-positive count, and mention rate.\n- Evidence: retained response or source-attribution record for every classified observation.\n## Comparison rule\n\nCompare periods only when the engine, interface, prompt-set version, eligibility rules, and denominator are equivalent. If any scope dimension changes, start a new series instead of presenting the difference as performance movement.\n\n## Limitations\n\nThis method measures observed outputs, not private model reasoning. Results can vary by engine, interface, prompt wording, account state, and time. A citation occurrence does not prove that a source caused an answer, produced a click, or generated revenue. NRLC has not published a worked citation-rate example because there is not yet an observation log with a prompt count, engine, dates, citation count, or citation rate. Search Console data may provide separate query and click context, but it is not substituted for citation observations.\n\n## Evidence\n\nMethod\n\nNRLC AI Search Measurement method\n\nObservation window\n\nDeclared per measurement run; no aggregate run is claimed by these method pages.\n\nDataset\n\nVersioned prompt set and answer-observation log supplied by the operator\n\nMethod\n\nFreeze prompts, name the engine and interface, classify observed citation and mention outcomes, preserve exclusions, then calculate C / P over eligible prompts.\n\nAuthors\n\nJoel David Maldonado\n\nSources\n\nNRLC AI Search Measurement method, Google Search Console Performance report documentation\n\nLast verified\n\n2026-09-21\n\nConfidence\n\nfirst-party operational convention; not asserted as an industry standard\n\nLimitations\n\nObserved outputs vary by engine, interface, prompt wording, account state, and time. The method does not expose private model reasoning or establish causal attribution.\n\nView resource\n            Methodology\n\n- Performance report (Search results) — Google Search Console Help\n\n\n---\n\nSource: https://nrlc.ai/en-us/ai-search-measurement/reporting-ai-search-performance/\nPublisher: Neural Command LLC\nLicense: Editorial use with attribution\n"
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