A GEO diagnostic report is an evidence-backed audit that analyzes AI engine citations, identifies crawl and content gaps, and delivers prioritized engineering tickets. This sample demonstrates how CiteAura turns a public-site crawl and a labeled AI baseline into actionable fixes, acceptance checks, and a client-ready delivery pack.
A GEO diagnostic scope is the structured boundary separating technical crawlability from generative answer sampling. The report keeps technical diagnosis separate from visibility measurement, so a customer can verify what was checked and what remains unmeasured across public pages, AI answers, machine discovery files, and competitor prompts.
| Evidence | Result | Sampling / source label | Recommended next step |
|---|---|---|---|
| Public pages | 18 eligible pages | Manual · product surface crawl | Use page-level findings to scope tickets. |
| AI answers | 18% mention rate | API · web-grounded retrieval | Review raw answers and citation gaps before changing copy. |
| Machine files | llms.txt missing | Manual · public file check | Generate and review a machine-readable asset. |
| Competitor prompts | 2 takeover gaps | API · parametric knowledge | Confirm competitor facts, then assign a playbook. |
Generative engines omit brand domains when pricing, technical specs, or FAQs are unextractable from the DOM or blocked by robots.txt. Verbatim ground-truth traces from AI engine responses show exactly why competitors are cited while brand pages are omitted.
A GEO action ticket is an engineering task containing concrete acceptance criteria and automated regression checkers. Every recommendation has an owner, an evidence link, and a checker that can reopen the ticket after a regression.
| Ticket | Priority | Action Item & Acceptance Gate | Category | Checker | Status |
|---|---|---|---|---|---|
| GEO-014 | P0 | Allow answer-engine crawlers on public docs Acceptance: re-crawl confirms GPTBot & OAI-SearchBot HTTP 200 without blocking. |
Robots | checker.robots |
In verification |
| GEO-021 | P1 | Expose canonical product facts in JSON-LD Acceptance: Schema graph parses and matches approved brand facts. |
Schema | checker.schema |
Passed |
| GEO-025 | P1 | Publish reviewed /llms.txt machine ingestion file Acceptance: Reachable at root and linked in delivery manifest. |
Machine | checker.llmstxt |
Passed |
| GEO-031 | P2 | Close the highest-value citation gap Acceptance: Comparable re-sample confirms citation link delta. |
Citation | checker.citation |
Passed |
Ticket GEO-014 unblocks AI search crawlers by removing root Disallow directives in robots.txt. Verification confirms GPTBot and OAI-SearchBot return HTTP 200 without blocking rules.
Ticket GEO-021 declares canonical product specifications via Schema.org JSON-LD. Verification confirms the entity graph parses cleanly and matches approved brand facts.
Ticket GEO-025 deploys a reviewed machine-ingestion file at /llms.txt. Verification confirms the file is reachable at root and linked in the delivery manifest.
Ticket GEO-031 closes priority citation gaps where models cite third-party directories. Verification confirms comparable re-sampling records a measurable citation link gain.
Delivery and verification is the formal validation process confirming that recommended site fixes were deployed and re-sampled before client handoff. The final pack contains an audit report, execution plan, ticket log, acceptance checklist, draft risks, and build map. The pack is marked diagnostic-ready until implementation evidence is complete.
| Milestone | Status | What the customer receives |
|---|---|---|
| Diagnostic ready | Complete | Scope, findings, provenance, and prioritized actions. |
| Visibility baseline | Limited | Comparable samples with explicit engine and mode labels. |
| Implementation ready | Review required | Generated assets remain human-reviewed until facts and content are approved. |
Generating a verified GEO diagnostic report starts with an automated site crawl followed by prompt cohort sampling. Start with a free technical diagnostic, then add model API keys for full AI visibility benchmarking.