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AI visibility audit worksheet

The short answer

Use this versioned CSV worksheet to record one row per planned prompt-surface-repeat-window cell and join before/after rows with a stable cell ID. Preserve the exact prompt, conditions, availability, run status, access-evidence pointer, raw-answer reference, visible URLs, separate outcomes, exclusion rule, alternatives, owner, and next decision. Outcome fields stay blank when no inspectable answer exists. The included rows are synthetic; the worksheet does not diagnose a cause or certify provider coverage.

Copy or download version 1.0

This is a manual, reusable template. RankEcho does not import, populate, submit, or execute it automatically. Replace the synthetic example values and preserve the evidence links and limits.

Download audit worksheet (CSV)

audit_version,example_status,observation_id,cell_id,panel_version,window,prompt_id,repeat_index,prompt_text,surface,locale,account_state,planned_cell,availability,run_status,collected_at_utc,access_evidence_artifact,answer_artifact,visible_source_urls,brand_mentioned,owned_link,other_citation,recommendation,absence,named_competitors,exclusion_rule,competing_explanations,owner,next_decision,notes
1.0,synthetic,SYNTHETIC-OBS-001,SYNTHETIC-CELL-001,SYNTHETIC-PANEL-1,before,SYNTHETIC-PROMPT-001,1,"Which inventory platform fits a two-person operations team?",declared-example-surface,en-US,signed-out,yes,available,observed,2026-08-15T09:00:00Z,synthetic-access-before-001.json,synthetic-answer-before-001.txt,https://example.org/roundup,no,no,yes,no,no,"Example Rival A|Example Rival B","Exclude only unavailable or failed attempts from observed-outcome rates.","Crawler access|prompt fit|entity clarity|ordinary answer variability",unassigned,"Verify the selected hypothesis","Illustrative observed row only; replace every value and retain the raw answer outside this CSV."
1.0,synthetic,SYNTHETIC-OBS-002,SYNTHETIC-CELL-001,SYNTHETIC-PANEL-1,after,SYNTHETIC-PROMPT-001,1,"Which inventory platform fits a two-person operations team?",declared-example-surface,en-US,signed-out,yes,unavailable,not-run,2026-08-25T09:05:00Z,synthetic-access-after-001.json,,,,,,,,,"Unavailable surface; exclude this attempt from observed-outcome rates.","Provider availability|account state|collection failure",unassigned,"Re-run only under the registered rule","Illustrative unavailable cell; outcome fields are blank because no inspectable answer exists."
Version 1.0 · 2026-09-02 · Worked example: synthetic, not customer data

Scope box: what does this page cover?

One row per planned prompt-surface-repeat-window cell, joined across windows by a stable cell ID.

The worksheet structures observations; it does not certify completeness or explain a provider's selection.

In scopeOut of scope
Protocol identityCause classification from absence
Availability and run statusSilent denominator changes
Raw evidence referencesUnsupported provider equivalence
Separate outcome labelsForecasts

What are the instructions?

Download or copy version 1.0, replace every synthetic value, and register the panel before collecting the after window. Use one row for every planned cell in each window, including unavailable and failed attempts; reuse the same cell ID for the same prompt, surface, conditions, and repeat index. Keep access records and raw answers in a stable evidence store referenced by the worksheet, and leave answer-outcome fields blank when no inspectable answer exists.

Free audits check Perplexity and Gemini once per prompt. Paid and trialing accounts add ChatGPT, Claude, and Google AI Overviews when those adapters are configured, for up to 5 engines. These product defaults do not determine the scope of a separately run external protocol. Google AI Overviews is reported only when an overview is shown and retrievable; otherwise that cell is marked skipped/unavailable rather than counted as a citation miss.

Which fields are included?

The preview groups fields by the decision they support.

Field groupIncluded columnsWhy keep it
Identityaudit_version, example_status, observation_id, cell_id, panel_version, window, prompt_id, repeat_indexReconstruct and pair the registered sample
Conditionsprompt_text, surface, locale, account_state, collected_at_utcCompare like with like
Run stateplanned_cell, availability, run_statusKeep unavailable and failed cells visible
Evidenceaccess_evidence_artifact, answer_artifact, visible_source_urlsRetain the access record for every attempt and raw answer support for observed cells
Outcomesbrand_mentioned, owned_link, other_citation, recommendation, absence, named_competitorsRecord distinct outcomes only for observed cells
Governanceexclusion_rule, competing_explanations, owner, next_decision, notesKeep exclusions, alternatives, accountability, and handoff visible

What does the worked example show?

The two included rows are illustrative and synthetic. They reuse one stable cell ID across before and after windows and each points to its access-evidence record. The first also points to an observed answer with a third-party URL and named example rivals; the second records an unavailable cell, so its answer artifact, visible URLs, and outcome fields are blank. It remains in the planned-cell count and outside available-case and common-cell outcome denominators.

Replace the example domain, prompt, surface, timestamps, and outcomes. Do not present the sample rows as customer evidence or a benchmark.

How do you copy or download the worksheet?

Use the CSV link for an editable local copy. A renderer may also expose the versioned copy text from the asset specification; both actions return the same deterministic payload.

What deployment validation and proof checks follow completion?

Check that each planned cell has one availability/run state, a retrievable access-evidence pointer, and a UTC timestamp; require retrievable raw-answer pointers for observed cells. Verify that URLs follow a frozen ownership rule and that unavailable or failed rows have blank answer-outcome fields and stay outside available-case and common-cell outcome rates. Preserve the worksheet version and stable cell-key rule used for the baseline.

The worksheet feeds Find and the fixed-prompt retest. It cannot show that a policy, page, or source caused an outcome; link the accepted deployment and report later observations with uncertainty.

What is the version history?

Version 1.0 — 2026-09-02: initial pilot CSV with stable cell IDs, window and repeat fields, availability, access-evidence and answer-artifact pointers, non-overlapping outcomes, exclusions, alternatives, owner, next decision, and a visibly synthetic example.

Where does this asset sit in the workflow?

Use it in Find to freeze the observation record, hand its IDs and evidence to a bounded Fix ticket, and reuse the same panel version in Prove.

Who owns the page, review, tests, and corrections?

Author and accountable publisher: Abiot Y. Derbie, RankEcho founder. Published 2026-09-02; updated 2026-09-02. Independent reviewer: unassigned. No independent external review is claimed.

Tested scope: CSV columns, deterministic payload parity, synthetic row labels, and links; users remain responsible for validating their collected evidence. Material provider and standards statements use the dated source records below. Examples are synthetic, not customer results. Send corrections through /contact; material corrections should update the visible date and version history.

Sources reviewed

Provider eligibility and measurement claims below were checked against primary documentation. These records do not establish a universal selection formula, causation, or a guaranteed ranking, impression, recommendation, or citation.

5 claim-level source records
Checked 2026-09-01 · Primary-source diagnostic review · Confidence is recorded per claim.
Claim reviewedOfficial sourceReview record
Google says normal Search indexing and snippet controls govern eligibility for AI Overviews and AI Mode; there are no additional technical requirements or special AI schema files.Google Search AI features documentationChecked 2026-09-01 · AI features documentation updated 2025-12-10 · Primary-source documentation review; eligibility does not guarantee selection or presentation in an AI feature. · Confidence: High
OpenAI documents OAI-SearchBot for ChatGPT search, GPTBot for potential model training, and ChatGPT-User for user-triggered actions; the controls are independent and robots.txt rules may not apply to ChatGPT-User.OpenAI crawler documentationChecked 2026-09-01 · Current OAI-SearchBot, GPTBot, and ChatGPT-User documentation · Primary-source documentation review; no claim that a permitted bot will index, rank, or cite a page. · Confidence: High
Google says its generative AI Search features use core Search systems: a page must be indexed, snippet-eligible, and included in Search generative AI features in Search Console. It requires no special AI file, content chunking, or AI-specific structured data, and eligibility does not guarantee display.Google guide to generative AI Search optimizationChecked 2026-09-01 · Google Search guidance updated July 10, 2026 · Primary-source documentation review; this is a Google Search eligibility and optimization boundary, not a universal answer-engine formula or ranking guarantee. · Confidence: High
Google's Generative AI performance report counts link impressions from AI Overviews and AI Mode and groups them by page, country, date, or device. It does not document prompt, ranking, citation-cause, or selection-formula fields.Google Search Console: Generative AI performance reportChecked 2026-09-01 · Worldwide rollout stated as August 31, 2026 · Primary-source documentation review; report visibility can be absent with insufficient impressions or exclusion, property and page aggregation can differ, and these link impressions remain distinct from other systems' metrics. · Confidence: High
Bing's AI Performance report counts observed citations and exposes sampled grounding queries, but Microsoft says citation count is not placement, ranking, authority, or page importance.Bing Webmaster Blog: AI PerformanceChecked 2026-09-01 · Public preview announced February 2026 · Primary-source documentation review; Bing metrics are treated as observations with their stated sampling and interpretation limits. · Confidence: High

Frequently asked questions

Is the example real audit data?

No. Every included row is labelled synthetic and must be replaced before use.

Should unavailable runs be deleted?

No. Keep them visible as planned but unavailable cells, leave every answer-outcome field blank, and exclude them from available-case and common-cell outcome denominators.

Does the worksheet explain why a citation is missing?

No. It records bounded observations. Find compares evidence-supported hypotheses; a missing outcome alone does not identify the cause.

Download the audit worksheet →
Last updated 2026-09-02 · RankEcho · Operated by Nexus Decision Systems LLC