Crawler access
A public audit can read robots.txt rules and the availability of selected resources. It cannot confirm whether a specific system will use the page in an answer.
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This page describes publicly detectable technical and editorial signals related to answer-based search: crawler access, document structure, structured data, authorship, sources and freshness. These signals cannot predict citations, rankings or traffic from external AI systems.
Last updated: Maintained by: CometWeb
Which public signals can be checked
This page organizes signals that can be verified from the public version of a site. Availability of a specific check depends on scan scope and configuration.
Answer structure
A public audit can check headings, questions, concise answers and structured data that describe the topic and relationships between information.
Credibility signals
A public audit can detect visible authorship, dates, sources and methodology notes. It does not assess an author’s reputation beyond the analyzed site.
Scope and limitations
Technical readiness helps systems read information, but it does not control the decisions of external search engines or models.
In scope
- Public access rules and response statuses
- HTML structure and detectable Schema.org data
- Visible dates, sources and author information
- Consistency of core indexing signals
Out of scope
- A guarantee of citation, visibility or ranking
- Assessment of private AI-system indexes
- Verification of every author statement
- Replacing research, editing or traditional SEO
Sources and verification method
This panel documents the sources used to define the signals. The documentation was manually reviewed on 2026-07-23.
AI Search readiness means public content is accessible, clearly structured and supported by identifiable sources. This helps crawlers interpret information, but it does not guarantee that ChatGPT, Claude, Perplexity, Gemini or Google will cite the page in an answer.
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The assessment uses the public robots.txt file, declared user-agent rules and availability of analyzed URLs. It describes detectable configuration at scan time. It cannot confirm whether a crawler visited the site or whether its operator added the content to an index.
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No. Robots.txt communicates access rules but does not require crawling, indexing or citation. HTTP status, CDN security, JavaScript requirements and other barriers also affect access. The external system’s operator decides whether and how content is used.
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Schema.org data describes the page type and relationships between elements in a machine-readable format. It can identify an article, author, organization or FAQ. Structured data does not improve weak content and cannot guarantee a rich result or citation.
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No. Llms.txt can point systems toward important public resources, but it does not replace HTML, robots.txt, sitemaps, canonical URLs or internal links. CometWeb treats it as a supplementary content index, not a mechanism that guarantees crawling, indexing or citation.
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No. An audit of public signals can detect access, structure, freshness and credibility elements. It cannot access source-selection algorithms or private indexes belonging to external models. The result can identify measurable barriers, but it does not predict a citation count.
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Logical headings describe document hierarchy and separate questions, answers, limitations and sources. Users and content-processing systems can identify each section’s scope more easily. A heading alone never replaces a complete, factual answer.
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No. Technical SEO still governs access, indexation, canonical URLs, internal linking and document quality. AI Search analysis extends that foundation with answer clarity, authorship, sources and rules for additional crawlers. Both areas depend on a sound technical baseline.
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Operators publish their own user-agent names and configuration guidance. OpenAI, Anthropic and Perplexity document them in the official sources linked on this page. Rules can change, so site owners should compare configuration against each operator’s current documentation.
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The analysis cannot see private indexes, user prompts, model weights or source-selection rules. It also does not measure brand reputation beyond the site. The result covers only public technical and editorial signals detectable during a specific scan.
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Review signals after changing robots.txt, templates, structured data, editorial processes or CDN configuration. Regular rescans help reveal regressions. The appropriate frequency depends on publishing volume and technical change, not an arbitrary optimization schedule.
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A crawler that respects robots.txt should follow the published rules, but behavior depends on the operator and bot type. A robots.txt rule differs from a network block. A CDN or WAF can also reject the request before content is fetched.
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The methodology defines data sources, scan scope, signal interpretation and automated-analysis limitations. Readers can distinguish a technical observation from a recommendation. A public method also makes checks easier to update when operator documentation changes.
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Start with a valid HTTP status, indexable canonical URL, consistent language and readable HTML. Then document authors, dates, sources and content limitations. Finally, validate structured data and crawler rules against each operator’s current documentation.
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Check the publicly detectable signals on your site.
Result scope depends on scan mode and configuration. It does not promise citations or rankings.
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